ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 45,Issue 8,2019 Table of Contents
2019, 45(8):1037-1051.
DOI: 10.7519/j.issn.1000-0526.2019.08.001
Abstract:
Based on surface observation and sounding data from 2001 to 2013, the spatial and temporal distribution of snowfall occurring at surface air temperature of 0-2℃ (hereinafter referred to as critical surface temperature condition) in China is analyzed, and comparative analysis of vertical thermal characteristics is made between snow and rain under the above condition, then a decision tree discriminant method is introduced to discriminate snow from rain. The results show that the frequency of snow under the critical surface air temperature conditions is generally higher than that of rain and sleet, and it mainly distributes in the central and eastern regions between southern North China and northern Jiangnan Area, with an average annual number of 7.69-15.38 stations. Combined soundings of snow and rain show maximum temperature difference around 650 hPa, more obvious when T2 m (surface air temperature) is lower. Maximum humidity difference lies around the surface, more obvious when T2 m is higher. A melting layer above the surface exists more frequently in rain than in snow. The melting layer of rain is mainly located in the middle layer, while that of snow is mainly near 1000 hPa. Discriminative accuracies of different decision tree discriminant models constructed from different factors vary differently. T2 m is especially important, and wetbulb temperature can improve the discriminative accuracy in the process of discrimination. The accuracy of the decision tree discriminant model constructed from cloud top temperature, middlelevel melting parameter and lowlevel wetbulb temperature is the highest among all models, with a discriminant accuracy rate of 91.86%.
Based on surface observation and sounding data from 2001 to 2013, the spatial and temporal distribution of snowfall occurring at surface air temperature of 0-2℃ (hereinafter referred to as critical surface temperature condition) in China is analyzed, and comparative analysis of vertical thermal characteristics is made between snow and rain under the above condition, then a decision tree discriminant method is introduced to discriminate snow from rain. The results show that the frequency of snow under the critical surface air temperature conditions is generally higher than that of rain and sleet, and it mainly distributes in the central and eastern regions between southern North China and northern Jiangnan Area, with an average annual number of 7.69-15.38 stations. Combined soundings of snow and rain show maximum temperature difference around 650 hPa, more obvious when T2 m (surface air temperature) is lower. Maximum humidity difference lies around the surface, more obvious when T2 m is higher. A melting layer above the surface exists more frequently in rain than in snow. The melting layer of rain is mainly located in the middle layer, while that of snow is mainly near 1000 hPa. Discriminative accuracies of different decision tree discriminant models constructed from different factors vary differently. T2 m is especially important, and wetbulb temperature can improve the discriminative accuracy in the process of discrimination. The accuracy of the decision tree discriminant model constructed from cloud top temperature, middlelevel melting parameter and lowlevel wetbulb temperature is the highest among all models, with a discriminant accuracy rate of 91.86%.
2019, 45(8):1052-1064.
DOI: 10.7519/j.issn.1000-0526.2019.08.002
Abstract:
An urban flooding was caused by heavy rainfall in Wuhan on 6 July 2016. Based on Doppler weather radar of Wuhan and surface automatic station observation, and EC 0.25°×0.25° fine-grid model data, the charactersitics of heavy rainfall, the evolution features of mesoscale convective system (MCS), the environmental condition and radar echo structure of Meiyu front are studied in this paper. The result shows that (1) the heavy rainfall event occurred under the circulation pattern of typical Meiyu period. The high temperature and high humidity areas on the northwest side of the subtropical anticyclone were stable with the Jianghuai shear line, and the heavy rainfall appeared in the convergence zone of the southwest low-level jet. (2) The train line was mainly composed of the mesoscale system near the Jianghuai shear line or boundary convergence line. The mesoscale cyclonic convergence and low-level southwest jet maintained a long time, which is the main reason for the formation of the “train effect”. (3) Heavy rainfall was a typical MCS, which moved along the southwest-northeast direction, and the special topography of Hubei reinforced the “train effect”. (4) The MCS has three distinct characteristics in radar echo. The first one is MCS in the radar echo pattern belongs to the band composed of stratiform and convective rain train line, consistent with the trend of the southwest airflow. The second is MCS moved in the direction of stratiform cloud and train lines were almost the same. MCS’s direction was parallel to the train line, and the component perpendicular to the train line is quite small. The third is the convective cells were newly born and strengthened in the upstream on the train line, moving downstream. The convective propagation direction and train line were in the opposite direction. (5) The southwest jet near the ground and bulls eyes intensified the precipitation.
An urban flooding was caused by heavy rainfall in Wuhan on 6 July 2016. Based on Doppler weather radar of Wuhan and surface automatic station observation, and EC 0.25°×0.25° fine-grid model data, the charactersitics of heavy rainfall, the evolution features of mesoscale convective system (MCS), the environmental condition and radar echo structure of Meiyu front are studied in this paper. The result shows that (1) the heavy rainfall event occurred under the circulation pattern of typical Meiyu period. The high temperature and high humidity areas on the northwest side of the subtropical anticyclone were stable with the Jianghuai shear line, and the heavy rainfall appeared in the convergence zone of the southwest low-level jet. (2) The train line was mainly composed of the mesoscale system near the Jianghuai shear line or boundary convergence line. The mesoscale cyclonic convergence and low-level southwest jet maintained a long time, which is the main reason for the formation of the “train effect”. (3) Heavy rainfall was a typical MCS, which moved along the southwest-northeast direction, and the special topography of Hubei reinforced the “train effect”. (4) The MCS has three distinct characteristics in radar echo. The first one is MCS in the radar echo pattern belongs to the band composed of stratiform and convective rain train line, consistent with the trend of the southwest airflow. The second is MCS moved in the direction of stratiform cloud and train lines were almost the same. MCS’s direction was parallel to the train line, and the component perpendicular to the train line is quite small. The third is the convective cells were newly born and strengthened in the upstream on the train line, moving downstream. The convective propagation direction and train line were in the opposite direction. (5) The southwest jet near the ground and bulls eyes intensified the precipitation.
2019, 45(8):1065-1074.
DOI: 10.7519/j.issn.1000-0526.2019.08.003
Abstract:
Standard precipitation verification method, extreme dependency index and method for object-based diagnostic evaluation (MODE) are applied in this paper to make evaluation of SMS-WARMS V2.0 precipitation in Southwest China from December 2015 to November 2016. The results show that (1) the treat scores of four seasons in Southwest are high, especially in spring and summer, and the performance is relatively stable within 48 h. (2) The results of frequency bias and true skill score show each magnitude precipitation in spring and summer forecasted by SMS-WARMS V2.0 in Southwest China is more than observation, but the model forecast to torrential rain in autumn and heavy rain in winter is relatively less. Overall, the forecast skill in Southwest China exhibits the features that the POD is higher than FAR. (3) The treat scores of light rain, torrential rain and downpour forecasted by SMS-WARMS V2.0 are higher than ECMWF model. (4) Model has a good performance in forecasting extreme precipitation in Southwest through extreme dependency index, especially better for central and northeastern Sichuan and southwestern Guizhou. (5) Precipitation area forecast of a rainstorm process caused by a southwest vortex in August 2015 performed well in space, but the intensity was stronger than observation. (6) Statistic results made by MODE show that the rainstorm object centroid has a small bias between forecast and observation, but the central intensity of precipitation is stronger than observation.
Standard precipitation verification method, extreme dependency index and method for object-based diagnostic evaluation (MODE) are applied in this paper to make evaluation of SMS-WARMS V2.0 precipitation in Southwest China from December 2015 to November 2016. The results show that (1) the treat scores of four seasons in Southwest are high, especially in spring and summer, and the performance is relatively stable within 48 h. (2) The results of frequency bias and true skill score show each magnitude precipitation in spring and summer forecasted by SMS-WARMS V2.0 in Southwest China is more than observation, but the model forecast to torrential rain in autumn and heavy rain in winter is relatively less. Overall, the forecast skill in Southwest China exhibits the features that the POD is higher than FAR. (3) The treat scores of light rain, torrential rain and downpour forecasted by SMS-WARMS V2.0 are higher than ECMWF model. (4) Model has a good performance in forecasting extreme precipitation in Southwest through extreme dependency index, especially better for central and northeastern Sichuan and southwestern Guizhou. (5) Precipitation area forecast of a rainstorm process caused by a southwest vortex in August 2015 performed well in space, but the intensity was stronger than observation. (6) Statistic results made by MODE show that the rainstorm object centroid has a small bias between forecast and observation, but the central intensity of precipitation is stronger than observation.
2019, 45(8):1075-1084.
DOI: 10.7519/j.issn.1000-0526.2019.08.004
Abstract:
Using the data of lighting locator, densely-obtained automatic station data and conventional data, 35 “thundersnow” events that occurred in Shandong Province from 2006 to 2015 are analyzed. The “thundersnow” can be divided into warm advection type and marine effect type according to the formation mechanism, and the characteristics in related element fields and physical quantity fields for the two kinds of events are summarized in detail. The main conclusions are as follows. Within 24 h before warm advection “thunderstorm” events, the temperature in the middle and lower troposphere is warming up, and the closer it is to the ground, the more obvious the temperature rise is. The events tend to occur when there is a sudden invasion of strong cold air from 850 hPa to the ground, the temperature difference between the upper and lower layers can reach 10 ℃, and the circulation situation is adjusted from uniform southward airflow to cold cushion in lower layer and the warm advection in the mid-upper layers. The center of ascending motion and the unstable stratification appear in the mid-upper layers. Two days before the marine effect “thunderstorm” events, the Bohai Sea is controlled by warm ridges, and the sea surface temperature is about 2 ℃ higher than usual. When the northward current behind the upper trough suddenly increases and sweeps across the Bohai Sea, the “thundersnow” events occur. Although convective activity also occurs in the lower troposphere, the thickness of unstable stratification and the temperature difference between upper and lower layers are larger than that in marine effect snowstorm in general.
Using the data of lighting locator, densely-obtained automatic station data and conventional data, 35 “thundersnow” events that occurred in Shandong Province from 2006 to 2015 are analyzed. The “thundersnow” can be divided into warm advection type and marine effect type according to the formation mechanism, and the characteristics in related element fields and physical quantity fields for the two kinds of events are summarized in detail. The main conclusions are as follows. Within 24 h before warm advection “thunderstorm” events, the temperature in the middle and lower troposphere is warming up, and the closer it is to the ground, the more obvious the temperature rise is. The events tend to occur when there is a sudden invasion of strong cold air from 850 hPa to the ground, the temperature difference between the upper and lower layers can reach 10 ℃, and the circulation situation is adjusted from uniform southward airflow to cold cushion in lower layer and the warm advection in the mid-upper layers. The center of ascending motion and the unstable stratification appear in the mid-upper layers. Two days before the marine effect “thunderstorm” events, the Bohai Sea is controlled by warm ridges, and the sea surface temperature is about 2 ℃ higher than usual. When the northward current behind the upper trough suddenly increases and sweeps across the Bohai Sea, the “thundersnow” events occur. Although convective activity also occurs in the lower troposphere, the thickness of unstable stratification and the temperature difference between upper and lower layers are larger than that in marine effect snowstorm in general.
2019, 45(8):1085-1092.
DOI: 10.7519/j.issn.1000-0526.2019.08.005
Abstract:
Model-based numerical prediction is often affected by bias when compared to local observations. In this study, the European Center for Medium-Range Weather Forecasting (ECMWF) data were used to generate the analog ensemble (AnEn) prediction over the 15 national weather stations and 274 automatic stations of Beijing, with a focus on correcting ECMWF prediction of the daily maximum and minimum temperatures, 1-7 day ahead, twice a day. The analog of a forecast for a given location and time is defined as the observation that corresponds to a past prediction matching selected features of the current forecast. The best analogs form AnEn, which produces accurate predictions and a reliable quantification of their uncertainty with similar or superior skill compared to traditional ensemble methods while requiring considerably less real-time computational resources. An analysis of the performance of ECMWF and AnEn in space and time was presented. The results demonstrate that a short training period of 60 days may be a good compromise for the computational efficiency and the quality of deterministic predictions. Extending the training periods would further increase the prediction quality than optimizing the environmental parameters, no matter 1-month, 3-month or 6-month optimizations. AnEn correction results are better than the predictions generated by the forecasters, particularly for daily minimum temperatures. AnEn effectively reduces the bias of ECMWF predictions, resulting in a skilled downscaled prediction at the observation location, consistently over time and space. However, AnEn is not very effective in improving predictions of haze, precipitation, and strong winds, which may require a much longer training data set. Furthermore, this study tests the results over time and space to make sure the method’s reliability for the future smart grid forecast operation.
Model-based numerical prediction is often affected by bias when compared to local observations. In this study, the European Center for Medium-Range Weather Forecasting (ECMWF) data were used to generate the analog ensemble (AnEn) prediction over the 15 national weather stations and 274 automatic stations of Beijing, with a focus on correcting ECMWF prediction of the daily maximum and minimum temperatures, 1-7 day ahead, twice a day. The analog of a forecast for a given location and time is defined as the observation that corresponds to a past prediction matching selected features of the current forecast. The best analogs form AnEn, which produces accurate predictions and a reliable quantification of their uncertainty with similar or superior skill compared to traditional ensemble methods while requiring considerably less real-time computational resources. An analysis of the performance of ECMWF and AnEn in space and time was presented. The results demonstrate that a short training period of 60 days may be a good compromise for the computational efficiency and the quality of deterministic predictions. Extending the training periods would further increase the prediction quality than optimizing the environmental parameters, no matter 1-month, 3-month or 6-month optimizations. AnEn correction results are better than the predictions generated by the forecasters, particularly for daily minimum temperatures. AnEn effectively reduces the bias of ECMWF predictions, resulting in a skilled downscaled prediction at the observation location, consistently over time and space. However, AnEn is not very effective in improving predictions of haze, precipitation, and strong winds, which may require a much longer training data set. Furthermore, this study tests the results over time and space to make sure the method’s reliability for the future smart grid forecast operation.
6 Micro-Meteorological Characteristics Analysis of Two Snowfall Processes in Gande of Qinghai Province
2019, 45(8):1093-1103.
DOI: 10.7519/j.issn.1000-0526.2019.08.006
Abstract:
Using observed micro-meteorological data of two snowfall processes in Gande of Qinghai Province, the snow depth, snow density, ice content in snow, water content in snow and snow surface temperature are discussed, and the relationships between surface albedo and snow density, ice content in snow, water content in snow are analyzed. Besides, the influence of accumulated snow on air temperature gradient, relative humidity gradient and wind speed gradient of snow cover are also analyzed. The results show that surface albedo increases obviously while ground is covered by snow. Albedo can be 0.8-0.9 at noon after snowfall. Albedo reduces along with snow melting. Snow albedo is positively related with snow density and ice content in snow and negatively related with water content in snow. Snow cover reduces absolute value of air temperature gradient. The absolute value of relative humidity gradient gets lower at dawn and higher at noon. Snow cover has no effect on wind speed gradient.
Using observed micro-meteorological data of two snowfall processes in Gande of Qinghai Province, the snow depth, snow density, ice content in snow, water content in snow and snow surface temperature are discussed, and the relationships between surface albedo and snow density, ice content in snow, water content in snow are analyzed. Besides, the influence of accumulated snow on air temperature gradient, relative humidity gradient and wind speed gradient of snow cover are also analyzed. The results show that surface albedo increases obviously while ground is covered by snow. Albedo can be 0.8-0.9 at noon after snowfall. Albedo reduces along with snow melting. Snow albedo is positively related with snow density and ice content in snow and negatively related with water content in snow. Snow cover reduces absolute value of air temperature gradient. The absolute value of relative humidity gradient gets lower at dawn and higher at noon. Snow cover has no effect on wind speed gradient.
2019, 45(8):1104-1112.
DOI: 10.7519/j.issn.1000-0526.2019.08.007
Abstract:
Based on the precipitation observations from 723 basic meteorological stations in China and the NCEP reanalysis data, the possible causes of the 2017 autumn rainfall anomalies in West China were investigated by detailed investigations about the impacts of sub-seasonal to seasonal anomaly of atmospheric circulation, interannual anomaly of external forcing from ocean together with long-term variations of precipitation. The results show that quasi-period variations with multiple timescales, including 3-4 a, 6-9 a, 12-18 a and 36 a since 1960s, along with an increasing long-term trend since 1990 found in the autumn rainfall in Western China. The abnormal heavy rainfall in West China during autumn of 2017 resulted from the superposition influences from multi-time scale variations. In the autumn of 2017, the position of polar vortex in the Northern Hemisphere lay towards East Asia, allowing the cold air from the low trough near Lake Baikal to splitting southward. Meanwhile, the West Pacific subtropical high was excessively stronger and westward. Therefore, a stronger water vapor convergence area was formed and eventually led to the abnormal heavy rainfall in West China. On sub-seasonal time scales, the East Asian summer monsoon retreated more slowly than normal, and the northern boundary position of the summer monsoon was continuously maintained northward than normal. The main rain band was correspondingly maintained around the region of West China, Jianghuai and Hanjiang in September and October. The sub-seasonal variations of the northward water vapor transportation from the West Pacific Ocean through the South China Sea, together with the sub-seasonal activities of northeastern cold vortex, may be sub-seasonal circulation factors which influence the autumn rainfall anomaly in West China. In addition, the interannual anomaly of autumn rainfall in West China and central-eastern equatorial Pacific SST shows a remarkable negative correlation. The La Ni〖AKn~D〗a condition which developed from the late summer and early autumn in 2017 acts as the important interannual forcing of autumn rainfall anomalies. Also, the abnormal heavy rainfall in West China is related to positive phases of decadal to multi-decadal variability and long-term increasing trend in recent years.
Based on the precipitation observations from 723 basic meteorological stations in China and the NCEP reanalysis data, the possible causes of the 2017 autumn rainfall anomalies in West China were investigated by detailed investigations about the impacts of sub-seasonal to seasonal anomaly of atmospheric circulation, interannual anomaly of external forcing from ocean together with long-term variations of precipitation. The results show that quasi-period variations with multiple timescales, including 3-4 a, 6-9 a, 12-18 a and 36 a since 1960s, along with an increasing long-term trend since 1990 found in the autumn rainfall in Western China. The abnormal heavy rainfall in West China during autumn of 2017 resulted from the superposition influences from multi-time scale variations. In the autumn of 2017, the position of polar vortex in the Northern Hemisphere lay towards East Asia, allowing the cold air from the low trough near Lake Baikal to splitting southward. Meanwhile, the West Pacific subtropical high was excessively stronger and westward. Therefore, a stronger water vapor convergence area was formed and eventually led to the abnormal heavy rainfall in West China. On sub-seasonal time scales, the East Asian summer monsoon retreated more slowly than normal, and the northern boundary position of the summer monsoon was continuously maintained northward than normal. The main rain band was correspondingly maintained around the region of West China, Jianghuai and Hanjiang in September and October. The sub-seasonal variations of the northward water vapor transportation from the West Pacific Ocean through the South China Sea, together with the sub-seasonal activities of northeastern cold vortex, may be sub-seasonal circulation factors which influence the autumn rainfall anomaly in West China. In addition, the interannual anomaly of autumn rainfall in West China and central-eastern equatorial Pacific SST shows a remarkable negative correlation. The La Ni〖AKn~D〗a condition which developed from the late summer and early autumn in 2017 acts as the important interannual forcing of autumn rainfall anomalies. Also, the abnormal heavy rainfall in West China is related to positive phases of decadal to multi-decadal variability and long-term increasing trend in recent years.
2019, 45(8):1113-1122.
DOI: 10.7519/j.issn.1000-0526.2019.08.008
Abstract:
Using the WRF/Chem zero-emission scenario simulation scheme, the simulated PM2.5 concentration in Hubei Province from 2 December 2015 to 31 January 2016 was separated into regional transmission component and local accumulation component. Based on the statistical analysis of numerical simulation results, the transmission channel of pollutants and the transmission contribution rate in Hubei Province as well as the influence of weather systems in key areas on different pollution components were studied. It was found that the heavy pollution process is dominated by the northerly and the easterly winds, showing the obviously regional transport characteristics. There are two main channels for pollutant transmission. The first is from Nanyang Basin in Henan Province to Xiangyang and into Jianghan Plain in Hubei Province, and the second is from Xinyang in Henan Province to Suizhou, Xiaogan and Wuhan, and then into the east of Jianghan Plain. The potential pollution source of the long-distance regional transmission lies in Henan, Anhui, Jiangsu, Shandong Provinces etc. In the process of heavy pollution, the contribution rate of external sources is as high as 66% on average for all cities, and the contribution rate is over 75% for the cleaner cities. The regional transport component shows, that in southeast China, which is the main sensitive region, the correlation of pressure (temperature) change and PM2.5 conveying is significantly negative (positive), having a good effect in maintaining the two vector belts of south and north associated with wind field (PM2.5), and promoting the south and east airflow. In addition, the Iranian Plateau weather system has a certain influence on the atmospheric circulation in East Asia through the upstream and downstream effects, which indirectly affects the regional pollution transportation. For the local accumulation component, the winter monsoon circulation system acts as the main weather system. Under the weak winter monsoon circulation, Mongolian high pressure system is weak and the western Pacific sea level pressure is higher, making the pollution contribution of local accumulation component higher.
Using the WRF/Chem zero-emission scenario simulation scheme, the simulated PM2.5 concentration in Hubei Province from 2 December 2015 to 31 January 2016 was separated into regional transmission component and local accumulation component. Based on the statistical analysis of numerical simulation results, the transmission channel of pollutants and the transmission contribution rate in Hubei Province as well as the influence of weather systems in key areas on different pollution components were studied. It was found that the heavy pollution process is dominated by the northerly and the easterly winds, showing the obviously regional transport characteristics. There are two main channels for pollutant transmission. The first is from Nanyang Basin in Henan Province to Xiangyang and into Jianghan Plain in Hubei Province, and the second is from Xinyang in Henan Province to Suizhou, Xiaogan and Wuhan, and then into the east of Jianghan Plain. The potential pollution source of the long-distance regional transmission lies in Henan, Anhui, Jiangsu, Shandong Provinces etc. In the process of heavy pollution, the contribution rate of external sources is as high as 66% on average for all cities, and the contribution rate is over 75% for the cleaner cities. The regional transport component shows, that in southeast China, which is the main sensitive region, the correlation of pressure (temperature) change and PM2.5 conveying is significantly negative (positive), having a good effect in maintaining the two vector belts of south and north associated with wind field (PM2.5), and promoting the south and east airflow. In addition, the Iranian Plateau weather system has a certain influence on the atmospheric circulation in East Asia through the upstream and downstream effects, which indirectly affects the regional pollution transportation. For the local accumulation component, the winter monsoon circulation system acts as the main weather system. Under the weak winter monsoon circulation, Mongolian high pressure system is weak and the western Pacific sea level pressure is higher, making the pollution contribution of local accumulation component higher.
LEI Zhengcui
,
ZHENG Yuanyuan
,
LIU Yinfeng
,
SUN Kangyuan
,
LIU Duanyang
,
HE Tao
,
WU Jinglu
,
ZHOU Wenjun
2019, 45(8):1123-1134.
DOI: 10.7519/j.issn.1000-0526.2019.08.009
Abstract:
Using conventional meteorological observation data, sounding data, pollutant concentration and AQI data, NCEP reanalysis data, the causes of a severe persistent fog-haze weather in Changzhou from November 24 to December 3, 2018 were analyzed. The results show that this fog-haze process lasted a long time with wide scope, large density and heavy pollution. The upper latitudinal circulation was dominant in the upper latitudes during the fog-haze period, and the warm ridges in the middle and lower layers were stable. The surface was continuously affected by the uniform pressure field or the top of weak inverted trough or the front of weak cold front, which provided a favorable circulation background for the continuous occurrence and development of fog-haze. The weak divergence, negative vorticity and weak downdraft in the boundary layer were the dynamic factors for the development of fog-haze weather. Long-time moisture saturation and low wind speed were beneficial to the occurrence and development of fog and haze. The average mixing layer height of fog was obviously lower than that of haze. The higher the haze level, the lower the height of the mixed layer. The change of mixing layer height was prior to the change of visibility, which was a guidance for the early warning of the fog-haze. The infiltration of weak cold air, proper increase of wind speed, rapid decline of mixing layer height and significant increase in the absolute value of negative net radiation exposure were the causes for the explosion of fog.
Using conventional meteorological observation data, sounding data, pollutant concentration and AQI data, NCEP reanalysis data, the causes of a severe persistent fog-haze weather in Changzhou from November 24 to December 3, 2018 were analyzed. The results show that this fog-haze process lasted a long time with wide scope, large density and heavy pollution. The upper latitudinal circulation was dominant in the upper latitudes during the fog-haze period, and the warm ridges in the middle and lower layers were stable. The surface was continuously affected by the uniform pressure field or the top of weak inverted trough or the front of weak cold front, which provided a favorable circulation background for the continuous occurrence and development of fog-haze. The weak divergence, negative vorticity and weak downdraft in the boundary layer were the dynamic factors for the development of fog-haze weather. Long-time moisture saturation and low wind speed were beneficial to the occurrence and development of fog and haze. The average mixing layer height of fog was obviously lower than that of haze. The higher the haze level, the lower the height of the mixed layer. The change of mixing layer height was prior to the change of visibility, which was a guidance for the early warning of the fog-haze. The infiltration of weak cold air, proper increase of wind speed, rapid decline of mixing layer height and significant increase in the absolute value of negative net radiation exposure were the causes for the explosion of fog.
2019, 45(8):1135-1148.
DOI: 10.7519/j.issn.1000-0526.2019.08.010
Abstract:
The severe convective weather in Zhoukou City on 6 July 2017 caused by a tornado was investigated and a general analysis of the circumstance and early warning practicability of tornado was made by using the high-level, surface and AWS data as well as the Doppler weather radar and FY-2G satellite data. The results show that the tornado disaster mainly affected the area with length of 4.5-5 km and width of 100-150 m between Xihua County and Huaiyang County of Henan Province, having considerable meso-γ scale vortex characteristics of the tornado with strength to Grade EF1 and Grade EF2 when strongest. (2) The tornado process was jointly influenced by the mid-latitude trough moving eastward and the warm-moist southwest airflow in the edge of subtropical high. The configuration of upper-level stream divergence and low-level jet offered heavy rain and tornado a favorable synoptically dynamic condition. The tornado was induced by the cyclonic convergent airflows on the convergence line which was between the severe rain cold outflow and the warm-moist airflow in the eastern part. Near the positive vortex center on the big va-lue of surface temperature, dew-point temperature and energy gradient may be where tornado could occur. (3) The Fuyang sounding data at 08:00 BT showed a strong conditional instable air where CAPE was 1712 J·kg-1 (3182 J·kg-1 corrected with surface temperature and dew point temperature at 14:00 BT), K index was 42℃, SWEAT index was 312, SI index was -4.5℃ and the PW was around 65 mm. The LCL was at a very low height of 959.2 hPa, wind vector difference of low-level vertical wind shear at 0-1 km was 10 m·s-1 or above, which offers a profitable circumstance conditions for the tornado. (4) On satellite images, the tornado occurred in the front of warm cloud bands whose TBB was under -72℃ where convective clouds developed vigorously. Lightning monitoring result showed the tornado was on the east side of the dense lightning flashes area. (5) On radar echo maps, the tornado occurred at the massive echo area on the front of northeast-southwest heavy rain echo banks. The occurrence of mesocyclone and its tornado features could give a reliable clue to the warning of tornado in the real-time operation. The enhancing of rotating speed and falling down of the height indicate the tornado would come to the ground surface. In a word, the results above could act as references for tornado monitoring and warning over the Huanghuai Plain.
The severe convective weather in Zhoukou City on 6 July 2017 caused by a tornado was investigated and a general analysis of the circumstance and early warning practicability of tornado was made by using the high-level, surface and AWS data as well as the Doppler weather radar and FY-2G satellite data. The results show that the tornado disaster mainly affected the area with length of 4.5-5 km and width of 100-150 m between Xihua County and Huaiyang County of Henan Province, having considerable meso-γ scale vortex characteristics of the tornado with strength to Grade EF1 and Grade EF2 when strongest. (2) The tornado process was jointly influenced by the mid-latitude trough moving eastward and the warm-moist southwest airflow in the edge of subtropical high. The configuration of upper-level stream divergence and low-level jet offered heavy rain and tornado a favorable synoptically dynamic condition. The tornado was induced by the cyclonic convergent airflows on the convergence line which was between the severe rain cold outflow and the warm-moist airflow in the eastern part. Near the positive vortex center on the big va-lue of surface temperature, dew-point temperature and energy gradient may be where tornado could occur. (3) The Fuyang sounding data at 08:00 BT showed a strong conditional instable air where CAPE was 1712 J·kg-1 (3182 J·kg-1 corrected with surface temperature and dew point temperature at 14:00 BT), K index was 42℃, SWEAT index was 312, SI index was -4.5℃ and the PW was around 65 mm. The LCL was at a very low height of 959.2 hPa, wind vector difference of low-level vertical wind shear at 0-1 km was 10 m·s-1 or above, which offers a profitable circumstance conditions for the tornado. (4) On satellite images, the tornado occurred in the front of warm cloud bands whose TBB was under -72℃ where convective clouds developed vigorously. Lightning monitoring result showed the tornado was on the east side of the dense lightning flashes area. (5) On radar echo maps, the tornado occurred at the massive echo area on the front of northeast-southwest heavy rain echo banks. The occurrence of mesocyclone and its tornado features could give a reliable clue to the warning of tornado in the real-time operation. The enhancing of rotating speed and falling down of the height indicate the tornado would come to the ground surface. In a word, the results above could act as references for tornado monitoring and warning over the Huanghuai Plain.
2019, 45(8):1149-1157.
DOI: 10.7519/j.issn.1000-0526.2019.08.011
Abstract:
To alleviate the crisis of urban thermal environment of Nanjing, the Weather Research and Forecasting Model (WRF) was uesd to simulate the effects of three types of roofs (conventional roof, high albedo roof and randomized glass-polymer hybrid metamaterial roof) during the extreme high temperature weather in Nanjing in 1-31 July 2017. The results showed that (1) cooling roofs (like high albedo roof and randomized glass-polymer hybrid metamaterial roof) can reduce the temperature of cities by weakening the solar radiation reaching the surface of the city. During the daytime, the average temperature of randomized glass-polymer hybrid metamaterial roof drops by 0.8-1.2℃, and the average temperature decreases 0.2-0.4℃ in the nighttime. The average temperature of the high albedol roof drops by 0.6-0.8℃ during the day and decreases 0.2℃ at night. (2) The surface temperature index can be used to characterize the thermal performance of the cooling roof. The surface temperature index of the randomized glass-polymer hybrid metamaterial roof is 0.16-0.43. The surface temperature index of the high albedo roof is 0.05-0.26, indicating that the cooling effect of the randomized glass-polymer hybrid metamaterial roof is stronger than the high albedo roof. (3) The high albedo roof and the randomized glass-polymer hybrid metamaterial roof can return 36.7% and 47.1% of the solar short-wave radiation respectively. The atmosphere absorbs heat 19.6% less and 34.8% less than conventional roof.
To alleviate the crisis of urban thermal environment of Nanjing, the Weather Research and Forecasting Model (WRF) was uesd to simulate the effects of three types of roofs (conventional roof, high albedo roof and randomized glass-polymer hybrid metamaterial roof) during the extreme high temperature weather in Nanjing in 1-31 July 2017. The results showed that (1) cooling roofs (like high albedo roof and randomized glass-polymer hybrid metamaterial roof) can reduce the temperature of cities by weakening the solar radiation reaching the surface of the city. During the daytime, the average temperature of randomized glass-polymer hybrid metamaterial roof drops by 0.8-1.2℃, and the average temperature decreases 0.2-0.4℃ in the nighttime. The average temperature of the high albedol roof drops by 0.6-0.8℃ during the day and decreases 0.2℃ at night. (2) The surface temperature index can be used to characterize the thermal performance of the cooling roof. The surface temperature index of the randomized glass-polymer hybrid metamaterial roof is 0.16-0.43. The surface temperature index of the high albedo roof is 0.05-0.26, indicating that the cooling effect of the randomized glass-polymer hybrid metamaterial roof is stronger than the high albedo roof. (3) The high albedo roof and the randomized glass-polymer hybrid metamaterial roof can return 36.7% and 47.1% of the solar short-wave radiation respectively. The atmosphere absorbs heat 19.6% less and 34.8% less than conventional roof.
12 Review on the Representation of Model Uncertainty in Convection-Allowing Ensemble Prediction System
2019, 45(8):1158-1168.
DOI: 10.7519/j.issn.1000-0526.2019.08.012
Abstract:
Convection-Allowing Ensemble Prediction System (CAEPS) has obvious advantages in predicting the convective events due to its fruitful probabilistic forecast information. The CAEPS has become one of the hot focuses in researching and developing the local high-resolution numerical weather prediction (NWP) system. Compared with global ensemble prediction system, representation of model uncertainty in CAEPS is lack of systematic research and theoretical basis, and becomes an important issue worthwhile further research. This paper devotes to reviewing the current state of CAEPS and the studies in representing the model uncertainty over the past 10 years. Up to now, several approaches have been developed in representing model uncertainties, including multi-model, multi-physic, multi-parameter and stochastic physics. These approaches have been widely applied in ensemble forecast of severe convective weather, tropical cyclone intensity and tracks and so on, but with limited effect in improving under-dispersion problem of CAEPS. Such limited effect may come from deficiency of these approaches in formulating the model uncertainties related to small-to-meso-scale system. Except for reviewing the past researches, we propose a way to detect and describe model uncertainties at convective scale.
Convection-Allowing Ensemble Prediction System (CAEPS) has obvious advantages in predicting the convective events due to its fruitful probabilistic forecast information. The CAEPS has become one of the hot focuses in researching and developing the local high-resolution numerical weather prediction (NWP) system. Compared with global ensemble prediction system, representation of model uncertainty in CAEPS is lack of systematic research and theoretical basis, and becomes an important issue worthwhile further research. This paper devotes to reviewing the current state of CAEPS and the studies in representing the model uncertainty over the past 10 years. Up to now, several approaches have been developed in representing model uncertainties, including multi-model, multi-physic, multi-parameter and stochastic physics. These approaches have been widely applied in ensemble forecast of severe convective weather, tropical cyclone intensity and tracks and so on, but with limited effect in improving under-dispersion problem of CAEPS. Such limited effect may come from deficiency of these approaches in formulating the model uncertainties related to small-to-meso-scale system. Except for reviewing the past researches, we propose a way to detect and describe model uncertainties at convective scale.
13 Comparing Strong Wind Data Observed by Boundary Layer Wind Profiling Radar and L-Band Radar in Jinan
2019, 45(8):1169-1180.
DOI: 10.7519/j.issn.1000-0526.2019.08.013
Abstract:
Based on the strong wind (≥10.8 m·s-1) data observed by Jinan boundary layer wind profile radar (WPR) and L-band sounding radar (LW) located in the same place, statistical correlation, fitting, and profile analysis were used to systematically compare the similarities and differences between spatial and temporal changes of both of them. The results show that the correlation coefficients of the u-component, v-component, wind direction, and wind speed are 0.973, 0.965, 0.994, and 0.665 respectively. The standard deviations are 2.04 m·s-1, 2.88 m·s-1, 10.82° and 2.53 m·s-1 respectively. The correlations of the two observed strong wind data are relatively high, with wind direction samples better than speed samples and precipitation period samples better than that of non-precipitation period samples. This indicates that the strong wind data observed by WPR are credible and the WPR horizontal wind data during precipitation period can be used. The strong wind direction and speed of the two observations are basically the same, but the differences at lower levels are bigger, especially at the heights of 340 m and below. Below the heights of 2980 m, 1900 m, and 2740 m the wind direction samples of WPR during precipitation periods, non-precipitation periods, and the whole periods have slightly lower values than that of LW. However, the wind speeds of WPR below 1300 m, 2740 m, and 1660 m are slightly bigger than that of LW. The overall complementarity of the two data is good, and the differences in wind direction, wind speed, and v-component of the two types are in accordance with the e-index law or the law of logarithm increase or decrease, but the u-component needs to be fitted by segments. When the regression equation is calculated, variations in height should be taken into account.
Based on the strong wind (≥10.8 m·s-1) data observed by Jinan boundary layer wind profile radar (WPR) and L-band sounding radar (LW) located in the same place, statistical correlation, fitting, and profile analysis were used to systematically compare the similarities and differences between spatial and temporal changes of both of them. The results show that the correlation coefficients of the u-component, v-component, wind direction, and wind speed are 0.973, 0.965, 0.994, and 0.665 respectively. The standard deviations are 2.04 m·s-1, 2.88 m·s-1, 10.82° and 2.53 m·s-1 respectively. The correlations of the two observed strong wind data are relatively high, with wind direction samples better than speed samples and precipitation period samples better than that of non-precipitation period samples. This indicates that the strong wind data observed by WPR are credible and the WPR horizontal wind data during precipitation period can be used. The strong wind direction and speed of the two observations are basically the same, but the differences at lower levels are bigger, especially at the heights of 340 m and below. Below the heights of 2980 m, 1900 m, and 2740 m the wind direction samples of WPR during precipitation periods, non-precipitation periods, and the whole periods have slightly lower values than that of LW. However, the wind speeds of WPR below 1300 m, 2740 m, and 1660 m are slightly bigger than that of LW. The overall complementarity of the two data is good, and the differences in wind direction, wind speed, and v-component of the two types are in accordance with the e-index law or the law of logarithm increase or decrease, but the u-component needs to be fitted by segments. When the regression equation is calculated, variations in height should be taken into account.
2019, 45(8):1181-1188.
DOI: 10.7519/j.issn.1000-0526.2019.08.014
Abstract:
The main characteristics of the general atmospheric circulation in May 2019 are as follows. There were two polar vortex centers in the Northern Hemisphere. The polar vortex in the north of Canada was stronger than usual and was closed to normal in the south of Novaya Zemlya. The 500 hPa geopotential height presented the distribution of a fourwave pattern in the high latitude of Northern Hemisphere. The strength of Western Pacific subtropical high was similar to normal years, and the south branch though was a little weaker. The monthly mean temperature across China was 16.2℃, closed to normal. The temperature fluctuated greatly in this month, and Yunnan Province experienced the warmest mean temperature since 1961. The monthly mean precipitation amount over China was 69.5 mm, same as the normal amount (69.5 mm). In addition, seven regional torrential rain processes occurred in China this month, and the extremely severe weather like hail and thunderstorms hit Beijing. Severe droughts were found in Jianghuai, Huanghuai and Yunnan, and four sanddust events happened in the northern part of China.
The main characteristics of the general atmospheric circulation in May 2019 are as follows. There were two polar vortex centers in the Northern Hemisphere. The polar vortex in the north of Canada was stronger than usual and was closed to normal in the south of Novaya Zemlya. The 500 hPa geopotential height presented the distribution of a fourwave pattern in the high latitude of Northern Hemisphere. The strength of Western Pacific subtropical high was similar to normal years, and the south branch though was a little weaker. The monthly mean temperature across China was 16.2℃, closed to normal. The temperature fluctuated greatly in this month, and Yunnan Province experienced the warmest mean temperature since 1961. The monthly mean precipitation amount over China was 69.5 mm, same as the normal amount (69.5 mm). In addition, seven regional torrential rain processes occurred in China this month, and the extremely severe weather like hail and thunderstorms hit Beijing. Severe droughts were found in Jianghuai, Huanghuai and Yunnan, and four sanddust events happened in the northern part of China.
Mobile website
® 2024 All Rights Reserved
Supported by:Beijing E-Tiller Technology Development Co., Ltd.
ISSN:1000-0526 CN:11-2282/P