ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 51,2025 Issue 7
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- The Future Projections of Extreme Weather, Climate and Water Events and Strategic Responses
- A Review of Downburst Genesis Mechanism and Warning
- The Pattern Structure and Thermodynamic and Dynamic Processes of Severe Storms Associated with Linear Convective Gales
- Analysis on Extremity and Characteristics of the “21·7” Severe Torrential Rain in Henan Province
- Diagnostic Analysis on Water Vapor and Jet Characteristics of the July 2021 Severe Torrential Rain in Henan Province
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2025,51(7):773-788, DOI: 10.7519/j.issn.1000-0526.2024.092401
Abstract:
Thunderstorm gales refer to strong winds with a wind speed ≥17 m·s-1 caused by severe convective weather systems. It is one of mesoscale and microscale severe convective weather causing huge disasters. Understanding their formation mechanisms and conducting accurate nowcasting and early warning are the keys to disaster prevention and mitigation. This article summarizes the existing studies on the formation mechanisms and nowcasting of thunderstorm gales, including synoptic patterns, ambient characteristics, different formation mechanisms and windstorm morphologies, as well as nowcasting technology. It has been found that most thunderstorm gales are generated in supercells, squall lines, and bow echoes through strong downdraft, gust front, momentum transmission, horizontal pressure gradient between outflow and ambient wind, dynamic forcing and superimposed effect of mesoscale vortex, and pumping effect of updraft on low-level warm and moist inflow, etc. On the basis of the above review, the difficulties and much-needed issues of the formation mechanisms and nowcasting of thunderstorm gales are discussed.
Thunderstorm gales refer to strong winds with a wind speed ≥17 m·s-1 caused by severe convective weather systems. It is one of mesoscale and microscale severe convective weather causing huge disasters. Understanding their formation mechanisms and conducting accurate nowcasting and early warning are the keys to disaster prevention and mitigation. This article summarizes the existing studies on the formation mechanisms and nowcasting of thunderstorm gales, including synoptic patterns, ambient characteristics, different formation mechanisms and windstorm morphologies, as well as nowcasting technology. It has been found that most thunderstorm gales are generated in supercells, squall lines, and bow echoes through strong downdraft, gust front, momentum transmission, horizontal pressure gradient between outflow and ambient wind, dynamic forcing and superimposed effect of mesoscale vortex, and pumping effect of updraft on low-level warm and moist inflow, etc. On the basis of the above review, the difficulties and much-needed issues of the formation mechanisms and nowcasting of thunderstorm gales are discussed.
2025,51(7):789-802, DOI: 10.7519/j.issn.1000-0526.2025.032901
Abstract:
South China is an important water vapor transport channel. Studying the water vapor budget in South China is essential for predicting precipitation processes in South China and its neighboring areas, and comprehending the impact of atmospheric circulation changes on weather and climate in China. Based on ERA5 data, the variation trend of water vapor budget and its correlation with precipitation in South China during the recent 40 years (1983-2022) are analyzed. The results show that water vapor in South China is mainly input through its the southern and western boundaries, and output through the northern and eastern boundaries, with the net budget being negative. The water vapor budget shows a declining trend, with a significant decrease in the output from the eastern boundary. In the four seasons, the input and output water vapor budget declines most obviously in spring. Water vapor enters into the South China Region mainly from the Indian Ocean and the Bay of Bengal in the southwest direction and western Pacific in the southwest direction. Water vapor in the middle and lower layers (700 hPa) is primarily transported from the Indian Ocean and the Bay of Bengal, while water vapor in the lower layer (925 hPa) mainly originates from western Pacific. In the recent 40 years, water vapor transport from the Indian Ocean and the Bay of Bengal and western Pacific has been weakening, causing the changes in water vapor transport from the direction of northeast to southwest in South China. Water vapor transport is positively correlated to precipitation in most areas of Guangxi and Guangdong, with correlation coefficient >0.6, of which the strengthening of southwestly water vapor transport is the key reason of precipitation. In addition, there is a trend of wetting in South China, with a 2.32% increase in precipitable water vapor (PWV) during the recent 40 years, which is the result of decrease in total water vapor outflow in the region than that of total inflow. The results of this study can provide a reference for further understanding of water vapor budget changes and abnormal precipitation events in South China.
South China is an important water vapor transport channel. Studying the water vapor budget in South China is essential for predicting precipitation processes in South China and its neighboring areas, and comprehending the impact of atmospheric circulation changes on weather and climate in China. Based on ERA5 data, the variation trend of water vapor budget and its correlation with precipitation in South China during the recent 40 years (1983-2022) are analyzed. The results show that water vapor in South China is mainly input through its the southern and western boundaries, and output through the northern and eastern boundaries, with the net budget being negative. The water vapor budget shows a declining trend, with a significant decrease in the output from the eastern boundary. In the four seasons, the input and output water vapor budget declines most obviously in spring. Water vapor enters into the South China Region mainly from the Indian Ocean and the Bay of Bengal in the southwest direction and western Pacific in the southwest direction. Water vapor in the middle and lower layers (700 hPa) is primarily transported from the Indian Ocean and the Bay of Bengal, while water vapor in the lower layer (925 hPa) mainly originates from western Pacific. In the recent 40 years, water vapor transport from the Indian Ocean and the Bay of Bengal and western Pacific has been weakening, causing the changes in water vapor transport from the direction of northeast to southwest in South China. Water vapor transport is positively correlated to precipitation in most areas of Guangxi and Guangdong, with correlation coefficient >0.6, of which the strengthening of southwestly water vapor transport is the key reason of precipitation. In addition, there is a trend of wetting in South China, with a 2.32% increase in precipitable water vapor (PWV) during the recent 40 years, which is the result of decrease in total water vapor outflow in the region than that of total inflow. The results of this study can provide a reference for further understanding of water vapor budget changes and abnormal precipitation events in South China.
2025,51(7):803-816, DOI: 10.7519/j.issn.1000-0526.2025.022402
Abstract:
Based on the minute precipitation observation data from Wuhan national meteorological stations since 1950s, the sliding accumulation method is used to identify short-duration heavy rainfall events, and the fuzzy identification method is used to determine the rain types of every single rainfall event. In addition, the spatio-temporal characteristics of short-duration heavy rainfall in Wuhan are systematically analyzed from the aspects of occurrence frequency, intensity and rain type, and the influence of urbanization on short-duration heavy rainfall is preliminarily explored. The results show that from 1954 to 2022, the short-duration heavy rainfall events in Wuhan show a small increasing trend, which suggests that the averaged annual frequency of heavy rainfall, annual average heavy precipitation, annual maximum 60-min heavy precipitation and annual maximum single heavy precipitation are 6.9 times, 289.9 mm, 98.0 mm and 282.2 mm, while the increasing rates are 0.3 times per 10 a, 16.7 mm per 10 a, 1.4 mm per 10 a and 0.9 mm per 10 a, respectively. Among them, the frequency and amount of annual heavy precipitation exhibit interdecadal characteristics, approximately presenting a “W” shape of “decrease-increase-decrease-increase”. The occurrence rate and contribution of heavy rainfall lasting for 60-120 min are the largest, being 41.6% and 32.2%, respectively. Heaviest rainfall in Wuhan mainly occurs from late June to mid-July, accounting for 33.6% of the whole year. The frequency of daily heavy rainfall is approximately unimodal, while the peak value occurs in 05:11 BT-05:40 BT, and the trough value occurs in 15:58 BT-16:47 BT. The average minute rainfall intensity is distributed in multi-peaks, with the main peak value appearing in 16:04 BT-17:34 BT, and the trough vlaue could be found in 07:53 BT-08:27 BT. The average minute rain intensity during daytime is greater than that at night, especially during 14:00 BT-20:00 BT. The average frequency of peaks and valleys per minute in spring is earlier than the annual average. In terms of individual rain patterns, the heavy rainfall at each station in Wuhan is dominated by the type Ⅰ and type Ⅳ rain patterns, while the heavy rainfall in 0-60 min is dominated by the type Ⅰ and type Ⅲ, and the heavy rainfall in more than 180 min is mainly type Ⅳ. The spatial variability of short-duration heavy rainfall in Wuhan area is relatively small, and the frequency, duration and precipitation of heavy rainfallin urban area are slightly higher than those in suburban area.
Based on the minute precipitation observation data from Wuhan national meteorological stations since 1950s, the sliding accumulation method is used to identify short-duration heavy rainfall events, and the fuzzy identification method is used to determine the rain types of every single rainfall event. In addition, the spatio-temporal characteristics of short-duration heavy rainfall in Wuhan are systematically analyzed from the aspects of occurrence frequency, intensity and rain type, and the influence of urbanization on short-duration heavy rainfall is preliminarily explored. The results show that from 1954 to 2022, the short-duration heavy rainfall events in Wuhan show a small increasing trend, which suggests that the averaged annual frequency of heavy rainfall, annual average heavy precipitation, annual maximum 60-min heavy precipitation and annual maximum single heavy precipitation are 6.9 times, 289.9 mm, 98.0 mm and 282.2 mm, while the increasing rates are 0.3 times per 10 a, 16.7 mm per 10 a, 1.4 mm per 10 a and 0.9 mm per 10 a, respectively. Among them, the frequency and amount of annual heavy precipitation exhibit interdecadal characteristics, approximately presenting a “W” shape of “decrease-increase-decrease-increase”. The occurrence rate and contribution of heavy rainfall lasting for 60-120 min are the largest, being 41.6% and 32.2%, respectively. Heaviest rainfall in Wuhan mainly occurs from late June to mid-July, accounting for 33.6% of the whole year. The frequency of daily heavy rainfall is approximately unimodal, while the peak value occurs in 05:11 BT-05:40 BT, and the trough value occurs in 15:58 BT-16:47 BT. The average minute rainfall intensity is distributed in multi-peaks, with the main peak value appearing in 16:04 BT-17:34 BT, and the trough vlaue could be found in 07:53 BT-08:27 BT. The average minute rain intensity during daytime is greater than that at night, especially during 14:00 BT-20:00 BT. The average frequency of peaks and valleys per minute in spring is earlier than the annual average. In terms of individual rain patterns, the heavy rainfall at each station in Wuhan is dominated by the type Ⅰ and type Ⅳ rain patterns, while the heavy rainfall in 0-60 min is dominated by the type Ⅰ and type Ⅲ, and the heavy rainfall in more than 180 min is mainly type Ⅳ. The spatial variability of short-duration heavy rainfall in Wuhan area is relatively small, and the frequency, duration and precipitation of heavy rainfallin urban area are slightly higher than those in suburban area.
2025,51(7):817-829, DOI: 10.7519/j.issn.1000-0526.2025.011502
Abstract:
To provide a reference for weather forecasting of major floods in the upper reaches of the Hanjiang River during autumn flood season, based on NCEP/NCAR reanalysis data and conventional meteorological and hydrological observation data, we analyze the water regimen and rainfall characteristics, large-scale circulation characteristics, and causes for flood-causing rainstorm of major floods in the upper reaches of the Hanjiang River during autumn flood season since 2000. The results showed that the flood processes in the Hanjiang River Basin have gradually increased during autumn flood season since the 21st century. The flood-causing rainstorm center in autumn flood season is mainly located in the south and west of the upper reaches of the Hanjiang River, that is, the Micang Mountain and Daba Mountain in the south of the Hanjiang River Basin, the river valley in the upstream of the Ankang Reservoir, and the Danjiang River section at the southern foot of the Waifang Mountain and the westsouth slope of the Funiu Mountain. The peak of floods usually presents in the patterns of single peak, double peak or multiple peak. The duration of a single peak flood process is the shortest, while the duration of a multipeak flood process is the longest. The duration from the onset of maximum precipitation to the appearance of the flood peak is 43 h on average. When the initial inflow exceeds 4500 m3·s-1, the time required for the formation of the flood peak will be greatly shortened. From the perspective of large-scale circulation characteristics, the abnormal precipita-tion in the upper reaches of the Hanjiang River in autumn flood season is closely correlated to the strong blocking system in the mid-high latitudes over the Eurasia, the stronger and westward Western Pacific subtropical high, the northward South Asia high and subtropical westerly jet flow. The high-level divergence large-value area corresponds to the upper reaches of the Hanjiang River. The vertical motion from low to high levels is enhanced, which is conducive to the occurrence of flood-causing rainstorm. The water vapor transported northward from the Arabian Sea through the Indian Peninsula and the southern South China Sea and westward from the Western Pacific in autumn flood season flood year in the upper reaches of the Hanjiang River has increased abnormally, providing an unusually sufficient water vapor supply for the occurrence of flood-causing rainstorm.
To provide a reference for weather forecasting of major floods in the upper reaches of the Hanjiang River during autumn flood season, based on NCEP/NCAR reanalysis data and conventional meteorological and hydrological observation data, we analyze the water regimen and rainfall characteristics, large-scale circulation characteristics, and causes for flood-causing rainstorm of major floods in the upper reaches of the Hanjiang River during autumn flood season since 2000. The results showed that the flood processes in the Hanjiang River Basin have gradually increased during autumn flood season since the 21st century. The flood-causing rainstorm center in autumn flood season is mainly located in the south and west of the upper reaches of the Hanjiang River, that is, the Micang Mountain and Daba Mountain in the south of the Hanjiang River Basin, the river valley in the upstream of the Ankang Reservoir, and the Danjiang River section at the southern foot of the Waifang Mountain and the westsouth slope of the Funiu Mountain. The peak of floods usually presents in the patterns of single peak, double peak or multiple peak. The duration of a single peak flood process is the shortest, while the duration of a multipeak flood process is the longest. The duration from the onset of maximum precipitation to the appearance of the flood peak is 43 h on average. When the initial inflow exceeds 4500 m3·s-1, the time required for the formation of the flood peak will be greatly shortened. From the perspective of large-scale circulation characteristics, the abnormal precipita-tion in the upper reaches of the Hanjiang River in autumn flood season is closely correlated to the strong blocking system in the mid-high latitudes over the Eurasia, the stronger and westward Western Pacific subtropical high, the northward South Asia high and subtropical westerly jet flow. The high-level divergence large-value area corresponds to the upper reaches of the Hanjiang River. The vertical motion from low to high levels is enhanced, which is conducive to the occurrence of flood-causing rainstorm. The water vapor transported northward from the Arabian Sea through the Indian Peninsula and the southern South China Sea and westward from the Western Pacific in autumn flood season flood year in the upper reaches of the Hanjiang River has increased abnormally, providing an unusually sufficient water vapor supply for the occurrence of flood-causing rainstorm.
2025,51(7):830-839, DOI: 10.7519/j.issn.1000-0526.2025.041501
Abstract:
Based on ERA5 hourly reanalysis data of atmospheric circulation field with horizontal resolution of 0.25°×0.25°, geopotential height data and temperature, the northeast cold vortex process and its climate change characteristics from 1979 to 2023 are analyzed. The results reveal that there are more northeast cold vortexes in the early 1990s and mid-2000s, and relatively fewer in the 2010s. The frequency of northeast cold vortex shows higher in the warm season than in the cold season, with the highest in June and the lowest in March. Its average duration is 4 days, with the shortest duration in April and the longest duration in January. The northeast cold vortex is mostly generated in the range of 45°-60°N, 100°-120°E and dies out within 40°-55°N near 140°E. The center of the northeast cold vortex is mainly concentrated within 45°-55°N and 115°-135°E. The northeast cold vortex mainly moves towards the east and southeast. To the east of 120°E, the average intensity of the cold vortex is stronger and weaker to the west. The intensity distribution of the northeast cold vortex within the year is stronger in the cold season than in the warm season. The intensity difference between the grids in the analysis area is the largest in March, and the smallest in June. The annual average intensity and circulation of northeast cold vortex show a significant weakening trend from 1979 to 2023. There is a significant negative correlation between the intensity of the northeast cold vortex and the temperature in most months in Northeast China, but a significant positive correlation with precipitation in April and June.
Based on ERA5 hourly reanalysis data of atmospheric circulation field with horizontal resolution of 0.25°×0.25°, geopotential height data and temperature, the northeast cold vortex process and its climate change characteristics from 1979 to 2023 are analyzed. The results reveal that there are more northeast cold vortexes in the early 1990s and mid-2000s, and relatively fewer in the 2010s. The frequency of northeast cold vortex shows higher in the warm season than in the cold season, with the highest in June and the lowest in March. Its average duration is 4 days, with the shortest duration in April and the longest duration in January. The northeast cold vortex is mostly generated in the range of 45°-60°N, 100°-120°E and dies out within 40°-55°N near 140°E. The center of the northeast cold vortex is mainly concentrated within 45°-55°N and 115°-135°E. The northeast cold vortex mainly moves towards the east and southeast. To the east of 120°E, the average intensity of the cold vortex is stronger and weaker to the west. The intensity distribution of the northeast cold vortex within the year is stronger in the cold season than in the warm season. The intensity difference between the grids in the analysis area is the largest in March, and the smallest in June. The annual average intensity and circulation of northeast cold vortex show a significant weakening trend from 1979 to 2023. There is a significant negative correlation between the intensity of the northeast cold vortex and the temperature in most months in Northeast China, but a significant positive correlation with precipitation in April and June.
2025,51(7):840-851, DOI: 10.7519/j.issn.1000-0526.2024.123102
Abstract:
Constructing a quantitative index to characterize the intensity of low-temperature freezing injury of winter wheat and revealing its spatio-temporal variation characteristics is crucial for scientific prevention of low-temperature freezing injury of winter wheat. Based on the winter daily meteorological observation data in Jiangsu Province from 1972 to 2022, disaster data of freezing injury of winter wheat from 2010 to 2022, and yield data of historical extreme freezing injury years, this paper determines the impact weights of disaster-causing factors on different types of freezing injury, and establishes three main types of freezing injury indices, including low-temperature freezing injury (last November to March), freezing injury during overwintering period (late December to mid February), and freezing injury during regreening-jointing period (late February to March). Multiple mathematical statistical methods such as Mann-Kendall mutation test and k-means clustering are used to conduct spatio-temporal analysis and evaluation of low-temperature freezing injury of winter wheat. Based on the ranking of freezing injury intensity during overwintering period and regreening-jointing period, two types of freezing injuries are classified into three levels, which are mild, moderate and severe. The results show that there is a significant difference in the intensity indices of low-temperature freezing injury between the north and the south of Jiangsu Province. They can be divided into high-risk zone (Xuzhou, Lianyungang, Suqian, Huai’an and Yancheng), medium-risk zone (Nanjing, Yangzhou, Taizhou and Nantong), and low-risk zone (Zhenjiang, Changzhou, Suzhou and Wuxi). Over the past 51 years, the intensity index of low-temperature freezing injury of winter wheat experienced a sudden decline in 1989 in Jiangsu Province. The severe freezing injury during overwintering period and regreening-jointing period both jumped from a relatively more injury period to a relatively fewer injury period in the late 1980s. Although the frequency of freezing injury during the development period of winter wheat has shown a decreasing trend, the intensity of extreme freezing injury has been increasing, and even the freezing injury index in some areas exceeded the historical record of 1977 in the 21st century.
Constructing a quantitative index to characterize the intensity of low-temperature freezing injury of winter wheat and revealing its spatio-temporal variation characteristics is crucial for scientific prevention of low-temperature freezing injury of winter wheat. Based on the winter daily meteorological observation data in Jiangsu Province from 1972 to 2022, disaster data of freezing injury of winter wheat from 2010 to 2022, and yield data of historical extreme freezing injury years, this paper determines the impact weights of disaster-causing factors on different types of freezing injury, and establishes three main types of freezing injury indices, including low-temperature freezing injury (last November to March), freezing injury during overwintering period (late December to mid February), and freezing injury during regreening-jointing period (late February to March). Multiple mathematical statistical methods such as Mann-Kendall mutation test and k-means clustering are used to conduct spatio-temporal analysis and evaluation of low-temperature freezing injury of winter wheat. Based on the ranking of freezing injury intensity during overwintering period and regreening-jointing period, two types of freezing injuries are classified into three levels, which are mild, moderate and severe. The results show that there is a significant difference in the intensity indices of low-temperature freezing injury between the north and the south of Jiangsu Province. They can be divided into high-risk zone (Xuzhou, Lianyungang, Suqian, Huai’an and Yancheng), medium-risk zone (Nanjing, Yangzhou, Taizhou and Nantong), and low-risk zone (Zhenjiang, Changzhou, Suzhou and Wuxi). Over the past 51 years, the intensity index of low-temperature freezing injury of winter wheat experienced a sudden decline in 1989 in Jiangsu Province. The severe freezing injury during overwintering period and regreening-jointing period both jumped from a relatively more injury period to a relatively fewer injury period in the late 1980s. Although the frequency of freezing injury during the development period of winter wheat has shown a decreasing trend, the intensity of extreme freezing injury has been increasing, and even the freezing injury index in some areas exceeded the historical record of 1977 in the 21st century.
2025,51(7):852-864, DOI: 10.7519/j.issn.1000-0526.2025.010801
Abstract:
Liquid water content (LWC), median volume diameter (MVD), outside air temperature and other meteorological conditions are important meteorological factors affecting the intensity of aircraft icing, and are also the basic condition for measuring and evaluating whether the aircraft natural icing certification flight test meets the natiural icing certification flight test standard. The meteorological conditions of a domestic large passenger aircraft natural icing test flight on 22 January 2022 are analyzed based on multi-source meteorological data. The results show that the high-altitude weather background of this natural icing certification flight test was a latitudinal fluctuating airflow, cooperated with the cold air inversion near the surface, forcing the southwest warm and humid airflow in the middle and lower layers of the troposphere to lift northward, and forming a wide range of non-precipitation layered cloud system. The height of the cloud top in the test area developed from 3.0 km to 4.6 km, and an inversion layer existed in 1.3-3.5 km, with the lowest temperature at the cloud top being -14℃, no precipitation in the cloud, and the radar basic reflectivity＜15 dBz. The ambient temperature of the two times of fights penetrating the cloud and the standby flight in the cloud for 45 min hovering flights was from -10 to -7℃, with the relative humidity＞80%, and the scattering of water vapor flux＜-2.73×10-7 g·s-1·hPa-1·cm-2. This provided ideal temperature and water vapor conditions for the natural icing test flights, and a weak updraft of -0.2 Pa·s-1 in the middle and upper part of the cloud layer contributed to the growth of the supercooled cloud droplets. The DMT sounding data show that the supercooled cloud is inhomogeneous both vertically and horizontally, and that the supercooled cloud droplets were dominant inside the cloud, where the mean value of LWC was 0.23-0.27 g·m-3, and the mean value of MVD was 15.82-15.93 μm. So there are aircraft natural icing meteorological conditions in winter under the influence of the “inversion + inversion trough” weather system, which is conducive to carrying out aircraft natural icing certification tests in Shaanxi.
Liquid water content (LWC), median volume diameter (MVD), outside air temperature and other meteorological conditions are important meteorological factors affecting the intensity of aircraft icing, and are also the basic condition for measuring and evaluating whether the aircraft natural icing certification flight test meets the natiural icing certification flight test standard. The meteorological conditions of a domestic large passenger aircraft natural icing test flight on 22 January 2022 are analyzed based on multi-source meteorological data. The results show that the high-altitude weather background of this natural icing certification flight test was a latitudinal fluctuating airflow, cooperated with the cold air inversion near the surface, forcing the southwest warm and humid airflow in the middle and lower layers of the troposphere to lift northward, and forming a wide range of non-precipitation layered cloud system. The height of the cloud top in the test area developed from 3.0 km to 4.6 km, and an inversion layer existed in 1.3-3.5 km, with the lowest temperature at the cloud top being -14℃, no precipitation in the cloud, and the radar basic reflectivity＜15 dBz. The ambient temperature of the two times of fights penetrating the cloud and the standby flight in the cloud for 45 min hovering flights was from -10 to -7℃, with the relative humidity＞80%, and the scattering of water vapor flux＜-2.73×10-7 g·s-1·hPa-1·cm-2. This provided ideal temperature and water vapor conditions for the natural icing test flights, and a weak updraft of -0.2 Pa·s-1 in the middle and upper part of the cloud layer contributed to the growth of the supercooled cloud droplets. The DMT sounding data show that the supercooled cloud is inhomogeneous both vertically and horizontally, and that the supercooled cloud droplets were dominant inside the cloud, where the mean value of LWC was 0.23-0.27 g·m-3, and the mean value of MVD was 15.82-15.93 μm. So there are aircraft natural icing meteorological conditions in winter under the influence of the “inversion + inversion trough” weather system, which is conducive to carrying out aircraft natural icing certification tests in Shaanxi.
2025,51(7):865-875, DOI: 10.7519/j.issn.1000-0526.2025.022101
Abstract:
On 28 December 2022, multiple vehicle collisions occurred on the Zhengxin Yellow River Bridge due to heavy fog. Based on ERA5 reanalysis and surface observation data, the method of disturbance-based synoptic analysis is used to diagnose and analyze the heavy fog episode. The results show that the heavy fog weather had the characteristics of strong local suddenness, low visibility, and significant nighttime cooling. The low visibility caused by heavy fog and the ice and slippery bridge deck caused by high humidity and low temperature were the meteorological reasons for the vehicle rear-end collision accidents. The synoptic conditions were stable, with weak cold air at the bottom and warm ridges in the southwest transport of warm and humid airflow into the foggy area, and the circulation pattern was favorable for the generation of fog. The water vapor flux near the bridge was high, and there existed weak water vapor convergence, shallow inversion layer and strong radiation cooling effect, which provided favorable dynamic, water vapor, and thermal conditions for the occurrence and persistence of radiation fog. The disturbance signals of wind speed, relative humidity, temperature and specific humidity can better reflect the predictable signals of heavy fog compared to the corresponding disturbance signals. The comprehensive analysis of multiple disturbance factors can help determine the dissipation time of fog.
On 28 December 2022, multiple vehicle collisions occurred on the Zhengxin Yellow River Bridge due to heavy fog. Based on ERA5 reanalysis and surface observation data, the method of disturbance-based synoptic analysis is used to diagnose and analyze the heavy fog episode. The results show that the heavy fog weather had the characteristics of strong local suddenness, low visibility, and significant nighttime cooling. The low visibility caused by heavy fog and the ice and slippery bridge deck caused by high humidity and low temperature were the meteorological reasons for the vehicle rear-end collision accidents. The synoptic conditions were stable, with weak cold air at the bottom and warm ridges in the southwest transport of warm and humid airflow into the foggy area, and the circulation pattern was favorable for the generation of fog. The water vapor flux near the bridge was high, and there existed weak water vapor convergence, shallow inversion layer and strong radiation cooling effect, which provided favorable dynamic, water vapor, and thermal conditions for the occurrence and persistence of radiation fog. The disturbance signals of wind speed, relative humidity, temperature and specific humidity can better reflect the predictable signals of heavy fog compared to the corresponding disturbance signals. The comprehensive analysis of multiple disturbance factors can help determine the dissipation time of fog.
2025,51(7):876-890, DOI: 10.7519/j.issn.1000-0526.2025.060601
Abstract:
In the winter of 2024/2025, the mean temperature in China was 0.4℃ higher than normal with significant intra-seasonal variations. Average precipitation was 41.1% lower than normal, and the regions south of the Yangtze River experienced persistently less precipitation. Atmospheric circulation patterns in the mid-to-high latitudes over Eurasia have shown staged differences in this winter. In December 2024, the Arctic Oscillation was in a negative phase and the East Asian trough and Siberian high were stronger than usual. All the three got weakened in January 2025 and then strengthened again in February. Especially in February, the negative phase of the Arctic Oscillation reached the strongest stage of this winter while the activity of Eurasian blocking high was significantly enhanced. These factors collectively triggered an obvious shift in the temperature of China from warmer to colder conditions. In the 2024/2025 winter, the low-latitude atmosphere responded significantly to the La Nina-type sea surface temperature anomalies in the equatorial central-eastern Pacific. Persistent cyclonic circulation anomalies dominated the lower troposphere from the Philippines to the South China Sea, while the regions south of the Yangtze River in China remained consistently influenced by northerly wind anomalies. Coupled with persistently weak activity of the India-Burma trough, the influences of multiple circulation conditions led to sustained moisture transport deficits and significantly reduced precipitation in eastern China, particularly in the southern part.
In the winter of 2024/2025, the mean temperature in China was 0.4℃ higher than normal with significant intra-seasonal variations. Average precipitation was 41.1% lower than normal, and the regions south of the Yangtze River experienced persistently less precipitation. Atmospheric circulation patterns in the mid-to-high latitudes over Eurasia have shown staged differences in this winter. In December 2024, the Arctic Oscillation was in a negative phase and the East Asian trough and Siberian high were stronger than usual. All the three got weakened in January 2025 and then strengthened again in February. Especially in February, the negative phase of the Arctic Oscillation reached the strongest stage of this winter while the activity of Eurasian blocking high was significantly enhanced. These factors collectively triggered an obvious shift in the temperature of China from warmer to colder conditions. In the 2024/2025 winter, the low-latitude atmosphere responded significantly to the La Nina-type sea surface temperature anomalies in the equatorial central-eastern Pacific. Persistent cyclonic circulation anomalies dominated the lower troposphere from the Philippines to the South China Sea, while the regions south of the Yangtze River in China remained consistently influenced by northerly wind anomalies. Coupled with persistently weak activity of the India-Burma trough, the influences of multiple circulation conditions led to sustained moisture transport deficits and significantly reduced precipitation in eastern China, particularly in the southern part.
2025,51(7):891-900, DOI: 10.7519/j.issn.1000-0526.2025.063001
Abstract:
In April 2025, the Northern Hemisphere polar vortex exhibited a monopole with an eccentric distribution and was stronger than normal. Over the Eurasian mid-to-high latitudes, the circulation pattern featured a pattern of “two troughs and one ridge”. The ridge between the East European trough and the East Asian trough was broad and flat. The national average temperature across the whole China was 13℃, which is 1.5℃ higher than the climatological average (11.5℃) in the same period. The national average precipitation was 38.9 mm, 11% less than the climatological average (43.6 mm). The main precipitation areas were located in Jiangnan and the northern parts of South China. The precipitation of Eastern Inner Mongolia and Northeast China was above the normal level. During this month, there were five major sand-dust processes, two cold air, three heavy rainfall processes, and four severe convective weather processes. Notably, the strong sandstorm process from 10 to 14 April was characterized by its long duration, high intensity and extensive dust coverage. This event was also accompanied by widespread strong winds and a significant drop in temperature.
In April 2025, the Northern Hemisphere polar vortex exhibited a monopole with an eccentric distribution and was stronger than normal. Over the Eurasian mid-to-high latitudes, the circulation pattern featured a pattern of “two troughs and one ridge”. The ridge between the East European trough and the East Asian trough was broad and flat. The national average temperature across the whole China was 13℃, which is 1.5℃ higher than the climatological average (11.5℃) in the same period. The national average precipitation was 38.9 mm, 11% less than the climatological average (43.6 mm). The main precipitation areas were located in Jiangnan and the northern parts of South China. The precipitation of Eastern Inner Mongolia and Northeast China was above the normal level. During this month, there were five major sand-dust processes, two cold air, three heavy rainfall processes, and four severe convective weather processes. Notably, the strong sandstorm process from 10 to 14 April was characterized by its long duration, high intensity and extensive dust coverage. This event was also accompanied by widespread strong winds and a significant drop in temperature.
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Technological Advances in National-Level Intelligent Digital Weather Forecasting Operational Systems
JIN Ronghua, CAO Yong, ZHAO Ruixia, DAI Kan, GUO Yunqian, XU Jun, ZENG Xiaoqing, WANG Yu, TANG Jian, WEI Qing
Available online: August 08, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.063003
Abstract:
Intelligent digital weather forecasting is a key means to support meteorological service. Countries around the world are actively developing new-generation seamless forecasting technology systems and promoting the application of artificial intelligence in the meteorological field. China has established a relatively complete intelligent digital weather forecasting operation system, achieving seamless forecasting for the near-surface and three-dimensional meteorological elements with a resolution of 1-km across the country and 5-km globally, covering a time range of 0-30 days. By developing adaptable technologies through the strategy of implementing different strategies at different time scales and integrating multi-source forecast, remarkable results have been achieved. A unified, standardized, and modularly expandable intelligent digital general technology framework has been constructed, constructing more than 30 types of algorithms and supporting "low-code" deployment, which plays an important role in major event support and extreme weather forecasting. The in-depth application of artificial intelligence technology has significantly improved forecasting performance in short-term and short-to-medium-term precipitation forecasting, severe convective weather forecasting, and disastrous gale forecasting by leveraging deep learning models. Progress has also been made in refined downscaling technology. At the same time, the data fusion and integration technology has continued to develop, and the intelligent integration of objective and subjective forecasting has developed to enhance the ability to forecast disastrous weather. China"s intelligent digital forecasting has improved the accuracy by 10% - 31% compared with the EC_IFS and CMA models and is widely applied in many fields. However, it still faces challenges. In the future, breakthroughs will be made in technologies related to the forecasting of disastrous and transitional weather, low-altitude hundreds-meter-resolution refined downscaling forecasting, industry-specific weather and risk forecasting, and the integrated platform with the meteorological "intelligent brain" as the core.
Intelligent digital weather forecasting is a key means to support meteorological service. Countries around the world are actively developing new-generation seamless forecasting technology systems and promoting the application of artificial intelligence in the meteorological field. China has established a relatively complete intelligent digital weather forecasting operation system, achieving seamless forecasting for the near-surface and three-dimensional meteorological elements with a resolution of 1-km across the country and 5-km globally, covering a time range of 0-30 days. By developing adaptable technologies through the strategy of implementing different strategies at different time scales and integrating multi-source forecast, remarkable results have been achieved. A unified, standardized, and modularly expandable intelligent digital general technology framework has been constructed, constructing more than 30 types of algorithms and supporting "low-code" deployment, which plays an important role in major event support and extreme weather forecasting. The in-depth application of artificial intelligence technology has significantly improved forecasting performance in short-term and short-to-medium-term precipitation forecasting, severe convective weather forecasting, and disastrous gale forecasting by leveraging deep learning models. Progress has also been made in refined downscaling technology. At the same time, the data fusion and integration technology has continued to develop, and the intelligent integration of objective and subjective forecasting has developed to enhance the ability to forecast disastrous weather. China"s intelligent digital forecasting has improved the accuracy by 10% - 31% compared with the EC_IFS and CMA models and is widely applied in many fields. However, it still faces challenges. In the future, breakthroughs will be made in technologies related to the forecasting of disastrous and transitional weather, low-altitude hundreds-meter-resolution refined downscaling forecasting, industry-specific weather and risk forecasting, and the integrated platform with the meteorological "intelligent brain" as the core.
Available online: August 07, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.080301
Abstract:
In this paper, a parallel chunking processing scheme is designed for the compression/decompression process by adopting OpenMP technology based on a conventional PC workstation as a benchmark, and the compression and decompression time of the data can be reduced to about 1/5 and 1/8 of the single-threaded one when the number of chunks reaches 16 under a 12-core/24-threaded CPU. For the decoding process, the results of parallel processing by PPI, radial and distance banks are compared, and it is found that the parallel processing scheme on radial is optimal, which can reduce the decoding time to about 1/8 of the single-threaded one. Through the application of the above two parallel optimization techniques, the pressure of radar base data in data transmission and preprocessing can be significantly reduced, and the data loading performance of the radar software can also be enhanced to improve the interactive experience of the radar analysis software based on base data.
In this paper, a parallel chunking processing scheme is designed for the compression/decompression process by adopting OpenMP technology based on a conventional PC workstation as a benchmark, and the compression and decompression time of the data can be reduced to about 1/5 and 1/8 of the single-threaded one when the number of chunks reaches 16 under a 12-core/24-threaded CPU. For the decoding process, the results of parallel processing by PPI, radial and distance banks are compared, and it is found that the parallel processing scheme on radial is optimal, which can reduce the decoding time to about 1/8 of the single-threaded one. Through the application of the above two parallel optimization techniques, the pressure of radar base data in data transmission and preprocessing can be significantly reduced, and the data loading performance of the radar software can also be enhanced to improve the interactive experience of the radar analysis software based on base data.
Available online: August 07, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.072802
Abstract:
The heavy rain events in North China include regional or valley torrential rain, also contain local strong precipitation only covering several hundreds to thousands km2 area. Essentially, the heavy rain events result in interaction among multi-scale synoptic systems with diversity of dynamical structures. However, it is not easy to resolve the interaction processes of every torrential rain event. On the views of the multi-scale synoptic systems and their interactions, the paper sums up the main mechanisms of heavy rainfall in North China by reconstructing interrelated research achievements：(1) Synoptic scale systems act as controlling functions in large area torrential rainfall processes. Their dynamical properties constructed by variously essential factors play leading roles on large scale moisture convergence strength,the ascending motion intensity and the duration; As far as the rainfall intensity and the location of extreme precipitation during a heavy rain event, the mesoscale systems are decisive factors. They are possible to be derived by the interaction of synoptic scale systems, induced by the complex underground surface such as terrains, urbans and interface between land and sea, and engendered by feedback effect of local strength precipitation; To the extreme precipitation intensity during heavy rain events over North China, the generation, development, structure evolution and organization of deep convective storms are the key factors. (2) The exceptionally complex nonlinear interaction processes exist in every torrential rain events over North China by variously interactions among the different scale synoptic systems and complicated underground forcing. It is actually difficult that any unitary system or isolated dynamical process are perfectly separated from the complex interaction whether by actual observed data or numerical simulation, in other words, the complex nonlinear interaction process itself is a weather life system built by diversity feedbacks each other. Some scientific themes on heavy precipitation events in North China, which should be resolved in future, are discussed in last part of the paper.
The heavy rain events in North China include regional or valley torrential rain, also contain local strong precipitation only covering several hundreds to thousands km2 area. Essentially, the heavy rain events result in interaction among multi-scale synoptic systems with diversity of dynamical structures. However, it is not easy to resolve the interaction processes of every torrential rain event. On the views of the multi-scale synoptic systems and their interactions, the paper sums up the main mechanisms of heavy rainfall in North China by reconstructing interrelated research achievements：(1) Synoptic scale systems act as controlling functions in large area torrential rainfall processes. Their dynamical properties constructed by variously essential factors play leading roles on large scale moisture convergence strength,the ascending motion intensity and the duration; As far as the rainfall intensity and the location of extreme precipitation during a heavy rain event, the mesoscale systems are decisive factors. They are possible to be derived by the interaction of synoptic scale systems, induced by the complex underground surface such as terrains, urbans and interface between land and sea, and engendered by feedback effect of local strength precipitation; To the extreme precipitation intensity during heavy rain events over North China, the generation, development, structure evolution and organization of deep convective storms are the key factors. (2) The exceptionally complex nonlinear interaction processes exist in every torrential rain events over North China by variously interactions among the different scale synoptic systems and complicated underground forcing. It is actually difficult that any unitary system or isolated dynamical process are perfectly separated from the complex interaction whether by actual observed data or numerical simulation, in other words, the complex nonlinear interaction process itself is a weather life system built by diversity feedbacks each other. Some scientific themes on heavy precipitation events in North China, which should be resolved in future, are discussed in last part of the paper.
Available online: August 07, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.032401
Abstract:
This paper reviews the challenges in forecast services for major events in China over the past two decades. The main conclusions include: In conventional "fixed-time and fixed-location" weather element forecasting scenarios, the forecast challenges primarily focus on convection generation and dissipation or the occurrence of weak precipitation. Over short-term periods (12h or longer), the weather situation forecast provided by numerical models remains an important basis for decision-making, and the support from high-resolution numerical model products is indispensable. whereas in short-time or nowcasting, observational data and the comprehensive analytical capabilities of the forecasting team are more critical; In special "fixed-time and fixed-location" forecasting scenarios involving clouds, local winds, and local visibility, due to inadequate observational coverage, limited forecast capabilities of numerical models, and the lack of targeted objective forecasting methods at this stage, the forecast experience of the forecasting team, combined with observations and weather situation analysis, is crucial for successful service, especially in overseas on-site service support, regardless of whether it is short-time or nowcasting; With increased observational system coverage, improved accurate forecasting capabilities of numerical models, and the development of targeted objective forecasting methods including AI, special element forecasting scenarios will gradually transition into conventional element forecasting scenarios, and the leading role of the forecasting team will also gradually shift to short-time or nowcasting . To meet the meteorological support needs for various major events in the future, it is necessary to strengthen the construction of a three-dimensional full-element observation system, enhance the accurate forecasting capabilities of numerical models, promote the development of targeted objective forecasting technologies, and build a forecasting team with continuous self-learning, high generalization abilities, and strong communication skills.
This paper reviews the challenges in forecast services for major events in China over the past two decades. The main conclusions include: In conventional "fixed-time and fixed-location" weather element forecasting scenarios, the forecast challenges primarily focus on convection generation and dissipation or the occurrence of weak precipitation. Over short-term periods (12h or longer), the weather situation forecast provided by numerical models remains an important basis for decision-making, and the support from high-resolution numerical model products is indispensable. whereas in short-time or nowcasting, observational data and the comprehensive analytical capabilities of the forecasting team are more critical; In special "fixed-time and fixed-location" forecasting scenarios involving clouds, local winds, and local visibility, due to inadequate observational coverage, limited forecast capabilities of numerical models, and the lack of targeted objective forecasting methods at this stage, the forecast experience of the forecasting team, combined with observations and weather situation analysis, is crucial for successful service, especially in overseas on-site service support, regardless of whether it is short-time or nowcasting; With increased observational system coverage, improved accurate forecasting capabilities of numerical models, and the development of targeted objective forecasting methods including AI, special element forecasting scenarios will gradually transition into conventional element forecasting scenarios, and the leading role of the forecasting team will also gradually shift to short-time or nowcasting . To meet the meteorological support needs for various major events in the future, it is necessary to strengthen the construction of a three-dimensional full-element observation system, enhance the accurate forecasting capabilities of numerical models, promote the development of targeted objective forecasting technologies, and build a forecasting team with continuous self-learning, high generalization abilities, and strong communication skills.
Available online: July 27, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.062601
Abstract:
Taking into account the relationships between model temperature forecasts, model topography, observed temperatures, and actual topography, a dynamically approximated vertical rate correction method for the 2 m temperature that evolves over space and time has been designed. A correction experiment is conducted for Chongqing in 2023. Evaluation of ECMWF model forecasts show that the spatial distribution of forecast skill for maximum and minimum 2 m temperatures is similar, but forecast skill for maximum temperature is significantly worse than for minimum temperature. Additionally, forecast skill declines with increasing forecast lead time. A strong correlation is found between model topographic elevation bias and temperature forecast bias; areas with smaller elevation bias tend to exhibit better forecast skill, and vice versa. Comparative research reveals that the correction scheme based on dynamically approximated vertical rate significantly outperforms the scheme based on constant vertical rate. Both schemes improve the ECMWF model temperature forecasts, with better correction performance for maximum temperatures than for minimum temperatures. Compared to the raw model forecasts, the corrected results based on dynamically approximated vertical rate have increased the 10-day average forecast accuracy of maximum and minimum temperatures by 12.71% and 8.3%, respectively, and reduced the mean absolute error by 0.68°C and 0.3°C, respectively. The monthly average forecast accuracy of the maximum temperature for 24 h forecast lead time has increased by 20.34%. The minimum temperature has increased by 14.44% on average. Overall, the corrected temperature forecasts are more stable. The correction scheme based on dynamically approximated vertical rate can effectively reduce the temperature forecast bias. The greater the model topographic elevation bias, the smaller the amplitude of weather process fluctuations, and the more obvious the correction performance.
Taking into account the relationships between model temperature forecasts, model topography, observed temperatures, and actual topography, a dynamically approximated vertical rate correction method for the 2 m temperature that evolves over space and time has been designed. A correction experiment is conducted for Chongqing in 2023. Evaluation of ECMWF model forecasts show that the spatial distribution of forecast skill for maximum and minimum 2 m temperatures is similar, but forecast skill for maximum temperature is significantly worse than for minimum temperature. Additionally, forecast skill declines with increasing forecast lead time. A strong correlation is found between model topographic elevation bias and temperature forecast bias; areas with smaller elevation bias tend to exhibit better forecast skill, and vice versa. Comparative research reveals that the correction scheme based on dynamically approximated vertical rate significantly outperforms the scheme based on constant vertical rate. Both schemes improve the ECMWF model temperature forecasts, with better correction performance for maximum temperatures than for minimum temperatures. Compared to the raw model forecasts, the corrected results based on dynamically approximated vertical rate have increased the 10-day average forecast accuracy of maximum and minimum temperatures by 12.71% and 8.3%, respectively, and reduced the mean absolute error by 0.68°C and 0.3°C, respectively. The monthly average forecast accuracy of the maximum temperature for 24 h forecast lead time has increased by 20.34%. The minimum temperature has increased by 14.44% on average. Overall, the corrected temperature forecasts are more stable. The correction scheme based on dynamically approximated vertical rate can effectively reduce the temperature forecast bias. The greater the model topographic elevation bias, the smaller the amplitude of weather process fluctuations, and the more obvious the correction performance.
Available online: July 25, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.070802
Abstract:
Based on high-precision online atmospheric CO2 concentration measurements from the Shenyang Urban Ecosystem Station during June 2023 to May 2024, the REBS(Robust extraction of baseline signal) algorithm was employed to separate regional background and pollution data. The influence of regional transport on atmospheric CO2 concentrations in Shenyang was analyzed using surface wind field data and MeteoInfo statistical software. The contributions of fossil fuel combustion emissions and ecosystem emissions/absorption to CO2 concentrations were estimated according to carbon conservation principles. Results show that the average CO2 concentration at Shenyang Urban Ecosystem Station was 477.2 ppm, with background and pollution concentrations averaging 474.9 ppm and 519.4 ppm, respectively. High-concentration CO2 air masses affecting Shenyang originated from the southwest during spring and summer, and from northwest and southwest during winter. The potential CO2 emission source regions throughout the year were mainly distributed in most parts of Liaoning and Jilin provinces, southern Heilongjiang, eastern Inner Mongolia, Beijing-Tianjin-Hebei region, Shandong Peninsula, and the Yellow Sea and Bohai Sea areas. Compared to other seasons, fossil fuel combustion emissions contributed more significantly to Shenyang"s atmospheric CO2 concentrations during autumn and winter.
Based on high-precision online atmospheric CO2 concentration measurements from the Shenyang Urban Ecosystem Station during June 2023 to May 2024, the REBS(Robust extraction of baseline signal) algorithm was employed to separate regional background and pollution data. The influence of regional transport on atmospheric CO2 concentrations in Shenyang was analyzed using surface wind field data and MeteoInfo statistical software. The contributions of fossil fuel combustion emissions and ecosystem emissions/absorption to CO2 concentrations were estimated according to carbon conservation principles. Results show that the average CO2 concentration at Shenyang Urban Ecosystem Station was 477.2 ppm, with background and pollution concentrations averaging 474.9 ppm and 519.4 ppm, respectively. High-concentration CO2 air masses affecting Shenyang originated from the southwest during spring and summer, and from northwest and southwest during winter. The potential CO2 emission source regions throughout the year were mainly distributed in most parts of Liaoning and Jilin provinces, southern Heilongjiang, eastern Inner Mongolia, Beijing-Tianjin-Hebei region, Shandong Peninsula, and the Yellow Sea and Bohai Sea areas. Compared to other seasons, fossil fuel combustion emissions contributed more significantly to Shenyang"s atmospheric CO2 concentrations during autumn and winter.
Available online: July 23, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.060901
Abstract:
One of the key constraints on the difficulty of short-range forecasting of warm-season precipitation in the Beijing-Tianjin-Hebei region is the lack of atmospheric dynamic parameter profiles and the unknown pre-precipitation signal. In this study, we analyzed the evolution of the dynamical field before the trigger of strong convection by using the dynamical parameter profiles inverted from the wind profile radar (RWP) mesoscale network in the warm season (April-September) of 2023-2024 and constructed the horizontal convergence intensity index before the trigger of strong convection. The results show that, before the trigger convection, the dynamical field is characterized by a vertical upward motion configuration with low-level convergence and high-level divergence. During the 30 min before precipitation, the continuously enhanced convergent and upward motion favors the occurrence of strong convection. Among 763 strong precipitation events, the horizontal convergence intensity index was able to effectively identify the strong precipitation events with an identification accuracy of 72.4%. This study develops a quantitative discrimination technique of strong convective precursor signals from RWP mesoscale network, which provides an important reference for quantitatively analyzing the early warning of strong convection in the Beijing-Tianjin-Hebei region.
One of the key constraints on the difficulty of short-range forecasting of warm-season precipitation in the Beijing-Tianjin-Hebei region is the lack of atmospheric dynamic parameter profiles and the unknown pre-precipitation signal. In this study, we analyzed the evolution of the dynamical field before the trigger of strong convection by using the dynamical parameter profiles inverted from the wind profile radar (RWP) mesoscale network in the warm season (April-September) of 2023-2024 and constructed the horizontal convergence intensity index before the trigger of strong convection. The results show that, before the trigger convection, the dynamical field is characterized by a vertical upward motion configuration with low-level convergence and high-level divergence. During the 30 min before precipitation, the continuously enhanced convergent and upward motion favors the occurrence of strong convection. Among 763 strong precipitation events, the horizontal convergence intensity index was able to effectively identify the strong precipitation events with an identification accuracy of 72.4%. This study develops a quantitative discrimination technique of strong convective precursor signals from RWP mesoscale network, which provides an important reference for quantitatively analyzing the early warning of strong convection in the Beijing-Tianjin-Hebei region.
Available online: July 21, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.052301
Abstract:
Heavy precipitation is one of the most widespread hazardous weather affecting the socioeconomic stability and people"s livelihoods in China. Accurately forecasting such events poses significant scientific challenges. The multi-scale nonlinear characteristics of moist physical processes make numerical weather forecasting and objective corrections for precipitation considerably more difficult than for other meteorological variables like wind and temperature. This study investigates correcting 3-hour precipitation forecasts in the Beijing-Tianjin-Hebei region. Utilizing station observations and numerical model predictions, we explore the application of machine learning in correcting heavy precipitation through strategies such as constructing and sampling precipitation datasets, inputting relevant physical features, and training on residuals. The results demonstrate that addressing the long-tailed distribution challenge of precipitation samples—while maintaining the true distribution of precipitation and moderately increasing the proportion of heavy precipitation samples—is crucial for enhancing correction effectiveness. Statistical tests on the test set show that the machine learning correction scheme achieves significant improvements in skill scores for precipitation ranging from 0.1 to 20 mm compared to the raw model forecasts, with the enhancement magnitude increasing as the threshold rises. Additionally, the evaluation of categorized heavy precipitation indicates that it is more challenging to achieve improvements in convective heavy precipitation forced by weak weather systems. However, machine learning demonstrates particular promise for correcting heavy precipitation events with lower forecast accuracy from the model. Specifically, the lower the model"s predictive capability, the greater the space and extent for improvement through machine learning corrections. Feature importance analysis reveals that incorporating physically factors—particularly dynamic-thermodynamic, moisture parameters and the duration of convection—positively enhances model forecast scores while simultaneously mitigating machine learning models" tendency toward overprediction of light to moderate precipitation events.
Heavy precipitation is one of the most widespread hazardous weather affecting the socioeconomic stability and people"s livelihoods in China. Accurately forecasting such events poses significant scientific challenges. The multi-scale nonlinear characteristics of moist physical processes make numerical weather forecasting and objective corrections for precipitation considerably more difficult than for other meteorological variables like wind and temperature. This study investigates correcting 3-hour precipitation forecasts in the Beijing-Tianjin-Hebei region. Utilizing station observations and numerical model predictions, we explore the application of machine learning in correcting heavy precipitation through strategies such as constructing and sampling precipitation datasets, inputting relevant physical features, and training on residuals. The results demonstrate that addressing the long-tailed distribution challenge of precipitation samples—while maintaining the true distribution of precipitation and moderately increasing the proportion of heavy precipitation samples—is crucial for enhancing correction effectiveness. Statistical tests on the test set show that the machine learning correction scheme achieves significant improvements in skill scores for precipitation ranging from 0.1 to 20 mm compared to the raw model forecasts, with the enhancement magnitude increasing as the threshold rises. Additionally, the evaluation of categorized heavy precipitation indicates that it is more challenging to achieve improvements in convective heavy precipitation forced by weak weather systems. However, machine learning demonstrates particular promise for correcting heavy precipitation events with lower forecast accuracy from the model. Specifically, the lower the model"s predictive capability, the greater the space and extent for improvement through machine learning corrections. Feature importance analysis reveals that incorporating physically factors—particularly dynamic-thermodynamic, moisture parameters and the duration of convection—positively enhances model forecast scores while simultaneously mitigating machine learning models" tendency toward overprediction of light to moderate precipitation events.
Available online: July 17, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.040301
Abstract:
In recent years, the interaction between aerosols and thunderstorm electrification had emerged as a focal point in academic research. Homogeneous nucleation of soluble aerosol droplets and heterogeneous nucleation of ice nuclei represent two primary mechanisms for ice crystal formation. The size and concentration of ice crystals in thunderstorms significantly influenced charge generation and distribution, which are critical factors in lightning occurrence. This study employed a three-dimensional thunderstorm model to investigate the impact of three distinct ice nucleation processes on lightning discharge characteristics, focused on a weak mountain thunderstorm case study. The results demonstrated that homogeneous nucleation generated a substantial number of ice crystals in the low-temperature region at the cloud top, resulting in prolonged discharge duration within the thunderstorm. The charge structure was predominantly dipolar, with a lower frequency of lightning, primarily consisting of cloud flashes originating from higher altitudes. In contrast, heterogeneous nucleation formed ice crystals in high-temperature regions, leading to an earlier charging process in thunderstorms. Ice crystals in these regions readily met charge reversal conditions, significantly increasing the negative non-inductive charging rate and favoring the formation of tripolar charge structures. Under these conditions, lightning occurred earlier and initiated from relatively lower altitudes, with heterogeneous nucleation facilitating lightning occurrence. When both homogeneous and heterogeneous nucleation processes occurred simultaneously, the thunderstorm charging process intensifies, resulting in a high lightning frequency. Furthermore, both nucleation processes advanced the initial lightning occurrence time and expanded the height range of the initial lightning trigger points. The tripolar charge structure promoted the occurrence of a substantial number of negative cloud-to-ground flashes.
In recent years, the interaction between aerosols and thunderstorm electrification had emerged as a focal point in academic research. Homogeneous nucleation of soluble aerosol droplets and heterogeneous nucleation of ice nuclei represent two primary mechanisms for ice crystal formation. The size and concentration of ice crystals in thunderstorms significantly influenced charge generation and distribution, which are critical factors in lightning occurrence. This study employed a three-dimensional thunderstorm model to investigate the impact of three distinct ice nucleation processes on lightning discharge characteristics, focused on a weak mountain thunderstorm case study. The results demonstrated that homogeneous nucleation generated a substantial number of ice crystals in the low-temperature region at the cloud top, resulting in prolonged discharge duration within the thunderstorm. The charge structure was predominantly dipolar, with a lower frequency of lightning, primarily consisting of cloud flashes originating from higher altitudes. In contrast, heterogeneous nucleation formed ice crystals in high-temperature regions, leading to an earlier charging process in thunderstorms. Ice crystals in these regions readily met charge reversal conditions, significantly increasing the negative non-inductive charging rate and favoring the formation of tripolar charge structures. Under these conditions, lightning occurred earlier and initiated from relatively lower altitudes, with heterogeneous nucleation facilitating lightning occurrence. When both homogeneous and heterogeneous nucleation processes occurred simultaneously, the thunderstorm charging process intensifies, resulting in a high lightning frequency. Furthermore, both nucleation processes advanced the initial lightning occurrence time and expanded the height range of the initial lightning trigger points. The tripolar charge structure promoted the occurrence of a substantial number of negative cloud-to-ground flashes.
Available online: July 14, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.071101
Abstract:
This paper proposes a deep learning model based on a sequential fusion encoder, which integrates the advantages of Convolutional Neural Networks (CNN), Convolutional Gated Recurrent Units (ConvGRU), and Transformer encoders, aiming to enhance the accuracy of winter precipitation phase prediction. Utilizing hourly precipitation weather phenomenon observational data from Wuhan over a 15-year period during winters from 2010 to 2024, as well as reanalysis data from the European Centre for Medium-Range Weather Forecasts, the model effectively addresses data imbalance issues through sample processing and data augmentation. Experimental results demonstrate superior performance in predicting solid precipitation, exhibiting high reliability in forecasting sleet and snow. By validating the model against complex weather processes in February 2024, its high precision in snowfall prediction is confirmed, though limitations are revealed in rapidly changing precipitation phases. This study offers an efficient and intelligent solution for deep learning-based prediction of winter precipitation phases, laying a foundation for further model optimization and enhanced predictive capabilities.
This paper proposes a deep learning model based on a sequential fusion encoder, which integrates the advantages of Convolutional Neural Networks (CNN), Convolutional Gated Recurrent Units (ConvGRU), and Transformer encoders, aiming to enhance the accuracy of winter precipitation phase prediction. Utilizing hourly precipitation weather phenomenon observational data from Wuhan over a 15-year period during winters from 2010 to 2024, as well as reanalysis data from the European Centre for Medium-Range Weather Forecasts, the model effectively addresses data imbalance issues through sample processing and data augmentation. Experimental results demonstrate superior performance in predicting solid precipitation, exhibiting high reliability in forecasting sleet and snow. By validating the model against complex weather processes in February 2024, its high precision in snowfall prediction is confirmed, though limitations are revealed in rapidly changing precipitation phases. This study offers an efficient and intelligent solution for deep learning-based prediction of winter precipitation phases, laying a foundation for further model optimization and enhanced predictive capabilities.
Available online: July 11, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.010902
Abstract:
IUsing the total irradiance data from 23 radiation observation stations in Henan Province in 2022 and CMA-WSP2.0 model products,,characteristic variables were selected by Lasso regression, training data sets and test data sets were established, and machine learning methods (Random forest, XGBoost, LightGBM) were used to train the model using the training data set, and the total irradiance forecast by CMA-WSP2.0 model in Henan Province was revised. The revised results were tested by site and region, season and total irradiance classification, and the following conclusions were obtained: The three machine learning methods of random forest, XGBoost, and LightGBM have good correction effects. Compared with the CMA-WSP2.0 model prediction results, the average absolute error and root mean square error are significantly reduced, and the 24-hour accuracy and 24-hour qualification rate are significantly improved. The average absolute error decreases by 18.32~32.91 W·, the average error decreases by 38~56%, and the root mean square error decreases by 36~52%. The 24-hour average accuracy and 24-hour average qualification rate increased by 7.3% and 5.7%. The results of regional statistics are consistent with those of the stations. For the five regions, the correction effect of western Henan is the best. The corrected deviation range of the three machine learning methods is narrower than that of the CMA-WSP2.0 simulation set, and the probability of the deviation distribution near 0 is greater. Among the seasonal test results, the three methods have more significant correction effect in winter. For different total irradiance levels, the three machine learning methods can effectively improve the CMA-WSP2.0 model prediction, and the correction effect tends to gradually weaken with the increase of total irradiance levels. The results can provide useful reference for improving the ability of total irradiance forecast in Henan Province.
IUsing the total irradiance data from 23 radiation observation stations in Henan Province in 2022 and CMA-WSP2.0 model products,,characteristic variables were selected by Lasso regression, training data sets and test data sets were established, and machine learning methods (Random forest, XGBoost, LightGBM) were used to train the model using the training data set, and the total irradiance forecast by CMA-WSP2.0 model in Henan Province was revised. The revised results were tested by site and region, season and total irradiance classification, and the following conclusions were obtained: The three machine learning methods of random forest, XGBoost, and LightGBM have good correction effects. Compared with the CMA-WSP2.0 model prediction results, the average absolute error and root mean square error are significantly reduced, and the 24-hour accuracy and 24-hour qualification rate are significantly improved. The average absolute error decreases by 18.32~32.91 W·, the average error decreases by 38~56%, and the root mean square error decreases by 36~52%. The 24-hour average accuracy and 24-hour average qualification rate increased by 7.3% and 5.7%. The results of regional statistics are consistent with those of the stations. For the five regions, the correction effect of western Henan is the best. The corrected deviation range of the three machine learning methods is narrower than that of the CMA-WSP2.0 simulation set, and the probability of the deviation distribution near 0 is greater. Among the seasonal test results, the three methods have more significant correction effect in winter. For different total irradiance levels, the three machine learning methods can effectively improve the CMA-WSP2.0 model prediction, and the correction effect tends to gradually weaken with the increase of total irradiance levels. The results can provide useful reference for improving the ability of total irradiance forecast in Henan Province.
Available online: July 08, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.070501
Abstract:
This paper describes a quality control (QC) algorithm for reflectivity data of dual-channel millimeter-wave cloud radar (MMCR) in different regions.The data for the research from the 15 MMCR stations which were the first batch of MMCR to be approved for operational use in China.The algorithm provides a method for automatically identifying the QC threshold parameters for reflectivity(Z)and linear depolarization ratio (LDR), combined with filtering check and continuity check, etc., which can effectively eliminate non cloud and non rain echoes.The method is based on the distribution characteristics between the cloud or rain echoes and clutter in the MMCR data. It classifies and labels the cloud or rain echo and clutter samples from the 15 stations in 2023. Based on the intersection points of the frequency curves of the two types of echoes, the QC threshold parameters for reflectivity(Z)and linear depolarization ratio (LDR) for each station can gets rapidly. By comparing the correlation coefficient, average deviation and root mean square error of cloud heights calculated from the MMCR data before and after quality control and radiosonde data at different stations and during different observation periods.The effectiveness of the QC method is discussed.The results show that non-meteorological echoes in the data can be effectively removed after QC,especially low-level suspended clutter. The correlation coefficient with radiosonde-identified cloud base height increases from 0.47 to 0.91, and the correlation coefficient with cloud top height increases from 0.80 to 0.87. That improved that the calculated cloud heights after QC more reasonable. The data after QC can enhances the consistency between the cloud height data of MMCR and radiosonde.
This paper describes a quality control (QC) algorithm for reflectivity data of dual-channel millimeter-wave cloud radar (MMCR) in different regions.The data for the research from the 15 MMCR stations which were the first batch of MMCR to be approved for operational use in China.The algorithm provides a method for automatically identifying the QC threshold parameters for reflectivity(Z)and linear depolarization ratio (LDR), combined with filtering check and continuity check, etc., which can effectively eliminate non cloud and non rain echoes.The method is based on the distribution characteristics between the cloud or rain echoes and clutter in the MMCR data. It classifies and labels the cloud or rain echo and clutter samples from the 15 stations in 2023. Based on the intersection points of the frequency curves of the two types of echoes, the QC threshold parameters for reflectivity(Z)and linear depolarization ratio (LDR) for each station can gets rapidly. By comparing the correlation coefficient, average deviation and root mean square error of cloud heights calculated from the MMCR data before and after quality control and radiosonde data at different stations and during different observation periods.The effectiveness of the QC method is discussed.The results show that non-meteorological echoes in the data can be effectively removed after QC,especially low-level suspended clutter. The correlation coefficient with radiosonde-identified cloud base height increases from 0.47 to 0.91, and the correlation coefficient with cloud top height increases from 0.80 to 0.87. That improved that the calculated cloud heights after QC more reasonable. The data after QC can enhances the consistency between the cloud height data of MMCR and radiosonde.
Available online: July 01, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.061901
Abstract:
This study aims to explore the potential applications of large language models (LLMs) in weather forecasting and the challenges they face. By analyzing the use of LLMs in scenarios such as meteorological knowledge retrieval, foundational forecasting models, diagnostic analysis, tool invocation, and text generation, the study finds that LLMs have great potential in enhancing the accuracy of weather forecasts and the intelligence of meteorological services. LLMs provide powerful assistance to forecasters by efficiently processing vast amounts of meteorological knowledge, integrating cross-domain multi-source information, and generating customized forecast products. However, LLMs still have limitations in areas such as the spatiotemporal understanding of atmospheric motion, bias, and hallucinations, which can be addressed through techniques such as data cleaning, bias correction and fine-tuning, and retrieval-augmented generation. By constructing high-quality meteorological corpora, optimizing benchmark testing frameworks, and integrating external tools, the effectiveness of LLMs in weather forecasting can be further enhanced. Overall, LLMs bring new technological opportunities to the meteorological field, but their widespread application still requires ongoing exploration and improvement in areas such as corpus quality, model optimization, and human-machine collaboration.
This study aims to explore the potential applications of large language models (LLMs) in weather forecasting and the challenges they face. By analyzing the use of LLMs in scenarios such as meteorological knowledge retrieval, foundational forecasting models, diagnostic analysis, tool invocation, and text generation, the study finds that LLMs have great potential in enhancing the accuracy of weather forecasts and the intelligence of meteorological services. LLMs provide powerful assistance to forecasters by efficiently processing vast amounts of meteorological knowledge, integrating cross-domain multi-source information, and generating customized forecast products. However, LLMs still have limitations in areas such as the spatiotemporal understanding of atmospheric motion, bias, and hallucinations, which can be addressed through techniques such as data cleaning, bias correction and fine-tuning, and retrieval-augmented generation. By constructing high-quality meteorological corpora, optimizing benchmark testing frameworks, and integrating external tools, the effectiveness of LLMs in weather forecasting can be further enhanced. Overall, LLMs bring new technological opportunities to the meteorological field, but their widespread application still requires ongoing exploration and improvement in areas such as corpus quality, model optimization, and human-machine collaboration.
Available online: July 01, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.010901
Abstract:
From January 1st to 17th, 2020, Shihezi experienced a persistent low visibility weather event. This study utilized tethered airships, microwave radiometers, ground-based lidars, and other equipment to conduct joint experiments to detect this event. The meteorological factors, atmospheric boundary layer characteristics, and the diurnal and daily variations of pollutants during this low visibility weather were analyzed. The results show:(1) An extended duration of haze phase alongside low atmospheric boundary layer height, significant inversion layer, and high pollutant concentration within the event. (2) The relationship between atmospheric boundary layer height variation and pollutant accumulation was significant, with a low atmospheric boundary layer height corresponding to low wind speed, high humidity, and high pollutant concentration. (3) Visibility averaged 1040m, with low surface wind speeds (lower 2m/s) and relative humidity between 71% and 92%. The atmospheric boundary layer exhibited a dry-above, moist-below structure, ranging from 230 to 500m, while aerosol pollutants were mainly between 150m and 450m. PM2.5 peaked at 319.7μg/m^3.(4) There was a negative correlation between relative humidity and PM2.5 concentration with visibility, with PM2.5 having a more significant impact on visibility. This study holds implications for haze monitoring and forecasting.
From January 1st to 17th, 2020, Shihezi experienced a persistent low visibility weather event. This study utilized tethered airships, microwave radiometers, ground-based lidars, and other equipment to conduct joint experiments to detect this event. The meteorological factors, atmospheric boundary layer characteristics, and the diurnal and daily variations of pollutants during this low visibility weather were analyzed. The results show:(1) An extended duration of haze phase alongside low atmospheric boundary layer height, significant inversion layer, and high pollutant concentration within the event. (2) The relationship between atmospheric boundary layer height variation and pollutant accumulation was significant, with a low atmospheric boundary layer height corresponding to low wind speed, high humidity, and high pollutant concentration. (3) Visibility averaged 1040m, with low surface wind speeds (lower 2m/s) and relative humidity between 71% and 92%. The atmospheric boundary layer exhibited a dry-above, moist-below structure, ranging from 230 to 500m, while aerosol pollutants were mainly between 150m and 450m. PM2.5 peaked at 319.7μg/m^3.(4) There was a negative correlation between relative humidity and PM2.5 concentration with visibility, with PM2.5 having a more significant impact on visibility. This study holds implications for haze monitoring and forecasting.
Available online: June 30, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.041302
Abstract:
To evaluate the accuracy and operational applicability of FY-4A/B GIIRS-retrieved temperature and humidity profiles in Guizhou, the FY-4A temperature profile and FY-4B temperature/humidity profiles were validated against radiosonde observations at Guiyang and Weining stations and ERA5 reanalysis data. The results indicate that only data with quality code 3 should be discarded, while retaining codes 0–2 to maximize the integrity of the profiles. Clouds significantly degrade GIIRS retrieval performance: under cloudy conditions, the RMSE of FY-4A temperature increases by 1.19°C (clear skies) and 0.96°C (cloud edges), while FY-4B temperature increases by 1.52°C and 1.21°C, and humidity by 1.28 g/kg and 0.95 g/kg, respectively. Cloud cover also amplifies vertical data dispersion. A systematic bias exists in FY-4A/B profiles; linear bias correction reduces the mean error (ME) to near zero under clear skies and improves cloudy conditions more markedly. Seasonal comparisons between sounding and satellite profiles demonstrate that FY-4A/B captures terrain-induced differences in atmospheric stratification between Guiyang and Weining. For three regional hail events in 2023, GIIRS products agreed well with radiosondes. The high-resolution profiles revealed pre-hail instability ("upper cold/lower warm" and "upper dry/lower wet"), offering valuable forecast indicators. However, near-surface layer retrieval errors caused CAPE underestimation and distorted low-level sounding structures. Surface-based 2-m temperature/dew point corrections restored realistic CAPE and thunderstorm-favorable profiles, aiding short-term convective forecasting.
To evaluate the accuracy and operational applicability of FY-4A/B GIIRS-retrieved temperature and humidity profiles in Guizhou, the FY-4A temperature profile and FY-4B temperature/humidity profiles were validated against radiosonde observations at Guiyang and Weining stations and ERA5 reanalysis data. The results indicate that only data with quality code 3 should be discarded, while retaining codes 0–2 to maximize the integrity of the profiles. Clouds significantly degrade GIIRS retrieval performance: under cloudy conditions, the RMSE of FY-4A temperature increases by 1.19°C (clear skies) and 0.96°C (cloud edges), while FY-4B temperature increases by 1.52°C and 1.21°C, and humidity by 1.28 g/kg and 0.95 g/kg, respectively. Cloud cover also amplifies vertical data dispersion. A systematic bias exists in FY-4A/B profiles; linear bias correction reduces the mean error (ME) to near zero under clear skies and improves cloudy conditions more markedly. Seasonal comparisons between sounding and satellite profiles demonstrate that FY-4A/B captures terrain-induced differences in atmospheric stratification between Guiyang and Weining. For three regional hail events in 2023, GIIRS products agreed well with radiosondes. The high-resolution profiles revealed pre-hail instability ("upper cold/lower warm" and "upper dry/lower wet"), offering valuable forecast indicators. However, near-surface layer retrieval errors caused CAPE underestimation and distorted low-level sounding structures. Surface-based 2-m temperature/dew point corrections restored realistic CAPE and thunderstorm-favorable profiles, aiding short-term convective forecasting.
Available online: June 20, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.011001
Abstract:
To obtain the X-band dual-polarization radar characteristics of hail in the southwestern Yunnan, a statistical analysis method was used to analyze 22 hail sample data detected by the Menglian X-band dual-polarization radar.The results show that hailstorm cells have the following characteristics:Maximum horizontal reflectivity factor (ZH) ≥58 dBz;The 45 dBz echo development height (H45) ≥7.1 km, with a height difference between H45 and the wet-bulb 0℃ level ≥3.3 km;86% of hail cells have H45 exceeding the height of the -20°C layer;The 50 dBz echo development height (H50) ≥5.7 km, with a height difference between H50 and the -20℃ level ranging from -1.2 to 2.7 km;Vertical integrated liquid water content (VIL) density ≥2.8 g·m-3, and the VIL increased by 4.7–18.3 kg·m-2 in the volume scan preceding hailfall.Differential reflectivity (ZDR) and specific differential phase (KDP) average and median values, above 0℃ layer, concentrated near 0 value, predominantly negative; below 0℃layer within 1 km, transition from negative to positive values, gradually increasing with height decrease, maximum in the near-surface layer, reaching approximately 1.5 dB and 0.7 °/km respectively. The range of values for each parameter above the 0℃ layer, ZDR -1.92 to 1.35 dB, KDP -1.97 to 1.29 °/km, correlation coefficient (CC) 0.86 to 0.99; below the 0℃ layer, ZDR -1.92 to 3.74 dB, KDP -2.98 to 2.66 °/km, CC 0.79 to 0.98.The research results provide a reference for the detection and identification of hail characteristics by the X-band dual-polarization radar in the southwestern Yunnan region.
To obtain the X-band dual-polarization radar characteristics of hail in the southwestern Yunnan, a statistical analysis method was used to analyze 22 hail sample data detected by the Menglian X-band dual-polarization radar.The results show that hailstorm cells have the following characteristics:Maximum horizontal reflectivity factor (ZH) ≥58 dBz;The 45 dBz echo development height (H45) ≥7.1 km, with a height difference between H45 and the wet-bulb 0℃ level ≥3.3 km;86% of hail cells have H45 exceeding the height of the -20°C layer;The 50 dBz echo development height (H50) ≥5.7 km, with a height difference between H50 and the -20℃ level ranging from -1.2 to 2.7 km;Vertical integrated liquid water content (VIL) density ≥2.8 g·m-3, and the VIL increased by 4.7–18.3 kg·m-2 in the volume scan preceding hailfall.Differential reflectivity (ZDR) and specific differential phase (KDP) average and median values, above 0℃ layer, concentrated near 0 value, predominantly negative; below 0℃layer within 1 km, transition from negative to positive values, gradually increasing with height decrease, maximum in the near-surface layer, reaching approximately 1.5 dB and 0.7 °/km respectively. The range of values for each parameter above the 0℃ layer, ZDR -1.92 to 1.35 dB, KDP -1.97 to 1.29 °/km, correlation coefficient (CC) 0.86 to 0.99; below the 0℃ layer, ZDR -1.92 to 3.74 dB, KDP -2.98 to 2.66 °/km, CC 0.79 to 0.98.The research results provide a reference for the detection and identification of hail characteristics by the X-band dual-polarization radar in the southwestern Yunnan region.
Available online: June 13, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.011302
Abstract:
Based on the complete monthly reports of the maximum and minimum temperatures recorded by instruments since the establishment of the Guiyang National Reference Meteorological Station on September 5, 1920, the sequences of the maximum and minimum temperatures and the daily temperature differences over the past century in Guiyang were established. Through multiple methods of verification of the sequences, it was found that the minimum temperature and the daily temperature differences from 1938 to 1944 had significant differences from the mean value of the sequences, and there were breakpoints in the sequences in 1937, 1944 and 2000. According to the historical evolution, observation record books and weather report stubs, as well as the comparison of multi-source and multi-station data, the minimum and maximum temperatures from 1938 to 1944 in the reports were found to be inaccurate, thus the data for this period were replaced with the records from the observation record books. Using the mean value of daily maximum and minimum temperatures and the daily temperature differences from 1938 to 1949, a conversion and correction scale was established to construct the daily temperatures for the period from 1921 to 1936 when there were no records. The non-uniformity of temperature caused by station relocation was revised recursively by using the initial values of this station and the annual changes of the optimal reference station. The final established homogenized temperature series of Guiyang over the past century shows a good consistency with the global temperature changes during the same period. The results show that over the past century, Guiyang"s temperature has experienced two relatively significant "warming", one from 1937 to 1953 and the other one starting from 1978, the current warming accelerated in 1996 and changed abruptly in 2011. The tendency rate of temperature change in Guiyang over the past century is 0.122℃ per decade to 0.136℃ per decade, and the minimum temperature has been oscillating upward since 1929, warming up with a tendency rate of 0.26℃ per decade to 0.31℃ per decade. The daily temperature differences decreases with a tendency rate of -0.27℃ per decade to -0.29℃ per decade. There is no obvious trend change in the maximum temperature. The warming rate of temperature and minimum temperature in autumn and winter is higher than that in spring and summer, February is the month of most warming, and July is the month of least warming. The warming is mainly caused by the increase in minimum temperature.
Based on the complete monthly reports of the maximum and minimum temperatures recorded by instruments since the establishment of the Guiyang National Reference Meteorological Station on September 5, 1920, the sequences of the maximum and minimum temperatures and the daily temperature differences over the past century in Guiyang were established. Through multiple methods of verification of the sequences, it was found that the minimum temperature and the daily temperature differences from 1938 to 1944 had significant differences from the mean value of the sequences, and there were breakpoints in the sequences in 1937, 1944 and 2000. According to the historical evolution, observation record books and weather report stubs, as well as the comparison of multi-source and multi-station data, the minimum and maximum temperatures from 1938 to 1944 in the reports were found to be inaccurate, thus the data for this period were replaced with the records from the observation record books. Using the mean value of daily maximum and minimum temperatures and the daily temperature differences from 1938 to 1949, a conversion and correction scale was established to construct the daily temperatures for the period from 1921 to 1936 when there were no records. The non-uniformity of temperature caused by station relocation was revised recursively by using the initial values of this station and the annual changes of the optimal reference station. The final established homogenized temperature series of Guiyang over the past century shows a good consistency with the global temperature changes during the same period. The results show that over the past century, Guiyang"s temperature has experienced two relatively significant "warming", one from 1937 to 1953 and the other one starting from 1978, the current warming accelerated in 1996 and changed abruptly in 2011. The tendency rate of temperature change in Guiyang over the past century is 0.122℃ per decade to 0.136℃ per decade, and the minimum temperature has been oscillating upward since 1929, warming up with a tendency rate of 0.26℃ per decade to 0.31℃ per decade. The daily temperature differences decreases with a tendency rate of -0.27℃ per decade to -0.29℃ per decade. There is no obvious trend change in the maximum temperature. The warming rate of temperature and minimum temperature in autumn and winter is higher than that in spring and summer, February is the month of most warming, and July is the month of least warming. The warming is mainly caused by the increase in minimum temperature.
Available online: June 03, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.011201
Abstract:
The refinement level of wind forecasting in numerical weather forecasting models cannot meet the needs of inland waterway transportation, and their adaptability to different regions varies. This article takes the western hills and central plains, most of them in Hubei Province, including the Yangtze River waterway, as research areas, Referring to the 10m wind of ART_1KM real-time product, this article analyzes the adaptability of 10m wind forecast of the European Central high-resolution atmospheric model deterministic forecasting product (EC-HRES) and the China Meteorological Administration mesoscale model forecasting product (CMA-MESO) in the research areas. A U-NET++ deep convolutional network model is constructed to achieve downscaling correction of wind speed forecast. The correction model improves the sampling module,and incorporates waterway item and terrain item into the loss function, enhancing the model"s expressive power and robustness, and improving the correction effect on the waterway. The verification shows that this method can effectively reduce the prediction error of wind speed on numerical forecasting models in the waterway area。
The refinement level of wind forecasting in numerical weather forecasting models cannot meet the needs of inland waterway transportation, and their adaptability to different regions varies. This article takes the western hills and central plains, most of them in Hubei Province, including the Yangtze River waterway, as research areas, Referring to the 10m wind of ART_1KM real-time product, this article analyzes the adaptability of 10m wind forecast of the European Central high-resolution atmospheric model deterministic forecasting product (EC-HRES) and the China Meteorological Administration mesoscale model forecasting product (CMA-MESO) in the research areas. A U-NET++ deep convolutional network model is constructed to achieve downscaling correction of wind speed forecast. The correction model improves the sampling module,and incorporates waterway item and terrain item into the loss function, enhancing the model"s expressive power and robustness, and improving the correction effect on the waterway. The verification shows that this method can effectively reduce the prediction error of wind speed on numerical forecasting models in the waterway area。
Available online: May 29, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.051901
Abstract:
Multiple DSG5 raindrop distrometers are utilized to analyze the raindrop size distribution of the residual vortex of Typhoon Haikui (2311) in the Pearl River Delta and evaluate the performance of different QPE algorithms in the S/X bands. The results indicate that the impact of the residual vortex of Haikui on rainfall in the Pearl River Delta can be divided into two main stages. The first stage is primarily influenced by the convergence of the southwest monsoon and easterly airflow on the eastern side of the vortex itself, with a deep moisture convergence layer. The microphysical processes of rainfall are relatively uniform with relatively small mass-weighted mean diameter (Dm) and higher normalized intercept parameter (lgNw), i.e., smaller particle sizes and higher number concentrations of raindrops. The second stage is characterized by intense rainfall caused by the convergence of southerly winds in the boundary layer on the outskirts of the residual vortex, with shallower moisture convergence layer. The rainfall particles are more dispersed, with more rainfall events featuring large Dm and low lgNw rain drops. Overall, medium-sized raindrops make a?major contribution to the total rainfall amount, but as rainfall intensity increases, the contribution of extremely large raindrops to rain rate at the second stage is significantly higher than that at the first stage. The dual-polarization parameters derived from raindrop size distribution of this process shows that, under the same rain rate (R), horizontal reflectivity factor (Zh), specific differential phase (KDP), and differential reflectivity (ZDR) at the first stage are smaller than those at the second stage. The deviation of QPE algorithms in the S/X bands calculated based on distrometers data shows that, R(Zh) has relatively large biases in both the S-band and X-band, while the bias of R(Zh, ZDR) is relatively small in the S-band but increases significantly with increasing rain rate in the X-band and R(KDP) has better performance in the X-band . R(KDP, ZDR) performs the best in both the S/X band and is minimally affected by changes in raindrop size distribution, with little difference between the two stages.
Multiple DSG5 raindrop distrometers are utilized to analyze the raindrop size distribution of the residual vortex of Typhoon Haikui (2311) in the Pearl River Delta and evaluate the performance of different QPE algorithms in the S/X bands. The results indicate that the impact of the residual vortex of Haikui on rainfall in the Pearl River Delta can be divided into two main stages. The first stage is primarily influenced by the convergence of the southwest monsoon and easterly airflow on the eastern side of the vortex itself, with a deep moisture convergence layer. The microphysical processes of rainfall are relatively uniform with relatively small mass-weighted mean diameter (Dm) and higher normalized intercept parameter (lgNw), i.e., smaller particle sizes and higher number concentrations of raindrops. The second stage is characterized by intense rainfall caused by the convergence of southerly winds in the boundary layer on the outskirts of the residual vortex, with shallower moisture convergence layer. The rainfall particles are more dispersed, with more rainfall events featuring large Dm and low lgNw rain drops. Overall, medium-sized raindrops make a?major contribution to the total rainfall amount, but as rainfall intensity increases, the contribution of extremely large raindrops to rain rate at the second stage is significantly higher than that at the first stage. The dual-polarization parameters derived from raindrop size distribution of this process shows that, under the same rain rate (R), horizontal reflectivity factor (Zh), specific differential phase (KDP), and differential reflectivity (ZDR) at the first stage are smaller than those at the second stage. The deviation of QPE algorithms in the S/X bands calculated based on distrometers data shows that, R(Zh) has relatively large biases in both the S-band and X-band, while the bias of R(Zh, ZDR) is relatively small in the S-band but increases significantly with increasing rain rate in the X-band and R(KDP) has better performance in the X-band . R(KDP, ZDR) performs the best in both the S/X band and is minimally affected by changes in raindrop size distribution, with little difference between the two stages.
Available online: May 28, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.040401
Abstract:
Due to the limitations of the limited area, lateral boundary perturbations are one of the primary perturbation methods for regional ensemble prediction. However, it remains unclear how to construct lateral boundary perturbations for the high-resolution regional ensemble prediction system of the China Meteorological Administration (CMA) to improve forecast skill. This paper develops a mixed lateral boundary perturbation method using the perturbation field of the CMA global ensemble prediction and lateral boundary field of the regional deterministic model, and adjusts the perturbation magnitude through dynamic perturbation coefficients. The results showed that the absence of lateral boundary perturbations suppresses the growth of perturbation energy at later forecast ranges, leading to insufficient ensemble spreads. The mixed lateral boundary perturbation scheme can enhance the perturbation energy spectra at meso-α and large scales, as well as improve the spread-skill relationships and probabilistic forecast skills for isobaric element and precipitation. Compared to the mixed lateral boundary perturbation scheme, the dynamic mixed lateral boundary perturbation scheme can enhance the spectral energy above 100 km, improve the spread-skill relationships, as well as the probabilistic forecast skills for low-level variables and precipitation beyond 24 hours, exhibiting good potential for operational application.
Due to the limitations of the limited area, lateral boundary perturbations are one of the primary perturbation methods for regional ensemble prediction. However, it remains unclear how to construct lateral boundary perturbations for the high-resolution regional ensemble prediction system of the China Meteorological Administration (CMA) to improve forecast skill. This paper develops a mixed lateral boundary perturbation method using the perturbation field of the CMA global ensemble prediction and lateral boundary field of the regional deterministic model, and adjusts the perturbation magnitude through dynamic perturbation coefficients. The results showed that the absence of lateral boundary perturbations suppresses the growth of perturbation energy at later forecast ranges, leading to insufficient ensemble spreads. The mixed lateral boundary perturbation scheme can enhance the perturbation energy spectra at meso-α and large scales, as well as improve the spread-skill relationships and probabilistic forecast skills for isobaric element and precipitation. Compared to the mixed lateral boundary perturbation scheme, the dynamic mixed lateral boundary perturbation scheme can enhance the spectral energy above 100 km, improve the spread-skill relationships, as well as the probabilistic forecast skills for low-level variables and precipitation beyond 24 hours, exhibiting good potential for operational application.
Available online: May 14, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.041602
Abstract:
Based on data from automatic weather stations, buoy observation stations, and ERA5 reanalysis spanning from 2015 to 2023, this study analyzes the characteristics of sea fog at Yangshan Port. Classification decision tree models were trained and validated using a comprehensive case database of sea fog events, and compared and verified their forcast results with those of the EC model. The results indicate that 2016 recorded the highest number of foggy days, with spring and early summer being the peak season, followed by winter. During dense fog events, the dominant wind directions ranged from northeast to north and southeast. Southeast winds prevailed during non-precipitation periods, while north winds dominated during precipitation. Monthly wind patterns transitioned from predominantly northerly in winter to northeasterly and southeasterly in spring. In the development stage of sea fog, southeast winds were dominant; during the mature stage, northeast winds prevailed; and during dissipation, north winds dominated. Fog events accompanied by precipitation were more frequent and longer-lasting. The classification decision tree models identified the temperature-dewpoint spread as a key factor in the formation of various sea fog types. Decision tree models demonstrated a lower miss rate and higher prediction performance than the EC model, particularly in forecasting the formation and duration of advection fog, while providing valuable insights into frontal and radiation fog events.
Based on data from automatic weather stations, buoy observation stations, and ERA5 reanalysis spanning from 2015 to 2023, this study analyzes the characteristics of sea fog at Yangshan Port. Classification decision tree models were trained and validated using a comprehensive case database of sea fog events, and compared and verified their forcast results with those of the EC model. The results indicate that 2016 recorded the highest number of foggy days, with spring and early summer being the peak season, followed by winter. During dense fog events, the dominant wind directions ranged from northeast to north and southeast. Southeast winds prevailed during non-precipitation periods, while north winds dominated during precipitation. Monthly wind patterns transitioned from predominantly northerly in winter to northeasterly and southeasterly in spring. In the development stage of sea fog, southeast winds were dominant; during the mature stage, northeast winds prevailed; and during dissipation, north winds dominated. Fog events accompanied by precipitation were more frequent and longer-lasting. The classification decision tree models identified the temperature-dewpoint spread as a key factor in the formation of various sea fog types. Decision tree models demonstrated a lower miss rate and higher prediction performance than the EC model, particularly in forecasting the formation and duration of advection fog, while providing valuable insights into frontal and radiation fog events.
Available online: May 14, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.031002
Abstract:
A localized severe convective rainfall event over eastern Sichuan basin under the background of southwest vortex on 8 August 2021 was analyzed by using the Chongqing S-band dual-pol radar, ERA5 reanalysis data and CMPAS multi-source precipitation product. The results are as follow: At the early development of convection, radar observed some relative weak convective characteristics. Snow particles play a major role in ice-phase particles at middle-upper level. The proportion of drizzle identification ranges from 20% to 40%, raindrops’ size and surface rain rate are both small. During the rapid intensification, radar measurements increased rapidly as well. ZDR and KDP columns can extend well above 8 km. Uplifted droplet generates supercooled water which facilitate ice-phase process over the melting layer. Melting of descending ice hydrometeors lead to the enhancement of liquid particles’ size and concentration at low level, which intensified the surface rain rate. Convective cells were merged with each other and shift eastward subsequently. As the system weakened, dry and wet snow particles become the main component of ice-phase at middle-upper level again. Both size and number of liquid particles at middle-lower level are decreased and surface rainrate gets weakened accordingly. Dual-pol variables and hydrometeor identification can basically exhibit the characteristic of hydrometeor transformation within the convective systems and cohere reasonably with the variation of surface rain rate.
A localized severe convective rainfall event over eastern Sichuan basin under the background of southwest vortex on 8 August 2021 was analyzed by using the Chongqing S-band dual-pol radar, ERA5 reanalysis data and CMPAS multi-source precipitation product. The results are as follow: At the early development of convection, radar observed some relative weak convective characteristics. Snow particles play a major role in ice-phase particles at middle-upper level. The proportion of drizzle identification ranges from 20% to 40%, raindrops’ size and surface rain rate are both small. During the rapid intensification, radar measurements increased rapidly as well. ZDR and KDP columns can extend well above 8 km. Uplifted droplet generates supercooled water which facilitate ice-phase process over the melting layer. Melting of descending ice hydrometeors lead to the enhancement of liquid particles’ size and concentration at low level, which intensified the surface rain rate. Convective cells were merged with each other and shift eastward subsequently. As the system weakened, dry and wet snow particles become the main component of ice-phase at middle-upper level again. Both size and number of liquid particles at middle-lower level are decreased and surface rainrate gets weakened accordingly. Dual-pol variables and hydrometeor identification can basically exhibit the characteristic of hydrometeor transformation within the convective systems and cohere reasonably with the variation of surface rain rate.
Available online: May 06, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.041802
Abstract:
Based on the China Meteorological Administration (CMA) convection-permitting ensemble prediction system (CMA-CPEPS) and regional ensemble prediction system (CMA-REPS), the precipitation forecasting performance during the 2023 flood season (from 15 June to 28 August) in China, and a case analysis of July 2023 severe torrential rain in North China was objectively and comprehensively evaluated. The results indicate that CMA-REPS has an issue with systematically overestimating precipitation forecasts, CMA-CPEPS has significantly improved this problem. Compared to CMA-REPS, CMA-CPEPS shows significantly superiority in predictive capacity for weather changes and its temporal changes, with better probability forecasting and resolution ability of precipitation. Both CMA-CPEPS and CMA-REPS exhibit low spread values, while spread/RMSE value and the spatial correlation between spread and RMSE of CMA-CPEPS and CMA-REPS are equivalent. In the July 2023 severe torrential rain in North China, CMA-CPEPS has better ability to capture precipitation details compared to CMA-REPS. CMA-CPEPS outperforms in forecasting precipitation intensity, the evolution trend of precipitation intensity, and spatio-temporal resolution of heavy precipitation, especially in short-duration heavy precipitation events. Overall, CMA-CPEPS represents a significantly enhancement over CMA-REPS in precipitation forecasting for the 2023 flood season in China.
Based on the China Meteorological Administration (CMA) convection-permitting ensemble prediction system (CMA-CPEPS) and regional ensemble prediction system (CMA-REPS), the precipitation forecasting performance during the 2023 flood season (from 15 June to 28 August) in China, and a case analysis of July 2023 severe torrential rain in North China was objectively and comprehensively evaluated. The results indicate that CMA-REPS has an issue with systematically overestimating precipitation forecasts, CMA-CPEPS has significantly improved this problem. Compared to CMA-REPS, CMA-CPEPS shows significantly superiority in predictive capacity for weather changes and its temporal changes, with better probability forecasting and resolution ability of precipitation. Both CMA-CPEPS and CMA-REPS exhibit low spread values, while spread/RMSE value and the spatial correlation between spread and RMSE of CMA-CPEPS and CMA-REPS are equivalent. In the July 2023 severe torrential rain in North China, CMA-CPEPS has better ability to capture precipitation details compared to CMA-REPS. CMA-CPEPS outperforms in forecasting precipitation intensity, the evolution trend of precipitation intensity, and spatio-temporal resolution of heavy precipitation, especially in short-duration heavy precipitation events. Overall, CMA-CPEPS represents a significantly enhancement over CMA-REPS in precipitation forecasting for the 2023 flood season in China.
Available online: April 28, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.040601
Abstract:
Abstract: Abstract: Based on observation data and ballistic theory, a simple model was established to analyze the influence of atmospheric vertical structure on the weather modification rocket ballistic performance during the ascending phase. The results indicate that the intensity and direction of the horizontal wind field have significant impact on ballistic performance, especially in low level wind fields below 1000m height. The impact of air density was relatively small. The model could be beneficial for ballistic correction, include ballistic height, deflection, and distance. It would provide relatively accurate prediction trajectory of weather modification rocket.
Abstract: Abstract: Based on observation data and ballistic theory, a simple model was established to analyze the influence of atmospheric vertical structure on the weather modification rocket ballistic performance during the ascending phase. The results indicate that the intensity and direction of the horizontal wind field have significant impact on ballistic performance, especially in low level wind fields below 1000m height. The impact of air density was relatively small. The model could be beneficial for ballistic correction, include ballistic height, deflection, and distance. It would provide relatively accurate prediction trajectory of weather modification rocket.
Available online: April 18, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.041801
Abstract:
The study of drought in the water source and receiving areas of the middle route project of South-to-North Water Diversion Project is of great significance for the water resource scheduling and operation management of the project. Based on the NCEP-NCAR reanalysis data and the daily average temperature, precipitation, and meteorological drought composite index of all meteorological stations in the water source and receiving areas of middle route project of South to North Water Diversion Project from 1961 to 2023, this article conducts identification and evaluation of regional drought processes in water source area and water receiving area. The results show that the annual values of drought days in the water source area and water receiving area are 101 days and 114 days, respectively, showing an overall spatial distribution characteristic of "more in the middle and less at both ends". The northern part of Henan and the southern part of Hebei in the water receiving area are high-value areas for drought days. The number of drought days in most of the water source areas, most of the water receiving areas in Henan, and eastern Hebei is increasing, while the number of drought days in most of the water receiving areas in northern, western, and southern Hebei, Beijing, and Tianjin is decreasing. Using the dynamic regional drought process identification method, a total of 97 regional drought processes have been identified in the study area since 1961. Using the percentile method to divide the intensity index of regional drought processes, threshold values corresponding to different intensity levels are obtained, and a total of 4 "extremely strong", 15 "strong", 30 "relatively strong", and 48 "moderate" regional drought processes occur in the study area. The strongest three regional drought processes occurred in 1968, 2001, and 1997, and the differences in circulation characteristics led to significant differences in the spatial and temporal distribution of drought days and the proportion of drought stations at different levels among the three processes. Among the 97 regional drought processes in the study area, 54.6% are caused by drought in the water source area but not in the water receiving area, which is beneficial for engineering water diversion. At the same time, in some years, the entire region is uniformly dry or the water source area is dry while the water receiving area is not dry, which is not conducive to engineering water diversion. Therefore, water resource scheduling of the middle route project of South-to-North Water Diversion Project needs to carry out targeted water diversion work based on the actual situation.
The study of drought in the water source and receiving areas of the middle route project of South-to-North Water Diversion Project is of great significance for the water resource scheduling and operation management of the project. Based on the NCEP-NCAR reanalysis data and the daily average temperature, precipitation, and meteorological drought composite index of all meteorological stations in the water source and receiving areas of middle route project of South to North Water Diversion Project from 1961 to 2023, this article conducts identification and evaluation of regional drought processes in water source area and water receiving area. The results show that the annual values of drought days in the water source area and water receiving area are 101 days and 114 days, respectively, showing an overall spatial distribution characteristic of "more in the middle and less at both ends". The northern part of Henan and the southern part of Hebei in the water receiving area are high-value areas for drought days. The number of drought days in most of the water source areas, most of the water receiving areas in Henan, and eastern Hebei is increasing, while the number of drought days in most of the water receiving areas in northern, western, and southern Hebei, Beijing, and Tianjin is decreasing. Using the dynamic regional drought process identification method, a total of 97 regional drought processes have been identified in the study area since 1961. Using the percentile method to divide the intensity index of regional drought processes, threshold values corresponding to different intensity levels are obtained, and a total of 4 "extremely strong", 15 "strong", 30 "relatively strong", and 48 "moderate" regional drought processes occur in the study area. The strongest three regional drought processes occurred in 1968, 2001, and 1997, and the differences in circulation characteristics led to significant differences in the spatial and temporal distribution of drought days and the proportion of drought stations at different levels among the three processes. Among the 97 regional drought processes in the study area, 54.6% are caused by drought in the water source area but not in the water receiving area, which is beneficial for engineering water diversion. At the same time, in some years, the entire region is uniformly dry or the water source area is dry while the water receiving area is not dry, which is not conducive to engineering water diversion. Therefore, water resource scheduling of the middle route project of South-to-North Water Diversion Project needs to carry out targeted water diversion work based on the actual situation.
Available online: April 17, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.041601
Abstract:
Based on the monthly rainfall of 643 stations in China, NCEP reanalysis data and NOAA ERSST sea surface temperature data from 1961 to 2023, impacts of early and late onset of El Ni?o on summer precipitation in China are analyzed. The results are as followed. Westerly wind anomalies in the equatorial west-central Pacific are more pronounced in June-August of years with early El Ni?o onset than in years with late El Ni?o onset, resulting in a more obvious warming of the sea surface temperature in the equatorial east-central Pacific in earlier onset years, the sea surface temperature in the quarter continues to rise. However, the positive anomaly of sea surface temperature in the equatorial east-central Pacific Ocean in the later onset years is not obvious and changes slowly. There is obvious differences in summer precipitation in central and eastern China between the El Ni?o earlier onset years and the El Ni?o later onset years, especially in July and August. In the El Ni?o earlier onset years, the Western North Pacific anticyclone (WNPAC) generally appears around August, the summer precipitation in central and eastern China is distributed in "-+-" from south to north, with more precipitation than normal in Jianghuai Region, and less precipitation than normal in other areas. In June, the Western Pacific Ocean is an abnormal cyclone, the precipitation in most of China’s central and eastern parts is less than normal. In July, the abnormal cyclone in the Western Pacific Ocean retreats southward significantly, the precipitation in regions of the Jiangnan, Northwest and North China continues to be less than normal. And the abnormal anticyclone to the east of Japan significantly extends westward and presses southward, the southeast coastal areas of China turns to abnormal southerly winds, leading to precipitation along the southern China coast, Jianghuai basin turn to more than normal. In August, Northwest Pacific Ocean turns into an anomalous anticyclone, WNPAC begins to appear, the precipitation over the middle and lower reaches of the Yangtze River and most parts of its south is more than normal, while the precipitation in most parts of northern China is less than normal. In the later onset years, WNPAC usually appears in October or later, the Western Pacific Ocean has been an abnormal cyclone from June to August. The summer precipitation in the central and eastern regions of China is distributed in "+-+" from south to north, and the precipitation persistence characteristics of each month are obvious.
Based on the monthly rainfall of 643 stations in China, NCEP reanalysis data and NOAA ERSST sea surface temperature data from 1961 to 2023, impacts of early and late onset of El Ni?o on summer precipitation in China are analyzed. The results are as followed. Westerly wind anomalies in the equatorial west-central Pacific are more pronounced in June-August of years with early El Ni?o onset than in years with late El Ni?o onset, resulting in a more obvious warming of the sea surface temperature in the equatorial east-central Pacific in earlier onset years, the sea surface temperature in the quarter continues to rise. However, the positive anomaly of sea surface temperature in the equatorial east-central Pacific Ocean in the later onset years is not obvious and changes slowly. There is obvious differences in summer precipitation in central and eastern China between the El Ni?o earlier onset years and the El Ni?o later onset years, especially in July and August. In the El Ni?o earlier onset years, the Western North Pacific anticyclone (WNPAC) generally appears around August, the summer precipitation in central and eastern China is distributed in "-+-" from south to north, with more precipitation than normal in Jianghuai Region, and less precipitation than normal in other areas. In June, the Western Pacific Ocean is an abnormal cyclone, the precipitation in most of China’s central and eastern parts is less than normal. In July, the abnormal cyclone in the Western Pacific Ocean retreats southward significantly, the precipitation in regions of the Jiangnan, Northwest and North China continues to be less than normal. And the abnormal anticyclone to the east of Japan significantly extends westward and presses southward, the southeast coastal areas of China turns to abnormal southerly winds, leading to precipitation along the southern China coast, Jianghuai basin turn to more than normal. In August, Northwest Pacific Ocean turns into an anomalous anticyclone, WNPAC begins to appear, the precipitation over the middle and lower reaches of the Yangtze River and most parts of its south is more than normal, while the precipitation in most parts of northern China is less than normal. In the later onset years, WNPAC usually appears in October or later, the Western Pacific Ocean has been an abnormal cyclone from June to August. The summer precipitation in the central and eastern regions of China is distributed in "+-+" from south to north, and the precipitation persistence characteristics of each month are obvious.
Available online: April 15, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.031001
Abstract:
Based on conventional observation data, Doppler weather radar data and ERA5 reanalysis data, the physical process responsible for the enhancement and maintenance of a strong squall line affecting the Bohai Sea area during the night of July 31, 2021 was analyzed. The results show that coastal terrain and sea surface temperature were key factors affecting the intensity of squall lines. The warm water areas in the central and western Bohai Sea exhibited favorable conditions for thermal instability, and the areas with high wind speeds corresponded to the areas with high sea surface temperatures. The horn-shaped coastal terrain around the Bohai Bay exhibited the "narrow tube effect", resulting in significant wind field convergence on the windward side of the coast, which was conducive to the triggering of convection. In the early stage, the cold pool outflow formed by multi-cell storms on land converged with environmental airflow, causing the storms to propagate eastward and move into the sea. The non-uniform onshore winds caused by the complex coastal terrain of the Bohai Bay were conducive to the formation of new coastal thunderstorms. These thunderstorms merged and strengthened, ultimately evolving into squall lines. The mesoscale vortices formed by the cold pool outflow of squall lines and the environmental airflow along the northern coast of Bohai Bay promoted the propagation and strengthening of squall lines along the coastline. The development of coastal convection led to the spread of cold density towards the sea, which strengthened the intensity of the sea surface cold pool and was conducive to the development of offshore squall lines. In the process of strengthening squall lines over the sea, boundary layer frontogenesis played a crucial role. Compared with the cold pool effect, the influence of boundary layer temperature and environmental airflow was more significant, ultimately leading to the development and strengthening of squall lines in the warm water area of the Bohai Sea and their weakening and dissipation in the cold water area.
Based on conventional observation data, Doppler weather radar data and ERA5 reanalysis data, the physical process responsible for the enhancement and maintenance of a strong squall line affecting the Bohai Sea area during the night of July 31, 2021 was analyzed. The results show that coastal terrain and sea surface temperature were key factors affecting the intensity of squall lines. The warm water areas in the central and western Bohai Sea exhibited favorable conditions for thermal instability, and the areas with high wind speeds corresponded to the areas with high sea surface temperatures. The horn-shaped coastal terrain around the Bohai Bay exhibited the "narrow tube effect", resulting in significant wind field convergence on the windward side of the coast, which was conducive to the triggering of convection. In the early stage, the cold pool outflow formed by multi-cell storms on land converged with environmental airflow, causing the storms to propagate eastward and move into the sea. The non-uniform onshore winds caused by the complex coastal terrain of the Bohai Bay were conducive to the formation of new coastal thunderstorms. These thunderstorms merged and strengthened, ultimately evolving into squall lines. The mesoscale vortices formed by the cold pool outflow of squall lines and the environmental airflow along the northern coast of Bohai Bay promoted the propagation and strengthening of squall lines along the coastline. The development of coastal convection led to the spread of cold density towards the sea, which strengthened the intensity of the sea surface cold pool and was conducive to the development of offshore squall lines. In the process of strengthening squall lines over the sea, boundary layer frontogenesis played a crucial role. Compared with the cold pool effect, the influence of boundary layer temperature and environmental airflow was more significant, ultimately leading to the development and strengthening of squall lines in the warm water area of the Bohai Sea and their weakening and dissipation in the cold water area.
Available online: April 11, 2025 , DOI: 10.7519/j.issn.1000-0526.2024.122601
Abstract:
From 29 to 30 June 2023, a local abrupt torrential rainstorm occurred in the western region of Hunan Province, but the forecasters and numerical models both failed to forecast the rainfall intensity. Based on conventional surface and upper-air observation data, Doppler radar and FY-4A data, ERA5 reanalysis data and numerical forecast products, the mesoscale characteristics and forecast difficulties of this heavy rainfall event were analyzed. The results show that this is a severe torrential rain process under the background of the northwest airflow behind the upper-level trough. The northwest airflow drives the cold air behind the northeast cold vortex to the south, and merges with the southwester warm-humid air flows strengthened at night, which leads to the occurrence of this process. The severe torrential rain is caused by a back-building and quasi-stationary meso-α-scale convective system ( MCS ), which is composed of several strongly developing γ-scale MCSs. On the doppler radar image, the MCS shows as an organized linear echo band, and the echo belongs to the warm cloud precipitation echo of low centroid and high rainfall efficiency. Under the favorable environmental background, the long-term maintenance of the boundary layer convergence line，the wind velocity pulsation of the low-level jet and the vertical structure of low-level convergence and high-level divergence lead to the initiation and organization of the convective cells, the consolidation strengthening, backward propagation of MCS and convective cell train effect are important reasons for the severe torrential rains. The significant deviations in the subjective forecast of short-term timeliness was possibly caused by the forecasting deviation of the lower troposphere dynamic and thermal fields of the numerical models, the deficiency of forecaster"s ability to correct the model forecast and the uncertainty of the heavy rainstorm forecast increased by the complex topography in western Hunan.. Therefore, it is very crucial for forecasters to use the automatic weather station data, satellite data and radar data with high spatiotemporal resolutions to analyze the changes of the mesoscale environmental conditions, strengthen the short-term nowcasting, and issue early warning signals in time.
From 29 to 30 June 2023, a local abrupt torrential rainstorm occurred in the western region of Hunan Province, but the forecasters and numerical models both failed to forecast the rainfall intensity. Based on conventional surface and upper-air observation data, Doppler radar and FY-4A data, ERA5 reanalysis data and numerical forecast products, the mesoscale characteristics and forecast difficulties of this heavy rainfall event were analyzed. The results show that this is a severe torrential rain process under the background of the northwest airflow behind the upper-level trough. The northwest airflow drives the cold air behind the northeast cold vortex to the south, and merges with the southwester warm-humid air flows strengthened at night, which leads to the occurrence of this process. The severe torrential rain is caused by a back-building and quasi-stationary meso-α-scale convective system ( MCS ), which is composed of several strongly developing γ-scale MCSs. On the doppler radar image, the MCS shows as an organized linear echo band, and the echo belongs to the warm cloud precipitation echo of low centroid and high rainfall efficiency. Under the favorable environmental background, the long-term maintenance of the boundary layer convergence line，the wind velocity pulsation of the low-level jet and the vertical structure of low-level convergence and high-level divergence lead to the initiation and organization of the convective cells, the consolidation strengthening, backward propagation of MCS and convective cell train effect are important reasons for the severe torrential rains. The significant deviations in the subjective forecast of short-term timeliness was possibly caused by the forecasting deviation of the lower troposphere dynamic and thermal fields of the numerical models, the deficiency of forecaster"s ability to correct the model forecast and the uncertainty of the heavy rainstorm forecast increased by the complex topography in western Hunan.. Therefore, it is very crucial for forecasters to use the automatic weather station data, satellite data and radar data with high spatiotemporal resolutions to analyze the changes of the mesoscale environmental conditions, strengthen the short-term nowcasting, and issue early warning signals in time.
Available online: April 01, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.012402
Abstract:
A warm sector severe convective event dominated by short-term heavy precipitation occurred in southern Anhui early in the morning of 27 May, 2023. The train effect formed by a number of north-south trend parallel meso-β scale short convections caused more than 100 mm sudden local heavy precipitation in 2 hours. The numerical simulation of this event was carried out by using WRF-EnKF, a rapid update assimilation system for service operation in Anhui Meteorological Observatory. The results show that (1) the interaction between large-scale environmental field and mesoscale convective system results in the increase of horizontal scale and intensification of several short convections. In terms of dynamic action, after the occurrence of convection, a meso-γ scale cyclonic vortex formed between the short convection and the low level jet core, causing the development of eastward convection. Meanwhile, the surface convergence line formed between the outflow of thunderstorm and the environmental wind triggers new convection in the south side of the short convection, making continuously development linearly to the south for the short convection. In terms of environmental conditions, multiple parallel low level jet cores provide favorable dynamic and thermal conditions for the development of convection. Inverse secondary circulation in the middle and upper levels occurred by the strong development of convection leads to the significant enhancement of atmospheric instability on the south side and the development of convection leads to the strengthen of deep vertical wind shear. (2) The interaction between the convections causes the maintenance of the short convection structure. Parallel convection forms parallel thunderstorm high pressure, and the interaction between the outflow of adjacent thunderstorms leads to the formation of multiple parallel positive and negative divergence pairs, thus bringing about multiple parallel zonal-vertical circulations between adjacent convections in the vertical direction. This is conducive to the maintenance and development of the structure of multiple short convections.
A warm sector severe convective event dominated by short-term heavy precipitation occurred in southern Anhui early in the morning of 27 May, 2023. The train effect formed by a number of north-south trend parallel meso-β scale short convections caused more than 100 mm sudden local heavy precipitation in 2 hours. The numerical simulation of this event was carried out by using WRF-EnKF, a rapid update assimilation system for service operation in Anhui Meteorological Observatory. The results show that (1) the interaction between large-scale environmental field and mesoscale convective system results in the increase of horizontal scale and intensification of several short convections. In terms of dynamic action, after the occurrence of convection, a meso-γ scale cyclonic vortex formed between the short convection and the low level jet core, causing the development of eastward convection. Meanwhile, the surface convergence line formed between the outflow of thunderstorm and the environmental wind triggers new convection in the south side of the short convection, making continuously development linearly to the south for the short convection. In terms of environmental conditions, multiple parallel low level jet cores provide favorable dynamic and thermal conditions for the development of convection. Inverse secondary circulation in the middle and upper levels occurred by the strong development of convection leads to the significant enhancement of atmospheric instability on the south side and the development of convection leads to the strengthen of deep vertical wind shear. (2) The interaction between the convections causes the maintenance of the short convection structure. Parallel convection forms parallel thunderstorm high pressure, and the interaction between the outflow of adjacent thunderstorms leads to the formation of multiple parallel positive and negative divergence pairs, thus bringing about multiple parallel zonal-vertical circulations between adjacent convections in the vertical direction. This is conducive to the maintenance and development of the structure of multiple short convections.
Available online: March 20, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.031902
Abstract:
Based on C-band weather radar products and multi-source observations, the persistent severe storm weather process and two major rainstorm monomers in southwest Yunnan was analyzed on 13-15 March 2023, and the results were as followed. The severe storm weather process occurred in the circulation background of the eastward retreat of the cold front on the ground, the establishment and intensification of the southwesterly rapids in the low (upper) air, and the persistent intrusion of the mid-level northwesterly flow, and the storm singletons mainly developed and intensified near the angle of the intersection of the mid- and high-altitude rapids. The continuous and stable transport of the low-level warm advection and the mid-level cold advection in southwest Yunnan intensifies the unstable stratification of the ambient atmosphere. The effective potential energy of convection is 826.6-1481.6 J·kg-1, the vertical wind shear from 0 to 3 km becomes 14.4-19.9 m·s-1, and that from 0 to 6 km becomes 27.6-34.5 m·s-1, and the unstable stratification of the high-level stratification and the strong shear environment are the main reasons for the development and maintenance of the catastrophic storms.The daytime storm was triggered by the coupling of southerly wind uplift forced by warm advection with weak surface convergence lines. The significant thermal and moisture contrast on either side of the Wuliang Mountains enhanced the storm"s development. In contrast, the nighttime storm initially formed near the mid-to-low-level baroclinic frontogenesis zone and was triggered by upslope lifting during its eastward movement, intensifying under the influence of the low-level southwesterly jet.Under the influence of diurnal variations and diverse topographic forcing, the radar echo characteristics of the storm cells exhibited distinct features. (1) Storm monomer No. 1 displayed radar echo morphologies such as an inflow notch, a bounded weak echo region (BWER), and a "V" notch, with radial velocity indicating a mesocyclone structure. During the hailfall period, the average composite reflectivity was 60.5 dBz, the average vertically integrated liquid (VIL) was 36.1 kg·m?2, and the average VIL density (VILD) was 4.0 g·m?3. In contrast, Storm monomer No. 2 exhibited a prominent rear-inflow jet (RIJ) and a forward-flank inflow notch (FIN), with more pronounced topographic responses in its echo, after crossing the Lancang River, the strong echo area, VIL, and VILD increased abruptly, with VILD rising from 1.7 g·m?3 to 4.5 g·m?3. (2) The life cycles and surface severe weather manifestations of the storm cells differed significantly. Cell 1 had a lifespan of 6 hours, accompanied by continuous hailfall during its influence period, with thunderstorm winds observed before and after its passage. The precipitation phase transitioned to a mix of hail and short-term heavy rainfall exceeding 20 mm·h?1 in the later stage. Cell 2 had a lifespan of 3 hours, with hailfall occurring only in the later stage of its development, and other types of convective weather were less intense.
Based on C-band weather radar products and multi-source observations, the persistent severe storm weather process and two major rainstorm monomers in southwest Yunnan was analyzed on 13-15 March 2023, and the results were as followed. The severe storm weather process occurred in the circulation background of the eastward retreat of the cold front on the ground, the establishment and intensification of the southwesterly rapids in the low (upper) air, and the persistent intrusion of the mid-level northwesterly flow, and the storm singletons mainly developed and intensified near the angle of the intersection of the mid- and high-altitude rapids. The continuous and stable transport of the low-level warm advection and the mid-level cold advection in southwest Yunnan intensifies the unstable stratification of the ambient atmosphere. The effective potential energy of convection is 826.6-1481.6 J·kg-1, the vertical wind shear from 0 to 3 km becomes 14.4-19.9 m·s-1, and that from 0 to 6 km becomes 27.6-34.5 m·s-1, and the unstable stratification of the high-level stratification and the strong shear environment are the main reasons for the development and maintenance of the catastrophic storms.The daytime storm was triggered by the coupling of southerly wind uplift forced by warm advection with weak surface convergence lines. The significant thermal and moisture contrast on either side of the Wuliang Mountains enhanced the storm"s development. In contrast, the nighttime storm initially formed near the mid-to-low-level baroclinic frontogenesis zone and was triggered by upslope lifting during its eastward movement, intensifying under the influence of the low-level southwesterly jet.Under the influence of diurnal variations and diverse topographic forcing, the radar echo characteristics of the storm cells exhibited distinct features. (1) Storm monomer No. 1 displayed radar echo morphologies such as an inflow notch, a bounded weak echo region (BWER), and a "V" notch, with radial velocity indicating a mesocyclone structure. During the hailfall period, the average composite reflectivity was 60.5 dBz, the average vertically integrated liquid (VIL) was 36.1 kg·m?2, and the average VIL density (VILD) was 4.0 g·m?3. In contrast, Storm monomer No. 2 exhibited a prominent rear-inflow jet (RIJ) and a forward-flank inflow notch (FIN), with more pronounced topographic responses in its echo, after crossing the Lancang River, the strong echo area, VIL, and VILD increased abruptly, with VILD rising from 1.7 g·m?3 to 4.5 g·m?3. (2) The life cycles and surface severe weather manifestations of the storm cells differed significantly. Cell 1 had a lifespan of 6 hours, accompanied by continuous hailfall during its influence period, with thunderstorm winds observed before and after its passage. The precipitation phase transitioned to a mix of hail and short-term heavy rainfall exceeding 20 mm·h?1 in the later stage. Cell 2 had a lifespan of 3 hours, with hailfall occurring only in the later stage of its development, and other types of convective weather were less intense.
Available online: March 11, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.022601
Abstract:
A cumuliform cloud with supercooled water is the condition required for the icing test flight, which is referred to as supercooled cumuliform cloud in this paper. On the basis of the cloud phase state, cloud classification and liquid water top height data from CloudSat-CALIPSO cloud products and the air temperature from ERA5 reanalysis data, focusing on the local solar afternoon data with good interannual continuity, the historical supercooled cloud sample data over China from 2006-2019 were derived, and the spatiotemporal distribution characteristics of supercooled cumuliform clouds were analyzed. The supercooled cumuliform clouds in China most occur in the eastern part of the Qinghai?Xizang Plateau and extend to central China via the Yunnan–Guizhou–Sichuan region, with an annual average occurrence frequency of 0.4. The high value areas of supercooled cumuliform clouds are more westward than that of supercooled stratiform cloud and the occurrence frequency is higher. The occurrence frequencies of the four types of supercooled cumuliform clouds in descending order were as follows: altocumulus over Southwest China, Central China, and East China; stratocumulus over the plateau and the eastern sea surface; cumulus over the southern side of the plateau; and deep convection over Yunnan, Central China, and the southeast land and sea. In winter, there are three high-value centers over Sichuan, Guizhou, the ocean over eastern China, and the Sea of Japan, while the high-value center in summer extends from the eastern part of the Qinghai–Xizang Plateau to other locations on the plateau and the surrounding mountainous areas. In addition, the interannual variation of supercooled cumuliform clouds showed significant increasing trends in January in central China, the west of Northwest China and the west of the Qinghai-Xizang Plateau.
A cumuliform cloud with supercooled water is the condition required for the icing test flight, which is referred to as supercooled cumuliform cloud in this paper. On the basis of the cloud phase state, cloud classification and liquid water top height data from CloudSat-CALIPSO cloud products and the air temperature from ERA5 reanalysis data, focusing on the local solar afternoon data with good interannual continuity, the historical supercooled cloud sample data over China from 2006-2019 were derived, and the spatiotemporal distribution characteristics of supercooled cumuliform clouds were analyzed. The supercooled cumuliform clouds in China most occur in the eastern part of the Qinghai?Xizang Plateau and extend to central China via the Yunnan–Guizhou–Sichuan region, with an annual average occurrence frequency of 0.4. The high value areas of supercooled cumuliform clouds are more westward than that of supercooled stratiform cloud and the occurrence frequency is higher. The occurrence frequencies of the four types of supercooled cumuliform clouds in descending order were as follows: altocumulus over Southwest China, Central China, and East China; stratocumulus over the plateau and the eastern sea surface; cumulus over the southern side of the plateau; and deep convection over Yunnan, Central China, and the southeast land and sea. In winter, there are three high-value centers over Sichuan, Guizhou, the ocean over eastern China, and the Sea of Japan, while the high-value center in summer extends from the eastern part of the Qinghai–Xizang Plateau to other locations on the plateau and the surrounding mountainous areas. In addition, the interannual variation of supercooled cumuliform clouds showed significant increasing trends in January in central China, the west of Northwest China and the west of the Qinghai-Xizang Plateau.
Available online: February 19, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.021801
Abstract:
Based on the hourly precipitation data of 122 national meteorological stations in Shandong from 1966 to 2023, the frequency variation of heavy precipitation are analyzed. Different marginal distribution functions are used to fit the duration and amount of precipitation and the change patterns of the return periods of heavy precipitation with different durations based on Copula function are investigated. The results are as followed. There is a significant dependence relation between the duration and amount of heavy precipitation, which can be fitted well using generalized extreme values and logarithmic normal distribution functions. The Gumbel Copula and Clayton Copula functions are suitable for portraying the dependence structure of the binary variables of the short-duration heavy precipitation in Shandong, while the Clayton Copula function is more appropriate when the precipitation lasts more than 8 h. The return period estimated by daily precipitation may seriously underestimate the hazard of short-duration heavy precipitation. For a short-duration heavy precipitation event under the same hazard-bearing condition, the shorter the duration, the longer the joint return period. The high-value areas of joint return period estimated by the Copula function gradually narrow down from the east and the south of Shandong to the east of Shandong with the increase of precipitation duration, and especially, the hazard of heavy precipitation that comes along once every 60 years is higher in the east and the south of Shandong. This method can more scientifically describe the disaster risks of heavy precipitation in different scenarios, especially in the short-duration heavy precipitation scenario, providing scientific reference for disaster prevention and mitigation planning and disaster risk managing in Shandong.
Based on the hourly precipitation data of 122 national meteorological stations in Shandong from 1966 to 2023, the frequency variation of heavy precipitation are analyzed. Different marginal distribution functions are used to fit the duration and amount of precipitation and the change patterns of the return periods of heavy precipitation with different durations based on Copula function are investigated. The results are as followed. There is a significant dependence relation between the duration and amount of heavy precipitation, which can be fitted well using generalized extreme values and logarithmic normal distribution functions. The Gumbel Copula and Clayton Copula functions are suitable for portraying the dependence structure of the binary variables of the short-duration heavy precipitation in Shandong, while the Clayton Copula function is more appropriate when the precipitation lasts more than 8 h. The return period estimated by daily precipitation may seriously underestimate the hazard of short-duration heavy precipitation. For a short-duration heavy precipitation event under the same hazard-bearing condition, the shorter the duration, the longer the joint return period. The high-value areas of joint return period estimated by the Copula function gradually narrow down from the east and the south of Shandong to the east of Shandong with the increase of precipitation duration, and especially, the hazard of heavy precipitation that comes along once every 60 years is higher in the east and the south of Shandong. This method can more scientifically describe the disaster risks of heavy precipitation in different scenarios, especially in the short-duration heavy precipitation scenario, providing scientific reference for disaster prevention and mitigation planning and disaster risk managing in Shandong.
Available online: February 18, 2025 , DOI: 10.7519/j.issn.1000-0526.2025.011603
Abstract:
On August 13, 2022, a local severe convection occurred near the coast of Shanghai under the control of Western Pacific subtropical high. This event displayed characteristics of a short life span, strong local manifestation, and high intensity. Using data from minute-level ground automatic weather stations, FY-4A geostationary meteorological satellite visible light cloud images, and dual-polarization radar reflectivity factor, a study was conducted on the short-range forecasting techniques and causes of this local strong convection, employing diagnostic variables such as Q vector, perturbation dew point temperature and perturbation temperature. The findings are as follows:(1) The occurrence of precipitation at the ground level was identified as the sign of local strong convective events. By analyzing radar reflectivity factor, satellite visible light cloud images, and Q vector divergence combined with perturbation dew point temperature and perturbation temperature data from ground automatic weather stations, advanced warnings of the convective event could be issued 23, 70, and 100 minutes in advance, respectively. This integrated monitoring and mutual verification of the atmospheric, satellite, and ground observations not only improved the lead time of early warnings for local severe convection but also reduced missed detections. (2) Under the control of the Western Pacific subtropical high-pressure system, temperatures exceeding 35 ℃, combined with the perturbations in temperature and dew point near the urban area, provided favorable thermodynamic conditions for the initiation of deep convection. Simultaneously, differences in land and water underlying characteristics led to higher temperatures on urban land compared to the adjacent Yangtze River water, generating onshore winds. On one hand, this process experienced abrupt changes in land-water underlying characteristics and complex urban land surfaces, causing convergence of wind direction and speed. On the other hand, the convergence of warm and cold air led to atmospheric instability, providing favorable local dynamic forcing conditions. (3) Further analysis reveals that the appearance of significant Q vector divergence convergence at the surface, persisting until surface precipitation occurs, indicates the generation of vertical upward motion due to the dynamic and thermal forcing at the surface. Furthermore, the interaction between the sea breeze front and the convergence-induced updrafts from the urban heat island results in local severe convection.
On August 13, 2022, a local severe convection occurred near the coast of Shanghai under the control of Western Pacific subtropical high. This event displayed characteristics of a short life span, strong local manifestation, and high intensity. Using data from minute-level ground automatic weather stations, FY-4A geostationary meteorological satellite visible light cloud images, and dual-polarization radar reflectivity factor, a study was conducted on the short-range forecasting techniques and causes of this local strong convection, employing diagnostic variables such as Q vector, perturbation dew point temperature and perturbation temperature. The findings are as follows:(1) The occurrence of precipitation at the ground level was identified as the sign of local strong convective events. By analyzing radar reflectivity factor, satellite visible light cloud images, and Q vector divergence combined with perturbation dew point temperature and perturbation temperature data from ground automatic weather stations, advanced warnings of the convective event could be issued 23, 70, and 100 minutes in advance, respectively. This integrated monitoring and mutual verification of the atmospheric, satellite, and ground observations not only improved the lead time of early warnings for local severe convection but also reduced missed detections. (2) Under the control of the Western Pacific subtropical high-pressure system, temperatures exceeding 35 ℃, combined with the perturbations in temperature and dew point near the urban area, provided favorable thermodynamic conditions for the initiation of deep convection. Simultaneously, differences in land and water underlying characteristics led to higher temperatures on urban land compared to the adjacent Yangtze River water, generating onshore winds. On one hand, this process experienced abrupt changes in land-water underlying characteristics and complex urban land surfaces, causing convergence of wind direction and speed. On the other hand, the convergence of warm and cold air led to atmospheric instability, providing favorable local dynamic forcing conditions. (3) Further analysis reveals that the appearance of significant Q vector divergence convergence at the surface, persisting until surface precipitation occurs, indicates the generation of vertical upward motion due to the dynamic and thermal forcing at the surface. Furthermore, the interaction between the sea breeze front and the convergence-induced updrafts from the urban heat island results in local severe convection.
Available online: January 06, 2025 , DOI: 10.7519/j.issn.1000-0526.2024.123001
Abstract:
This study examines the multi-scale processes responsible for an extreme thunderstorm downburst event (peak wind 31.5 m·s-1) that occurred at Tianjin Airport on 4 August 2013, focusing on the synoptic background, structural characteristics of the storm, and dynamical mechanisms of the severe winds. The results show that this event developed within a post-trough unstable environment, characterized by a pronounced dry layer in the mid-troposphere and moisture concentration below 925 hPa. Convective available potential energy (CAPE) exceeding 3000 J·kg-1, coupled with strong 0-6 km vertical wind shear and steep temperature lapse rates in the boundary layer, established a favorable environment for thunderstorm gales. The damaging winds originated from a squall line propagating rapidly from northwest to southeast. The passage of its leading gust front triggered the initial wind surge, while subsequent extreme winds during the second phase resulted from a downburst generated by an intensifying multi-cell storm embedded in the squall line. Both the squall line and downburst exhibited significant mobility, with precipitation-induced evaporative cooling, hydrometeor loading, and mid-level convergence identified as primary drivers of downburst formation.
This study examines the multi-scale processes responsible for an extreme thunderstorm downburst event (peak wind 31.5 m·s-1) that occurred at Tianjin Airport on 4 August 2013, focusing on the synoptic background, structural characteristics of the storm, and dynamical mechanisms of the severe winds. The results show that this event developed within a post-trough unstable environment, characterized by a pronounced dry layer in the mid-troposphere and moisture concentration below 925 hPa. Convective available potential energy (CAPE) exceeding 3000 J·kg-1, coupled with strong 0-6 km vertical wind shear and steep temperature lapse rates in the boundary layer, established a favorable environment for thunderstorm gales. The damaging winds originated from a squall line propagating rapidly from northwest to southeast. The passage of its leading gust front triggered the initial wind surge, while subsequent extreme winds during the second phase resulted from a downburst generated by an intensifying multi-cell storm embedded in the squall line. Both the squall line and downburst exhibited significant mobility, with precipitation-induced evaporative cooling, hydrometeor loading, and mid-level convergence identified as primary drivers of downburst formation.
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2012,38(12):1482-1491, DOI: 10.7519/j.issn.1000-0526.2012.12.005
Abstract:
By using the conventional meteorological data, Doppler radar data and NCEP/NCAR reanalysis data, the characteristics of Doppler radar’s reflectivity, environmental condition and trigger mechanism of the heavy rain are analyzed and compared between two abrupt heavy rain processes occurring in Sichuan Basin on 3 July (7.3) and 23 July (7.23) 2011. The results show that: the “7.3” heavy rain happened under a typical circulation background, and moisture transporting to the heavy rain area from the South China Sea was smoothly, thus the heavy rainfall maintained so long, but the “7.23” heavy rain occurred behind the upper cold vortex, and convective unstable energy was abundant and vertical wind shear was strong, thus this heavy rain process happened with hail and thunderstorm weather accompanied, its radar reflectivity was 5 dBz stronger than “7.3” case and had the characteristics of severe storms such as the low level weak reflectivity and the upper echo overhang. As a whole, the non equilibrium force is contributed to the occurrence of heavy rain and it is the excited mechanism of the two heavy rainfalls, and the change of the divergence evolvement is consistent with the strength and the position of the heavy rain which would happen 6 hours later．
By using the conventional meteorological data, Doppler radar data and NCEP/NCAR reanalysis data, the characteristics of Doppler radar’s reflectivity, environmental condition and trigger mechanism of the heavy rain are analyzed and compared between two abrupt heavy rain processes occurring in Sichuan Basin on 3 July (7.3) and 23 July (7.23) 2011. The results show that: the “7.3” heavy rain happened under a typical circulation background, and moisture transporting to the heavy rain area from the South China Sea was smoothly, thus the heavy rainfall maintained so long, but the “7.23” heavy rain occurred behind the upper cold vortex, and convective unstable energy was abundant and vertical wind shear was strong, thus this heavy rain process happened with hail and thunderstorm weather accompanied, its radar reflectivity was 5 dBz stronger than “7.3” case and had the characteristics of severe storms such as the low level weak reflectivity and the upper echo overhang. As a whole, the non equilibrium force is contributed to the occurrence of heavy rain and it is the excited mechanism of the two heavy rainfalls, and the change of the divergence evolvement is consistent with the strength and the position of the heavy rain which would happen 6 hours later．
2017,43(7):769-780, DOI: 10.7519/j.issn.1000-0526.2017.07.001
Abstract:
The spatial distributions of severe convective wind (SCW) and nonsevere thunderstorms (NT) over South China, occurring between 08:00 BT and 20:00 BT during spring and summer in 2010-2014, were analyzed by using the observational data from China Meteorological Administration. And then, their environmental characteristics were compared between SCW and NT in spring and summer. It was found that SCW in summer is more frequently than that in spring and that NT in summer is about 3.6 times the counts of NT in spring. SCW events mainly concentrate in the western Guangdong to the Pearl River Delta Region. Compared to NT, SCW is generally associated with stronger baroclinity, instability and stronger dynamic forcing. The precipitable water and averaged relative humidity between 700-500 hPa of SCW tend to be higher than those of NT in spring, while the opposite is the case for the pattern in summer. In conclusion, it is obvious that the dynamic forcing for SCW in spring is much better than these in summer, while the thermal condition is more significant in summer.
The spatial distributions of severe convective wind (SCW) and nonsevere thunderstorms (NT) over South China, occurring between 08:00 BT and 20:00 BT during spring and summer in 2010-2014, were analyzed by using the observational data from China Meteorological Administration. And then, their environmental characteristics were compared between SCW and NT in spring and summer. It was found that SCW in summer is more frequently than that in spring and that NT in summer is about 3.6 times the counts of NT in spring. SCW events mainly concentrate in the western Guangdong to the Pearl River Delta Region. Compared to NT, SCW is generally associated with stronger baroclinity, instability and stronger dynamic forcing. The precipitable water and averaged relative humidity between 700-500 hPa of SCW tend to be higher than those of NT in spring, while the opposite is the case for the pattern in summer. In conclusion, it is obvious that the dynamic forcing for SCW in spring is much better than these in summer, while the thermal condition is more significant in summer.
2010,36(3):9-18, DOI: 10.7519/j.issn.1000-0526.2010.3.002
Abstract:
Potential vorticity (PV) is one of the important concepts in advanced synoptic and dynamic meteorology. This paper is a brief introduction to the theory of potential vorticity, including the concept of PV, the conservation and invertibility of PV, PV thinking, moist PV (MPV), and the application of PV theory.
Potential vorticity (PV) is one of the important concepts in advanced synoptic and dynamic meteorology. This paper is a brief introduction to the theory of potential vorticity, including the concept of PV, the conservation and invertibility of PV, PV thinking, moist PV (MPV), and the application of PV theory.
FU Jiaolan, MA Xuekuan, CHEN Tao, ZHANG Fang, ZHANG Xidi, SUN Jun, QUAN Wanqing, YANG Shunan, SHEN Xiaolin
2017,43(5):528-539, DOI: 10.7519/j.issn.1000-0526.2017.05.002
Abstract:
An extremely severe precipitation event took place in North China in 19-20 July 2016. It was characterized by large rainfall, persistent rainfall, warm cloud rainfall, strong local rainfall intensity and orographic precipitation. Its rainfall was larger than that of the extreme rainfall in 3-5 August 1996, and only next to the amount of the 2-7 August 1963 extreme rainfall event. It occurred under the circulation background of the South Asia high moving eastward, the West Pacific subtropical high moving northwestward and the low vortex in the westerlies developing in mid high latitude. The abnormal development of Huanghuai cyclone, southwest and southeast low level jets, and the abnormally abundant moisture indicates that the dynamic lifting and moisture conditions favored this severe rainfall process significantly. The whole rainfall event presented clearly the phase characteristics, and could be divided into two stages. The first stage was the orographic rainfall caused by the easterly winds ahead of the trough from the early morning to the daytime of 19 July, while the second part was produced by spiral rain bands in the north side of Huanghuai cyclone from the night of 19 to the daytime of 20 July. In the first stage, the easterly low level jet was lifted by the Taihang Mountains, which continuously triggered the convective cells along the east edge of the mountains. The weak dry and cold advection at mid level and the strong warm and wet advection at low level jointly maintained the convective instability. The cold pool generated by heavy rainfall and the mesoscale frontogenesis process created by local orographic effect provided favorable conditions for severe convections to occur continuously. The second stage rainfall was mainly related to the development of cut off vortex and Huanghuai cyclone. The blocking of the high pressure system slowed the steps of Huanghuai cyclone in North China, thus leading to the long lasting rainfall process.
An extremely severe precipitation event took place in North China in 19-20 July 2016. It was characterized by large rainfall, persistent rainfall, warm cloud rainfall, strong local rainfall intensity and orographic precipitation. Its rainfall was larger than that of the extreme rainfall in 3-5 August 1996, and only next to the amount of the 2-7 August 1963 extreme rainfall event. It occurred under the circulation background of the South Asia high moving eastward, the West Pacific subtropical high moving northwestward and the low vortex in the westerlies developing in mid high latitude. The abnormal development of Huanghuai cyclone, southwest and southeast low level jets, and the abnormally abundant moisture indicates that the dynamic lifting and moisture conditions favored this severe rainfall process significantly. The whole rainfall event presented clearly the phase characteristics, and could be divided into two stages. The first stage was the orographic rainfall caused by the easterly winds ahead of the trough from the early morning to the daytime of 19 July, while the second part was produced by spiral rain bands in the north side of Huanghuai cyclone from the night of 19 to the daytime of 20 July. In the first stage, the easterly low level jet was lifted by the Taihang Mountains, which continuously triggered the convective cells along the east edge of the mountains. The weak dry and cold advection at mid level and the strong warm and wet advection at low level jointly maintained the convective instability. The cold pool generated by heavy rainfall and the mesoscale frontogenesis process created by local orographic effect provided favorable conditions for severe convections to occur continuously. The second stage rainfall was mainly related to the development of cut off vortex and Huanghuai cyclone. The blocking of the high pressure system slowed the steps of Huanghuai cyclone in North China, thus leading to the long lasting rainfall process.
2006,32(10):64-69, DOI: 10.7519/j.issn.1000-0526.2006.10.010
Abstract:
Based on the data of CINRAD Doppler Radar which located at Xinle of Hebei Province,the hail,strong wind and heavy rainfall weather events in mid-south Hebei in 2004 are statistically analyzed.The routine radar products,such as echo reflectivity,radial velocity,Vertically Integrated Liquid(VIL)Water,hail index,mesocyclone,velocity azimuth display wind profile,etc.are used in this statistics.The results show that hail's VIL value is larger than generic thunder storm's.At the same time,greater VIL value and longer sustaining will bring about greater diameter hail and larger effect area.It is the very useful index to indicate strong wind in mesocyclone products and the wind direction sudden change in radial velocity products.A reference based on analyzing this type synoptic forecast with radar system in future is proposed.
Based on the data of CINRAD Doppler Radar which located at Xinle of Hebei Province,the hail,strong wind and heavy rainfall weather events in mid-south Hebei in 2004 are statistically analyzed.The routine radar products,such as echo reflectivity,radial velocity,Vertically Integrated Liquid(VIL)Water,hail index,mesocyclone,velocity azimuth display wind profile,etc.are used in this statistics.The results show that hail's VIL value is larger than generic thunder storm's.At the same time,greater VIL value and longer sustaining will bring about greater diameter hail and larger effect area.It is the very useful index to indicate strong wind in mesocyclone products and the wind direction sudden change in radial velocity products.A reference based on analyzing this type synoptic forecast with radar system in future is proposed.
Zhou Yuquan, Chen Yingying, Li Juan, Huang Yimei, He Xiaodong, Zhou Feifei, Wu Menxin, Hu Bo, Mao Jietai
2008,34(12):27-35, DOI: 10.7519/j.issn.1000-0526.2008.12.004
Abstract:
Cloud macro and micro physical characteristic parameters play an important role not only in the field of the analysis and forecast of the weather and climate, but also in the field of weather modification to identify the seeding c ondition. Based on the data from FY-2C/D stationary satellite and SBDART radiati on transfer model, associated with the sounding data and surface information, a method retrieving cloud macro and micro physical parameters is established in th is research. These parameters include cloud top height, cloud top temperature, d epth of super-cooled layer, depth of warm layer, cloud bottom height, depth of c loud, cloud optical thickness, cloud effective particle radius and cloud liquid water content. It has been run operationally. In this paper, the correlated info rmation such as physical meaning, retrieving method and technology, retrieving p rocess and data format are simply introduced. Furthermore, comparing with the ob servation of Cloudsat up to the minute, the retrieving results of main cloud par ameters are proved to be reasonable and usable. By contrast with same kind produ cts of MODIS, it also shows good corresponding relationship.
Cloud macro and micro physical characteristic parameters play an important role not only in the field of the analysis and forecast of the weather and climate, but also in the field of weather modification to identify the seeding c ondition. Based on the data from FY-2C/D stationary satellite and SBDART radiati on transfer model, associated with the sounding data and surface information, a method retrieving cloud macro and micro physical parameters is established in th is research. These parameters include cloud top height, cloud top temperature, d epth of super-cooled layer, depth of warm layer, cloud bottom height, depth of c loud, cloud optical thickness, cloud effective particle radius and cloud liquid water content. It has been run operationally. In this paper, the correlated info rmation such as physical meaning, retrieving method and technology, retrieving p rocess and data format are simply introduced. Furthermore, comparing with the ob servation of Cloudsat up to the minute, the retrieving results of main cloud par ameters are proved to be reasonable and usable. By contrast with same kind produ cts of MODIS, it also shows good corresponding relationship.
2012,38(10):1255-1266, DOI: 10.7519/j.issn.1000-0526.2012.10.012
Abstract:
Precipitation characteristics, environment conditions, generation and development of the mesoscale convective system that brought about the extreme torrential rain in Beijing on 21 July 2012 were analyzed comprehensively in this paper by using various conventional and unconventional data. The results showed that the extreme torrential rain had the characteristics of long duration, great rainfall and wide coverage area and its process consisted of warm area precipitation and frontal precipitation. The warm area rainfall started earlier, the severe precipitation center was scattered and lasted long while the frontal rainfallprocess contained several severe rainfall centers with high precipitation efficiency, lasting a short time.Environment conditions of the mesoscale convective system that triggered this extreme severe rainfall were analyzed. The results showed that interactions of high level divergence, the wind shear and convergence with the vortex in the lower troposphere and the surface wind convergence line provided favorable environment to the severe extreme rain. The warm humid airs from the tropical and sub tropical zones converged over the torrential rain region, continuous and sufficient water vapor manifested as high atmospheric column of precipitable water and strong low level water vapor convergence and other extreme vapor conditions for the torrential rain. In addition, the intense precipitation was triggered by the vortex wind shear, wind disturbance on low level jet, surface wind convergence line and the effect of terrain under the condition of the plentiful water vapour and maintained. With the cold front moved eastward, heavy frontal rainfall was brought by the development and evolution of convective system made by the cold air and the suitable vertical wind shear.Generation and development processes of the mesoscale convective system were also studied. The findings suggested that stratiform cloud precipitation and dispersed convective precipitation occurred firstly in the precipitation process. The warm and steady stratiform cloud precipitation changed to be highly organized convectional precipitation as the cold dry air invaded. Many small scale and mesoscale convective clusters developed into mesoscale convective complex (MCC), leading to the extreme severe precipitation. Since all the directions of the echo long axis, terrain and echo movement were parallel, train effect was obviously seen in the radar echo imegery during this precipitation process. Meanwhile, the radar echo had the characteristics of backward propagation and low centroid which was similar to tropical heavy rainfalls. Finally, a series of scientific problems were proposed according to the integrated analysis on the observation data of this rare torrential rain event, such as the causes for the extreme torrential rain and the extreme rich water vapor, mechanisms for the warm area torrential rain in the north of China, the mechanism for the train effect and backward propagation, mechanisms for the organization and maintenance of the convective cells, the simulation and analysis ability of the numerical models to extreme torrential rains and so on.
Precipitation characteristics, environment conditions, generation and development of the mesoscale convective system that brought about the extreme torrential rain in Beijing on 21 July 2012 were analyzed comprehensively in this paper by using various conventional and unconventional data. The results showed that the extreme torrential rain had the characteristics of long duration, great rainfall and wide coverage area and its process consisted of warm area precipitation and frontal precipitation. The warm area rainfall started earlier, the severe precipitation center was scattered and lasted long while the frontal rainfallprocess contained several severe rainfall centers with high precipitation efficiency, lasting a short time.Environment conditions of the mesoscale convective system that triggered this extreme severe rainfall were analyzed. The results showed that interactions of high level divergence, the wind shear and convergence with the vortex in the lower troposphere and the surface wind convergence line provided favorable environment to the severe extreme rain. The warm humid airs from the tropical and sub tropical zones converged over the torrential rain region, continuous and sufficient water vapor manifested as high atmospheric column of precipitable water and strong low level water vapor convergence and other extreme vapor conditions for the torrential rain. In addition, the intense precipitation was triggered by the vortex wind shear, wind disturbance on low level jet, surface wind convergence line and the effect of terrain under the condition of the plentiful water vapour and maintained. With the cold front moved eastward, heavy frontal rainfall was brought by the development and evolution of convective system made by the cold air and the suitable vertical wind shear.Generation and development processes of the mesoscale convective system were also studied. The findings suggested that stratiform cloud precipitation and dispersed convective precipitation occurred firstly in the precipitation process. The warm and steady stratiform cloud precipitation changed to be highly organized convectional precipitation as the cold dry air invaded. Many small scale and mesoscale convective clusters developed into mesoscale convective complex (MCC), leading to the extreme severe precipitation. Since all the directions of the echo long axis, terrain and echo movement were parallel, train effect was obviously seen in the radar echo imegery during this precipitation process. Meanwhile, the radar echo had the characteristics of backward propagation and low centroid which was similar to tropical heavy rainfalls. Finally, a series of scientific problems were proposed according to the integrated analysis on the observation data of this rare torrential rain event, such as the causes for the extreme torrential rain and the extreme rich water vapor, mechanisms for the warm area torrential rain in the north of China, the mechanism for the train effect and backward propagation, mechanisms for the organization and maintenance of the convective cells, the simulation and analysis ability of the numerical models to extreme torrential rains and so on.
2013,39(10):1284-1292, DOI: 10.7519/j.issn.1000-0526.2013.10.006
Abstract:
Based on the fog observation data during 24-27 December 2006 (advection radiation fog), NCEP NC reanalysis data (2.5°×2.5°) and GDAS global meteorological data (1°×1°), detailed trajectory analysis of the boundary layer characteristics and water vapor transport of the fog is investigated, combined with the weather condition, meteorological elements and physical quantity field. The results show that: (1) there is thick inversion layer, even multi layer inversion throughout the dense fog event. Temperatures of different inversion tops in the middle and high levels are 2-5℃ higher than the surface temperature. The thickness of inversion layer is more than 200 m, and it gets to 500 m at 08:00 BT 26 December, indicating the atmosphere is very stable and conducive to the convergence of water vapor before the fog forms. However, it is not favorable for the divergence of water vapor after the formation of fog, which helps the development and maintenance of the fog, causing the fog to last about 64 hours with dense fog (visibility <50 m) about 37 hours; (2) The divergence of water vapor flux in low level is negative in the advection fog event. The upper air has persistent moisture convergence and the strongest moisture convergence appears at 02:00 BT 25 December, being -30×10-7 g·s-1·cm-2·hPa-1. The accumulation of low level water vapor makes fog form and develop while the divergence of water vapor flux speeds up its dissipation. 〖JP2〗The long lasting advection radiation fog is mainly caused by the continuous water vapor convergence; (3) The water vapor path is from the coastal area in easten China to Nanjing. The water vapor is continuously supplied from sea during the fog event, with the water vapor flux maximum getting to 2 g·s-1·hPa-1·cm-1. The sufficient supply and supplementary of water vapor determines the duration of the fog.
Based on the fog observation data during 24-27 December 2006 (advection radiation fog), NCEP NC reanalysis data (2.5°×2.5°) and GDAS global meteorological data (1°×1°), detailed trajectory analysis of the boundary layer characteristics and water vapor transport of the fog is investigated, combined with the weather condition, meteorological elements and physical quantity field. The results show that: (1) there is thick inversion layer, even multi layer inversion throughout the dense fog event. Temperatures of different inversion tops in the middle and high levels are 2-5℃ higher than the surface temperature. The thickness of inversion layer is more than 200 m, and it gets to 500 m at 08:00 BT 26 December, indicating the atmosphere is very stable and conducive to the convergence of water vapor before the fog forms. However, it is not favorable for the divergence of water vapor after the formation of fog, which helps the development and maintenance of the fog, causing the fog to last about 64 hours with dense fog (visibility <50 m) about 37 hours; (2) The divergence of water vapor flux in low level is negative in the advection fog event. The upper air has persistent moisture convergence and the strongest moisture convergence appears at 02:00 BT 25 December, being -30×10-7 g·s-1·cm-2·hPa-1. The accumulation of low level water vapor makes fog form and develop while the divergence of water vapor flux speeds up its dissipation. 〖JP2〗The long lasting advection radiation fog is mainly caused by the continuous water vapor convergence; (3) The water vapor path is from the coastal area in easten China to Nanjing. The water vapor is continuously supplied from sea during the fog event, with the water vapor flux maximum getting to 2 g·s-1·hPa-1·cm-1. The sufficient supply and supplementary of water vapor determines the duration of the fog.
ZHANG Xiaoling, ZHANG Tao, LIU Xinhua, ZHOU Qingliang, CHEN Yun, ZHOU Xiaoxia, ZHENG Yongguang, ZHAO Surong
2010,36(7):143-150, DOI: 10.7519/j.issn.1000-0526.2010.7.021
Abstract:
Mesoscale severe weather forecasting ability is limited, in some sense for a lack of valid analysis on mesoscale convective systems and its favorable environments. This paper introduces the mesoscale weather chart analysis techniq ue which was tested in the National Meteorological Center (NMC). Mesoscale weath er chart analyzes the favorable environmental conditions of mesoscale convective systems based on observational data and numerical weather forecast outputs. It includes upper air composite chart and surface chart. In the upper air composite ch art, by analyzing wind, temperature, moisture, temperature change and height change, the diagnostic systems and features in all the lower, middle and upper t roposphere isobaric layers are combined into one plot, which can clearly displa y the available environments and synoptic pattern of severe convective weather. In the surface chart, the analysis contents are pressure, wind, temperature, moi sture, convective weather phenomena and all kinds of boundaries (fronts). The te st in NMC shows that mesoscale weather chart analysis is a dependable means for severe convective weather outlook forecasting.
Mesoscale severe weather forecasting ability is limited, in some sense for a lack of valid analysis on mesoscale convective systems and its favorable environments. This paper introduces the mesoscale weather chart analysis techniq ue which was tested in the National Meteorological Center (NMC). Mesoscale weath er chart analyzes the favorable environmental conditions of mesoscale convective systems based on observational data and numerical weather forecast outputs. It includes upper air composite chart and surface chart. In the upper air composite ch art, by analyzing wind, temperature, moisture, temperature change and height change, the diagnostic systems and features in all the lower, middle and upper t roposphere isobaric layers are combined into one plot, which can clearly displa y the available environments and synoptic pattern of severe convective weather. In the surface chart, the analysis contents are pressure, wind, temperature, moi sture, convective weather phenomena and all kinds of boundaries (fronts). The te st in NMC shows that mesoscale weather chart analysis is a dependable means for severe convective weather outlook forecasting.
2009,35(1):55-64, DOI: 10.7519/j.issn.1000-0526.2009.1.007
Abstract:
A strong rainstorm is analysis which occurred in Xinghua located the north of Ji angsu province on 25 July 2007. Results show that wind disaster originated from two kinds of rainstorm. One kind was the gust front which occurred at the front of the storm. Strong wind of grade 7-9 was attained when it happened. Another ki nd was the downburst arose in the multi cell storm. The original height of refl ectivity core was higher than -20℃ isotherm. It had the characteristics of conv ergence on the mid level and descending of reflectivity core. The strong wind ab ove grade 10 was attained, when the descending airflow diverged strongly on the ground. A new cell was combined with the former storm above the gust front, thus the storm enhanced. When the downburst happened, the storm weakened, and another new cell was combin ed with the former storm. The downburst happened continuously, and the impact of gust front persisted.
A strong rainstorm is analysis which occurred in Xinghua located the north of Ji angsu province on 25 July 2007. Results show that wind disaster originated from two kinds of rainstorm. One kind was the gust front which occurred at the front of the storm. Strong wind of grade 7-9 was attained when it happened. Another ki nd was the downburst arose in the multi cell storm. The original height of refl ectivity core was higher than -20℃ isotherm. It had the characteristics of conv ergence on the mid level and descending of reflectivity core. The strong wind ab ove grade 10 was attained, when the descending airflow diverged strongly on the ground. A new cell was combined with the former storm above the gust front, thus the storm enhanced. When the downburst happened, the storm weakened, and another new cell was combin ed with the former storm. The downburst happened continuously, and the impact of gust front persisted.
2014,40(4):400-411, DOI: 10.7519/j.issn.1000-0526.2014.04.002
Abstract:
Based on the synoptic environment analysis of about 100 severe convection cases in China since 2000 and the reference of related literatures, from the perspectives of the three essential conditions for the development of severe convection, namely the thermal instability, lift and moisture, five basic synoptic situation configurations of severe convection in China are proposed and expounded. They are cold advection forcing category, warm advection forcing category, baroclinic frontogenesis category, quasi barotropic category and elevated thunderstorm category. The typical characteristics of the upper cold advection forcing category is that the mid upper strong cold advection above 500 hPa strengthens and reaches the boundary warm convergence zone. The warm advection forcing category is characterized by trough with special structure moving over low level strong warm and moist advection. The deep convection produced by the mid lower layer convergence of cold and warm air features the baroclinic frontogenesis category. The quasi barotropic category mostly occurs at the northern and the southern edges or the interior of summer subtropical high and the area with weak baroclinicity, where the dynamic forcing and the surface inhomogeneous local heating play major roles. The features of elevated thunderstorms are the southwest jet in 700-500 hPa lifted by boundary cold wedge and the instable energy is from above 700 hPa. The classification based on the difference of the formation mechanisms can grasp accurately the synoptic characteristics, the situation configurations, the dynamic and thermal properties and the key points in analyzing short term potential forecast, providing more technical support to further enhance the level of weather prediction.
Based on the synoptic environment analysis of about 100 severe convection cases in China since 2000 and the reference of related literatures, from the perspectives of the three essential conditions for the development of severe convection, namely the thermal instability, lift and moisture, five basic synoptic situation configurations of severe convection in China are proposed and expounded. They are cold advection forcing category, warm advection forcing category, baroclinic frontogenesis category, quasi barotropic category and elevated thunderstorm category. The typical characteristics of the upper cold advection forcing category is that the mid upper strong cold advection above 500 hPa strengthens and reaches the boundary warm convergence zone. The warm advection forcing category is characterized by trough with special structure moving over low level strong warm and moist advection. The deep convection produced by the mid lower layer convergence of cold and warm air features the baroclinic frontogenesis category. The quasi barotropic category mostly occurs at the northern and the southern edges or the interior of summer subtropical high and the area with weak baroclinicity, where the dynamic forcing and the surface inhomogeneous local heating play major roles. The features of elevated thunderstorms are the southwest jet in 700-500 hPa lifted by boundary cold wedge and the instable energy is from above 700 hPa. The classification based on the difference of the formation mechanisms can grasp accurately the synoptic characteristics, the situation configurations, the dynamic and thermal properties and the key points in analyzing short term potential forecast, providing more technical support to further enhance the level of weather prediction.
2014,40(2):133-145, DOI: 10.7519/j.issn.1000-0526.2014.02.001
Abstract:
By using the NCEP reanalysis data, the vapor budget of the area covered by the severe torrential rain over the northeast of North China on 21 July, 2012 is calculated according to the vapor budget equation. The results show that meridional water vapor transportation is dominant while the extremely heavy rain hits Beijing Region, where most moist vapor comes from the southern boundary below 500 hPa. The low level regional moisture convergence is consistent with the time and space when the torrential rain breaks out and develops. Above the middle level the vertical vapor transport is more prominent. Then the variation features of the vapor transport corridors and their moisture contributions are got through the HYSPLIT mode. The backward trajectory analyses illustrate two major vapor transport corridors. The moistest vapor derived from Yellow Sea and East China Sea along the low level make the main moisture contribution during the heavy precipitation. Moisture from the South China Sea and the Bay of Bengal strengthens the water vapor in the region when the heavy rain starts and develops. Also the drier vapor corridor along the high level from the northwest of China plays an important role in this case.
By using the NCEP reanalysis data, the vapor budget of the area covered by the severe torrential rain over the northeast of North China on 21 July, 2012 is calculated according to the vapor budget equation. The results show that meridional water vapor transportation is dominant while the extremely heavy rain hits Beijing Region, where most moist vapor comes from the southern boundary below 500 hPa. The low level regional moisture convergence is consistent with the time and space when the torrential rain breaks out and develops. Above the middle level the vertical vapor transport is more prominent. Then the variation features of the vapor transport corridors and their moisture contributions are got through the HYSPLIT mode. The backward trajectory analyses illustrate two major vapor transport corridors. The moistest vapor derived from Yellow Sea and East China Sea along the low level make the main moisture contribution during the heavy precipitation. Moisture from the South China Sea and the Bay of Bengal strengthens the water vapor in the region when the heavy rain starts and develops. Also the drier vapor corridor along the high level from the northwest of China plays an important role in this case.
2012,38(2):164-173, DOI: 10.7519/j.issn.1000-0526.2012.02.004
Abstract:
Many weather forecasters seem to have acquaintance with most of basic concepts or fundamental theories which are connected with severe convection, but some of them are misapplied frequently by some forecasters when they are engaged in severe convective weather analysis or forecasting argumentation. Due to the above problem, some basic concepts and fundamental theories should be explained from the view of forecasting application. The following issues are discussed in this paper. They are the relationship between humidity and water vapor content, the role of clod air during the precipitation process, the fundamental theories connected with thermal and dynamic instability, the sounding analysis related to instability parameters, the relationship between helicity or moist potential vorticity and instability, the relationship among the convergence line, lifting velocity and convective vertical movement, and the essential connection between the synoptic patterns and severe convective phenomena.
Many weather forecasters seem to have acquaintance with most of basic concepts or fundamental theories which are connected with severe convection, but some of them are misapplied frequently by some forecasters when they are engaged in severe convective weather analysis or forecasting argumentation. Due to the above problem, some basic concepts and fundamental theories should be explained from the view of forecasting application. The following issues are discussed in this paper. They are the relationship between humidity and water vapor content, the role of clod air during the precipitation process, the fundamental theories connected with thermal and dynamic instability, the sounding analysis related to instability parameters, the relationship between helicity or moist potential vorticity and instability, the relationship among the convergence line, lifting velocity and convective vertical movement, and the essential connection between the synoptic patterns and severe convective phenomena.
2012,38(1):1-16, DOI: 10.7519/j.issn.1000-0526.2012.01.001
Abstract:
In this paper, the modulation of atmospheric MJO on typhoon generation over the northwestern Pacific and its mechanism are first studied by using the MJO index. The results show that the MJO plays an important modulation role in typhoon generation over the northwestern Pacific: The proportion of typhoon number is 21 between active period and inactive period; During the MJO active period, the proportion of typhoon number is also 2:1 between phases 5-6 and phases 2-3 of MJO. The composite analyses of atmospheric circulation show that there are different circulation patterns over the northwestern Pacific in different phases of the MJO, which will affect the typhoon generation. In phases 5-6 (2-3), the dynamic factor and convective heating patterns over western Pacific are favorable (unfavorable) for typhoon generation. Then， the comparing analyses of the 30-60 day low frequency kinetic energy in lower and higher levels of the troposphere show that the atmospheric intraseasonal oscillation over the northwestern Pacific has a clear impact on the typhoon generation. There is an evident positive (negative) anomaly area of 30-60 day low frequency kinetic energy in the more (less) typhoon years over the northwestern Pacific east of the Philippines, which means that strong (weak) atmospheric intraseasonal oscillation (ISO) over the northwestern Pacific is favorable (unfavorable) for typhoon generation. The analyses of 200 hPa velocity potential show that there is a clear divergence (convergence) pattern over the northwestern Pacific in the more (less) typhoon years, which is favorable (unfavorable) for typhoon generation. The modulation of the intraseasonal oscillation on the typhoon tracks over the northwestern Pacific is studied by observational data analyses. We classified the main classes of typhoon tracks into 5 types as straight west moving typhoons (I), northwest moving typhoons (II), recurving to Korea/west of Japan typhoons (III), landing on Japan typhoons (IV) and recurving to the east of Japan typhoons (V). Then the composite analyses of atmospheric low-frequency wind fields at 850, 500 and 200 hPa, corresponding to the typhoon forming date, for every typhoon track are completed. The analysis results of relationships between the low-frequency (ISO) wind fields and typhoon tracks have indicated that the typhoon tracks will be affected by wind pattern of the ISO. The low frequency positive vorticity belt (the maximum value line of cyclonic vorticity) associated with low-frequency cyclone (LFC) at 850 hPa is so closely related to the typhoon track, that the maximum value line (belt) of low frequency cyclonic vorticity can be an important factor to predicate the typhoon tracks over the northwestern Pacific. And the typhoon tracks will be also affected by the ISO circulation pattern at 200 hPa, particularly the strong low frequency wind associated with low frequency anticyclone (LFAC).
In this paper, the modulation of atmospheric MJO on typhoon generation over the northwestern Pacific and its mechanism are first studied by using the MJO index. The results show that the MJO plays an important modulation role in typhoon generation over the northwestern Pacific: The proportion of typhoon number is 21 between active period and inactive period; During the MJO active period, the proportion of typhoon number is also 2:1 between phases 5-6 and phases 2-3 of MJO. The composite analyses of atmospheric circulation show that there are different circulation patterns over the northwestern Pacific in different phases of the MJO, which will affect the typhoon generation. In phases 5-6 (2-3), the dynamic factor and convective heating patterns over western Pacific are favorable (unfavorable) for typhoon generation. Then， the comparing analyses of the 30-60 day low frequency kinetic energy in lower and higher levels of the troposphere show that the atmospheric intraseasonal oscillation over the northwestern Pacific has a clear impact on the typhoon generation. There is an evident positive (negative) anomaly area of 30-60 day low frequency kinetic energy in the more (less) typhoon years over the northwestern Pacific east of the Philippines, which means that strong (weak) atmospheric intraseasonal oscillation (ISO) over the northwestern Pacific is favorable (unfavorable) for typhoon generation. The analyses of 200 hPa velocity potential show that there is a clear divergence (convergence) pattern over the northwestern Pacific in the more (less) typhoon years, which is favorable (unfavorable) for typhoon generation. The modulation of the intraseasonal oscillation on the typhoon tracks over the northwestern Pacific is studied by observational data analyses. We classified the main classes of typhoon tracks into 5 types as straight west moving typhoons (I), northwest moving typhoons (II), recurving to Korea/west of Japan typhoons (III), landing on Japan typhoons (IV) and recurving to the east of Japan typhoons (V). Then the composite analyses of atmospheric low-frequency wind fields at 850, 500 and 200 hPa, corresponding to the typhoon forming date, for every typhoon track are completed. The analysis results of relationships between the low-frequency (ISO) wind fields and typhoon tracks have indicated that the typhoon tracks will be affected by wind pattern of the ISO. The low frequency positive vorticity belt (the maximum value line of cyclonic vorticity) associated with low-frequency cyclone (LFC) at 850 hPa is so closely related to the typhoon track, that the maximum value line (belt) of low frequency cyclonic vorticity can be an important factor to predicate the typhoon tracks over the northwestern Pacific. And the typhoon tracks will be also affected by the ISO circulation pattern at 200 hPa, particularly the strong low frequency wind associated with low frequency anticyclone (LFAC).
2015,41(2):212-218, DOI: 10.7519/j.issn.1000-0526.2015.02.009
Abstract:
From 1 May to 8 June 2013 CMA Meteorological Observation Centre conducted an experiment of cloud height observations by using cloud radar (35 GHz), whose observation data are the echo power value and temporal resolution is 1 min and a ceilometer whose observation data are the back scattering intens data with 1 min temporal resolution. The result of analyzing the data observed from the 39 d experiment indicates that: (1) the data acquisition ratio of cloud radar is 26% larger than that of ceilometer; (2) the ratio is 51% in fog haze weather; (3) relatively, precipitation has more significant effect on cloud base height measured by laser ceilometer than that by cloud radar; (4) height of cloud base measured by cloud radar is almost consistent with the height by ceilometer because their average deviation is less than 300 m.
From 1 May to 8 June 2013 CMA Meteorological Observation Centre conducted an experiment of cloud height observations by using cloud radar (35 GHz), whose observation data are the echo power value and temporal resolution is 1 min and a ceilometer whose observation data are the back scattering intens data with 1 min temporal resolution. The result of analyzing the data observed from the 39 d experiment indicates that: (1) the data acquisition ratio of cloud radar is 26% larger than that of ceilometer; (2) the ratio is 51% in fog haze weather; (3) relatively, precipitation has more significant effect on cloud base height measured by laser ceilometer than that by cloud radar; (4) height of cloud base measured by cloud radar is almost consistent with the height by ceilometer because their average deviation is less than 300 m.
2011,37(10):1262-1269, DOI: 10.7519/j.issn.1000-0526.2011.10.009
Abstract:
Based on the daily precipitation data at 110 observational stations during 1961-2008 in South China， the climatic characteristics and variation of torrential rain days， rainstorm intensity and contribution which is in annual， the first and second flood seasons in South China were studied by using statistical and diagnostic methods， such as linear regression analysis， Mann Kendall test， wavelet analysis and the computation of trend coefficients. The results have shown that the annual mean torrential rain days have a decreasing trend from coastal regions to inland in South China in recent 48 years， the highest center is in Dongxing of Guangxi （14.9 d）， and the lowest center is in Longlin of Guangxi （3.2 d）. About 72% of the total torrential rain days occurred in the flood seasons with about 45% in the first season and 27% in the second season. The mean torrential rain days have increased faintly in annual， the first and second flood seasons in South China， but it is not obvious. There are the characteristics of interannual and interdecadal changes. The mean rainstorm intensity has increased faintly in annual and in the first flood season in South China. However, since 2005 it has become obviously. The mean rainstorm intensity has declined in the second flood season， but it is not obvious. The annual mean rainstorm contribution to the total rainfall has increased obviously， but the mean contribution is not obvious in the first and second flood seasons. The wavelet analysis has shown that the changes of torrential rain days， intensity and contribution which is in annual， the first and second flood seasons in South China have two significant periods of 2-3 a and 3-4 a.
Based on the daily precipitation data at 110 observational stations during 1961-2008 in South China， the climatic characteristics and variation of torrential rain days， rainstorm intensity and contribution which is in annual， the first and second flood seasons in South China were studied by using statistical and diagnostic methods， such as linear regression analysis， Mann Kendall test， wavelet analysis and the computation of trend coefficients. The results have shown that the annual mean torrential rain days have a decreasing trend from coastal regions to inland in South China in recent 48 years， the highest center is in Dongxing of Guangxi （14.9 d）， and the lowest center is in Longlin of Guangxi （3.2 d）. About 72% of the total torrential rain days occurred in the flood seasons with about 45% in the first season and 27% in the second season. The mean torrential rain days have increased faintly in annual， the first and second flood seasons in South China， but it is not obvious. There are the characteristics of interannual and interdecadal changes. The mean rainstorm intensity has increased faintly in annual and in the first flood season in South China. However, since 2005 it has become obviously. The mean rainstorm intensity has declined in the second flood season， but it is not obvious. The annual mean rainstorm contribution to the total rainfall has increased obviously， but the mean contribution is not obvious in the first and second flood seasons. The wavelet analysis has shown that the changes of torrential rain days， intensity and contribution which is in annual， the first and second flood seasons in South China have two significant periods of 2-3 a and 3-4 a.
2014,40(7):816-826, DOI: 10.7519/j.issn.1000-0526.2014.07.005
Abstract:
In term of precipitation data of 2400 stations from 1981 to 2010, annual, seasonal and monthly distribution and evolution characteristics of rainstorm were analyzed. The results show that the processes of rainstorm have been increased evidently since 21 century especially in the south of China, but the duration is relatively short. Rainstorm days have been increased, but the amount of precipitation is not as much as in 1990s. Variation trend of the annual (monthly) precipitation amount is in accordance with that of rainstorm days, but rainfall is averagely more while the rainstorm days are less during spring rainfall phase over the south of Yangtze River. Distribution of the maximum annual rainstorm days is very similar with that of the annual mean rainstorm days, revealing the feature of more in south and east but less in north and west. Maximum annual rainstorm days are more than double of annual average rainstorm days with multi centers due to the effect of topography. The months of maximum monthly rainstorm days over different regions of the same province are incompletely same as the result of the impact of different weather systems. Generally, rainstorm days have been increased since 2000, rainstorm begins earlier, ends latter and lasts longer than before. Nowadays, as the extreme rainfall events and secondary disasters happen frequently, it is conducive for the forecast of quantitative precipitation forecast (QPF) to learn the spatio temporal distribution and evolution features of rainstorm.
In term of precipitation data of 2400 stations from 1981 to 2010, annual, seasonal and monthly distribution and evolution characteristics of rainstorm were analyzed. The results show that the processes of rainstorm have been increased evidently since 21 century especially in the south of China, but the duration is relatively short. Rainstorm days have been increased, but the amount of precipitation is not as much as in 1990s. Variation trend of the annual (monthly) precipitation amount is in accordance with that of rainstorm days, but rainfall is averagely more while the rainstorm days are less during spring rainfall phase over the south of Yangtze River. Distribution of the maximum annual rainstorm days is very similar with that of the annual mean rainstorm days, revealing the feature of more in south and east but less in north and west. Maximum annual rainstorm days are more than double of annual average rainstorm days with multi centers due to the effect of topography. The months of maximum monthly rainstorm days over different regions of the same province are incompletely same as the result of the impact of different weather systems. Generally, rainstorm days have been increased since 2000, rainstorm begins earlier, ends latter and lasts longer than before. Nowadays, as the extreme rainfall events and secondary disasters happen frequently, it is conducive for the forecast of quantitative precipitation forecast (QPF) to learn the spatio temporal distribution and evolution features of rainstorm.
2014,40(4):389-399, DOI: 10.7519/j.issn.1000-0526.2014.04.001
Abstract:
Thunderstorm potential forecasting based on three ingredients has been widely accepted. This article aims to discuss some basical questions in operational forecast applications, and clarify some easily confused concepts. The content includes atmospheric instablility and convection, thunderstorms trigger mechanism and lifting and its relationship with snoptical weather system, how to deal with the three elements of the thunderstorm “enough”, the combination of pattern recognition and ingredients based forecasting methodology. Atmospheric instablility is one of the three ingredients of convection initiation, and it is also very important to thunderstorm short time forecasting and analysis. This paper discusses various mesoscale instability related to the thunderstorm, and inicates how to estimate the spatial and temporal evolution of CAPE. In addition, the definition and criterion for potential instability and symmetric instability are discussed profoundly.
Thunderstorm potential forecasting based on three ingredients has been widely accepted. This article aims to discuss some basical questions in operational forecast applications, and clarify some easily confused concepts. The content includes atmospheric instablility and convection, thunderstorms trigger mechanism and lifting and its relationship with snoptical weather system, how to deal with the three elements of the thunderstorm “enough”, the combination of pattern recognition and ingredients based forecasting methodology. Atmospheric instablility is one of the three ingredients of convection initiation, and it is also very important to thunderstorm short time forecasting and analysis. This paper discusses various mesoscale instability related to the thunderstorm, and inicates how to estimate the spatial and temporal evolution of CAPE. In addition, the definition and criterion for potential instability and symmetric instability are discussed profoundly.
2011,37(5):599-606, DOI: 10.7519/j.issn.1000-0526.2011.5.012
Abstract:
Using the diurnal snow data of 120 meteorological stations in Yunnan Province during 1961-2008, the temporal and spatial distribution characteristics and the trend of climatic change of the annual and monthly snow fall are analyzed. It is pointed out that the total trend of snow frequency and covering stations has been decreasing in Yunnan in the recent 50 years. And the annual snow frequency has declined at a mean rate of 4.5 times per year. The temporal trends of monthly snow frequency and covering stations are all negative. Moreover the reduction of snow frequency in December is the largest in magnitude, therefore, it is the most remarkable. And the reduction of snow stations in April is the largest. As far as the spatial change of the secular trend variation of annual snow frequency is concerned, the reduction of annual snow frequency is larger in Northwest Yunnan than in its northeast and east, where the reduction rate is 0.44 times per year. And the temporal changes of annual snowfall and depth of snow cover are studied, the results show that the secular trends of annual snowfall and the maximum depth of snow cover are all positive. This means that in the nearly 50 years the heavy snow frequency has increased over Yunnan Province.
Using the diurnal snow data of 120 meteorological stations in Yunnan Province during 1961-2008, the temporal and spatial distribution characteristics and the trend of climatic change of the annual and monthly snow fall are analyzed. It is pointed out that the total trend of snow frequency and covering stations has been decreasing in Yunnan in the recent 50 years. And the annual snow frequency has declined at a mean rate of 4.5 times per year. The temporal trends of monthly snow frequency and covering stations are all negative. Moreover the reduction of snow frequency in December is the largest in magnitude, therefore, it is the most remarkable. And the reduction of snow stations in April is the largest. As far as the spatial change of the secular trend variation of annual snow frequency is concerned, the reduction of annual snow frequency is larger in Northwest Yunnan than in its northeast and east, where the reduction rate is 0.44 times per year. And the temporal changes of annual snowfall and depth of snow cover are studied, the results show that the secular trends of annual snowfall and the maximum depth of snow cover are all positive. This means that in the nearly 50 years the heavy snow frequency has increased over Yunnan Province.
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ISSN:1000-0526 CN:11-2282/P