ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 47,Issue 10,2021 Table of Contents
2021, 47(10):1169-1181.
DOI: 10.7519/j.issn.1000-0526.2021.10.001
Abstract:
The characteristics of multi-source monitoring data and the causes of sudden temperature decline before and after the abrupt snowfall in southern Jiangsu Province on 28 March 2020, are investigated with the data of automatic meteorological station, dual polarization radar， microwave radiometer, NCEP reanalysis data and simulation results of mesoscale model WRF. The research shows that the time and area changes of temperature drop are consistent with the beginning time and moving direction of heavy precipitation in this sudden snowfall. The 0℃ layer height decline and the increase of liquid water content inversed by microwave radiometer can be used as the approach criterion to judge the surface temperature and precipitation phase transition. The time of ground temperature decrease lags behind the temperature drop in the 1-3 km height for about 2-3 hours. The radar reflectivity factor, the correlation coefficient and classified products of dual polarization radar products have obvious characteristics in the judgment of rain-snow conversion and snow expansion direction during this snowfall. The light zone and shape change of the 0℃ layer are consistent with the cooling zone and movement direction of the lower layer. In the correlation coefficients, the asymmetrical characteristic regions and morphological changes of different phase particles reflect the changes in height, thickness and movement direction of the melting layer. Asymmetric characteristics of mixed phase layer and wet snow monitoring signals of classified products appear 1-2 hours earlier than snowfall. The diagnostic analysis shows that the latent heat of melting during the subsidence of ice crystals and snowflakes and the latent heat of evaporation through the dry area have a positive contribution to the short and rapid decrease of temperature in the lower layer. The temperature change presents the spatio-temporal evolution characteristics from above to below and from west to east. The earliest temperature decline occurs at the height of 850-700 hPa. The near-surface temperature decline is delayed by about 2 hours. Therefore, this result suggests that the multi-source monitoring data can provide better decision support for the rain-snow conversion process, especially in the short-time and nowcasting forecasts.
The characteristics of multi-source monitoring data and the causes of sudden temperature decline before and after the abrupt snowfall in southern Jiangsu Province on 28 March 2020, are investigated with the data of automatic meteorological station, dual polarization radar， microwave radiometer, NCEP reanalysis data and simulation results of mesoscale model WRF. The research shows that the time and area changes of temperature drop are consistent with the beginning time and moving direction of heavy precipitation in this sudden snowfall. The 0℃ layer height decline and the increase of liquid water content inversed by microwave radiometer can be used as the approach criterion to judge the surface temperature and precipitation phase transition. The time of ground temperature decrease lags behind the temperature drop in the 1-3 km height for about 2-3 hours. The radar reflectivity factor, the correlation coefficient and classified products of dual polarization radar products have obvious characteristics in the judgment of rain-snow conversion and snow expansion direction during this snowfall. The light zone and shape change of the 0℃ layer are consistent with the cooling zone and movement direction of the lower layer. In the correlation coefficients, the asymmetrical characteristic regions and morphological changes of different phase particles reflect the changes in height, thickness and movement direction of the melting layer. Asymmetric characteristics of mixed phase layer and wet snow monitoring signals of classified products appear 1-2 hours earlier than snowfall. The diagnostic analysis shows that the latent heat of melting during the subsidence of ice crystals and snowflakes and the latent heat of evaporation through the dry area have a positive contribution to the short and rapid decrease of temperature in the lower layer. The temperature change presents the spatio-temporal evolution characteristics from above to below and from west to east. The earliest temperature decline occurs at the height of 850-700 hPa. The near-surface temperature decline is delayed by about 2 hours. Therefore, this result suggests that the multi-source monitoring data can provide better decision support for the rain-snow conversion process, especially in the short-time and nowcasting forecasts.
2021, 47(10):1182-1192.
DOI: 10.7519/j.issn.1000-0526.2021.10.002
Abstract:
Based on the Bayesian model for decision supporting, the decision making procedures in the meteorological service for the Beijing 21 July 2012 extra torrential rain are simulated and analyzed in this paper. The diagnosis in decision makings on the typical torrentail rain event try to prove its possibility of application in supporting decision making model (SDMM) to attain the optimal decision in solving the uncertainties problems of decision making, under the current condition of data resources (e.g., the mesoscale NWP system and observation data)， weather forecasting and meteorological observing technological levels. With the NWP products on that day, the floods and debris flow risks both have been assessed to be high. Combine with the data of floods threshold and rainfalls recorded in the historical flood events and the predicted rainfall magnitude distribution on that day, a high torrential rain risk can also be recognized consequently. The posteriori probability deduced using the Bayesian model is only 23.1%. However, considering the expected losses (EL) gap in predicting severe weather and non-severe weather, the non-severe weather prediction EL can be obviously greater than the severe weather prediction EL. Therefore, the optimal decision making in that situation would have been to publish severe weather warning and pick the pessimistic scheme in the meteorological service advisably. The simulation of the meteorological service on the extra torrential rain day reveals that the tolerability to the severe weather forecasting and warning uncertainty can relieve the pressure on forecasters who are often afraid of giving false forecasting and warning. In additional to perfect emergency preparations, the uncertainty information could be published, and properly be delivered to the actual meteorological information users in weather forecasts, which ultimately helps to converte the deterministic weather forecasting mode into that of non-determinacy.
Based on the Bayesian model for decision supporting, the decision making procedures in the meteorological service for the Beijing 21 July 2012 extra torrential rain are simulated and analyzed in this paper. The diagnosis in decision makings on the typical torrentail rain event try to prove its possibility of application in supporting decision making model (SDMM) to attain the optimal decision in solving the uncertainties problems of decision making, under the current condition of data resources (e.g., the mesoscale NWP system and observation data)， weather forecasting and meteorological observing technological levels. With the NWP products on that day, the floods and debris flow risks both have been assessed to be high. Combine with the data of floods threshold and rainfalls recorded in the historical flood events and the predicted rainfall magnitude distribution on that day, a high torrential rain risk can also be recognized consequently. The posteriori probability deduced using the Bayesian model is only 23.1%. However, considering the expected losses (EL) gap in predicting severe weather and non-severe weather, the non-severe weather prediction EL can be obviously greater than the severe weather prediction EL. Therefore, the optimal decision making in that situation would have been to publish severe weather warning and pick the pessimistic scheme in the meteorological service advisably. The simulation of the meteorological service on the extra torrential rain day reveals that the tolerability to the severe weather forecasting and warning uncertainty can relieve the pressure on forecasters who are often afraid of giving false forecasting and warning. In additional to perfect emergency preparations, the uncertainty information could be published, and properly be delivered to the actual meteorological information users in weather forecasts, which ultimately helps to converte the deterministic weather forecasting mode into that of non-determinacy.
2021, 47(10):1193-1205.
DOI: 10.7519/j.issn.1000-0526.2021.10.003
Abstract:
The precipitation forecasts made by three global models, ECMWF-IFS, NCEP-GFS, and GRAPES-GFS, are verified based on the meteorological and hydrological observations over Yalong River Basin in western Sichuan Province in 2018 flood season. Generally, the 3 d precipitation forecasts of the three models consist fairly well with observations, especially for light rains in which omissions are less but false alarms are more common. However, in moderately and heavily rainy days, precipitation forecasts appear less useful. These forecasts work the best when east-moving plateau trough coupled with southwest stream dominates, but are the worst when weather induced by low-level shears along with southwest stream is more prevailing. When the west-extending subtropical high dominates, their skills in predicting rainfall are unstable. Moreover, intercomparisons of these three precipitation forecasts show that in Yalong River Basin ECMWF-IFS performs best, GRAPES-GFS ranks next, but more care needs to be taken when NCEP-GFS is applied in daily operation. ECMWF-IFS usually forecasts more rainfall and its TS scores for moderate and heavy rains are usually higher than the TS scores of the other two models, but it more probably makes false alarms for light rains. Precipitation forecasted by GRAPES-GFS is less than others, TS scores for light rains are the highest among the three models, while its ability of predicting moderate and heavy rains is still weaker than ECMWF-IFS. NCEP-GFS can forecast light rain well, but more easily misses moderate and heavy rains.
The precipitation forecasts made by three global models, ECMWF-IFS, NCEP-GFS, and GRAPES-GFS, are verified based on the meteorological and hydrological observations over Yalong River Basin in western Sichuan Province in 2018 flood season. Generally, the 3 d precipitation forecasts of the three models consist fairly well with observations, especially for light rains in which omissions are less but false alarms are more common. However, in moderately and heavily rainy days, precipitation forecasts appear less useful. These forecasts work the best when east-moving plateau trough coupled with southwest stream dominates, but are the worst when weather induced by low-level shears along with southwest stream is more prevailing. When the west-extending subtropical high dominates, their skills in predicting rainfall are unstable. Moreover, intercomparisons of these three precipitation forecasts show that in Yalong River Basin ECMWF-IFS performs best, GRAPES-GFS ranks next, but more care needs to be taken when NCEP-GFS is applied in daily operation. ECMWF-IFS usually forecasts more rainfall and its TS scores for moderate and heavy rains are usually higher than the TS scores of the other two models, but it more probably makes false alarms for light rains. Precipitation forecasted by GRAPES-GFS is less than others, TS scores for light rains are the highest among the three models, while its ability of predicting moderate and heavy rains is still weaker than ECMWF-IFS. NCEP-GFS can forecast light rain well, but more easily misses moderate and heavy rains.
2021, 47(10):1206-1218.
DOI: 10.7519/j.issn.1000-0526.2021.10.004
Abstract:
In this paper an object-based selection method is proposed on how to select the best products from lots of numerical forecasts. This method firstly gives single object score with different weight means of TS score, center of gravity score, area size score, and location shape score. On this basis, the regional forecast overall evaluation and selection are conducted. Batch comparative experiments of 3 months and cases studies with local scattered rainfall and large-scale rainfall weather processes are conducted. The results show that the object-based selection result is reasonable. The weight of every score item of single object has great impact on the selection result. Increasing the weight of TS score (exceeding 0.4) can improve the selection result. It is the key factor to calculate regional forecast score based on every object area size weight score in the forecast region. The object-based selection method has remarkable advantages for local scattered rainfall and it can overcome TS score’s shortcoming. Usually the object-based selection result is more reasonable because it includes the shape, center of gravity and area scores of rainfall forecast.
In this paper an object-based selection method is proposed on how to select the best products from lots of numerical forecasts. This method firstly gives single object score with different weight means of TS score, center of gravity score, area size score, and location shape score. On this basis, the regional forecast overall evaluation and selection are conducted. Batch comparative experiments of 3 months and cases studies with local scattered rainfall and large-scale rainfall weather processes are conducted. The results show that the object-based selection result is reasonable. The weight of every score item of single object has great impact on the selection result. Increasing the weight of TS score (exceeding 0.4) can improve the selection result. It is the key factor to calculate regional forecast score based on every object area size weight score in the forecast region. The object-based selection method has remarkable advantages for local scattered rainfall and it can overcome TS score’s shortcoming. Usually the object-based selection result is more reasonable because it includes the shape, center of gravity and area scores of rainfall forecast.
2021, 47(10):1219-1232.
DOI: 10.7519/j.issn.1000-0526.2021.10.005
Abstract:
Based on the daily precipitation data at 97 national stations in Hunan Province from 1981 to 2018, conventional observation data, ERA-Interim data and typhoon path data, the climatic statistics method, meteorological analysis method and composite synthesis method are used to analyze the climatic characteristics of extreme precipitation in Hunan Province and their weather system types. The results show that during the past 38 years, the average threshold of the daily extreme precipitation in Hunan Province was 71.6 mm, and there were 130 extreme precipitation days per year. Both the values had large interannual variability, and there was a significant change in 1993. Before 1993, the average threshold of the daily extreme precipitation was low (65.7 mm), and there were only 99 extreme precipitation days per year; after 1993, the average threshold was high (74.7 mm), and there were 146 extreme precipitation days per year. The spatial distributions of daily extreme precipitation thresholds and extreme precipitation days were uneven. In central Hunan and areas north to it, the thresholds of extreme precipitation were high, the intensity of extreme precipitation was strong, and the frequency of occurrence was low. But in the south of Hunan, the threshold was low, the intensity of extreme precipitation was weak and the frequency of occurrence was high. The regional extreme precipitation processes of Hunan mainly occur from May to August, especially in June. Five types for weather systems of extreme precipitation processes are summarized: the southwest vortex and warm shear line type, the cold trough and shear line type, the typhoon type, the subtropical high edge type, the consistent southerly wind type. The main influence systems of extreme precipitation in Hunan are upper trough, southwest vortex, shear line and low-level jet. If the southwest vortex does not move out of the southwest region of China or its location is to the south, the extreme precipitation in Hunan will be caused by the southwest vortex and warm shear line, and if the location of southwest vortex is to the north, or there is a new vortex developing and strengthening on the east side of Wuling Mountains, then the extreme precipitation in Hunan will be caused by the cold shear line behind the southwest vortex (new vortex). The topography has a significant effect on the increase of extreme precipitation, especially on the extreme precipitation process of typhoon in southeastern Hunan. In different seasons, the subtropical high has different effects on the area and intensity of extreme precipitation. For the extreme precipitation in the warm zone under the background of weak forcing, the application of high spatio-temporal resolution data should be strengthened to analyze the meso- and small-scale trigger mechanism.
Based on the daily precipitation data at 97 national stations in Hunan Province from 1981 to 2018, conventional observation data, ERA-Interim data and typhoon path data, the climatic statistics method, meteorological analysis method and composite synthesis method are used to analyze the climatic characteristics of extreme precipitation in Hunan Province and their weather system types. The results show that during the past 38 years, the average threshold of the daily extreme precipitation in Hunan Province was 71.6 mm, and there were 130 extreme precipitation days per year. Both the values had large interannual variability, and there was a significant change in 1993. Before 1993, the average threshold of the daily extreme precipitation was low (65.7 mm), and there were only 99 extreme precipitation days per year; after 1993, the average threshold was high (74.7 mm), and there were 146 extreme precipitation days per year. The spatial distributions of daily extreme precipitation thresholds and extreme precipitation days were uneven. In central Hunan and areas north to it, the thresholds of extreme precipitation were high, the intensity of extreme precipitation was strong, and the frequency of occurrence was low. But in the south of Hunan, the threshold was low, the intensity of extreme precipitation was weak and the frequency of occurrence was high. The regional extreme precipitation processes of Hunan mainly occur from May to August, especially in June. Five types for weather systems of extreme precipitation processes are summarized: the southwest vortex and warm shear line type, the cold trough and shear line type, the typhoon type, the subtropical high edge type, the consistent southerly wind type. The main influence systems of extreme precipitation in Hunan are upper trough, southwest vortex, shear line and low-level jet. If the southwest vortex does not move out of the southwest region of China or its location is to the south, the extreme precipitation in Hunan will be caused by the southwest vortex and warm shear line, and if the location of southwest vortex is to the north, or there is a new vortex developing and strengthening on the east side of Wuling Mountains, then the extreme precipitation in Hunan will be caused by the cold shear line behind the southwest vortex (new vortex). The topography has a significant effect on the increase of extreme precipitation, especially on the extreme precipitation process of typhoon in southeastern Hunan. In different seasons, the subtropical high has different effects on the area and intensity of extreme precipitation. For the extreme precipitation in the warm zone under the background of weak forcing, the application of high spatio-temporal resolution data should be strengthened to analyze the meso- and small-scale trigger mechanism.
2021, 47(10):1233-1245.
DOI: 10.7519/j.issn.1000-0526.2021.10.006
Abstract:
Based on daily air pollution data, meteorological observation data and sounding data from Weather Station of Shapingba in Chongqing, and the NCEP/NCAR reanalysis data during 2014-2018, the characteristics of monthly, seasonal and annual AQI, different air pollutant concentration and the day numbers with different air pollutant concentrations are analyzed systematically. Besides, the 500 hPa geopotential height field, 850 hPa wind field, vertical velocity field and the skew T-lnp diagram of heavy pollution days are also analyzed. The results show that the monthly variation of AQI in Chongqing is W-shaped, while those of PM2.5, PM10 and CO are U-shaped, and that of O3 is inverted U-shaped. Except that the concentration of O3 is the highest in midsummer, the concentrations of other pollutants are so high in December and January that the air quality becomes the worst in the two months. The concentration of O3 shows an increasing trend but other pollutants major decreasing year by year, and the air quality was significantly improved. PM2.5 was the main pollutant in Chongqing, especially in winter. PM10 pollution increases in spring, NO2 pollution mainly occurs in early spring and late autumn, and O3 pollution mainly appears in midsummer. Air pollution usually happens in winter. The meteorological diffusion condition is poor in Chongqing when the circulation in the middle and high latitudes of Eurasia in the middle troposphere has a distribution of low in the north and high in the south, and the cold air force is so weak that the lower troposphere is dominated by the south wind in most of the southern region. The condition is favorable for diffusion and clearance of air pollutant when the circulation in the middle and high latitudes of Eurasia in the middle troposphere has a distribution of high in the north and low in the south, and the meridional circulation is obvious. The rising convergence of water vapor is so weak that the relative humidity of the lower troposphere is low on heavy pollution days. The near-surface inversion layer and the thin wet layer maintain for a long time making atmospheric stratification relatively stable, which is the key of development and maintenance of air pollution in Chongqing.
Based on daily air pollution data, meteorological observation data and sounding data from Weather Station of Shapingba in Chongqing, and the NCEP/NCAR reanalysis data during 2014-2018, the characteristics of monthly, seasonal and annual AQI, different air pollutant concentration and the day numbers with different air pollutant concentrations are analyzed systematically. Besides, the 500 hPa geopotential height field, 850 hPa wind field, vertical velocity field and the skew T-lnp diagram of heavy pollution days are also analyzed. The results show that the monthly variation of AQI in Chongqing is W-shaped, while those of PM2.5, PM10 and CO are U-shaped, and that of O3 is inverted U-shaped. Except that the concentration of O3 is the highest in midsummer, the concentrations of other pollutants are so high in December and January that the air quality becomes the worst in the two months. The concentration of O3 shows an increasing trend but other pollutants major decreasing year by year, and the air quality was significantly improved. PM2.5 was the main pollutant in Chongqing, especially in winter. PM10 pollution increases in spring, NO2 pollution mainly occurs in early spring and late autumn, and O3 pollution mainly appears in midsummer. Air pollution usually happens in winter. The meteorological diffusion condition is poor in Chongqing when the circulation in the middle and high latitudes of Eurasia in the middle troposphere has a distribution of low in the north and high in the south, and the cold air force is so weak that the lower troposphere is dominated by the south wind in most of the southern region. The condition is favorable for diffusion and clearance of air pollutant when the circulation in the middle and high latitudes of Eurasia in the middle troposphere has a distribution of high in the north and low in the south, and the meridional circulation is obvious. The rising convergence of water vapor is so weak that the relative humidity of the lower troposphere is low on heavy pollution days. The near-surface inversion layer and the thin wet layer maintain for a long time making atmospheric stratification relatively stable, which is the key of development and maintenance of air pollution in Chongqing.
2021, 47(10):1246-1254.
DOI: 10.7519/j.issn.1000-0526.2021.10.007
Abstract:
In order to identify the meteorological factor and key peroid of Sclerotinia sclerotiorum for oilseed rape over the region along the Yangtze River, and improve the ability of monitoring and evaluating, this paper builds a meteorological grade evaluation model based on precipitation and temperature, using the data including infected plant rate of Sclerotinia sclerotiorum for oilseed rape and daily meteorological data from 1995 to 2019 in Chizhou and Tongcheng, Anhui Province, by the means of linear correlation and regression analysis. Then the fitting test and validation are carried out for the model. The results show that the key period of stem infected is from the late March to the early May. Precipitation is the main meteorological factor affecting the occurrence of Sclerotinia sclerotiorum, and the appropriate temperature could promote the occurrence of Sclerotinia.The comprehensive meteorological index formed by introducing the precipitation coefficient and temperature coefficient, could effectively indicate the comprehensive effect of precipitation and temperature on the Sclerotinia sclerotiorum. The accuracies of the evaluation model for simulation and validation are 86.2% and 85.0% in Chizhou, and 83.8% and 85.0% in Tongcheng, respectively. Therefore, the model established in this study can be used for the monitoring and evaluation of Sclerotinia sclerotiorum in the areas along the Yangtze River in Anhui Province.
In order to identify the meteorological factor and key peroid of Sclerotinia sclerotiorum for oilseed rape over the region along the Yangtze River, and improve the ability of monitoring and evaluating, this paper builds a meteorological grade evaluation model based on precipitation and temperature, using the data including infected plant rate of Sclerotinia sclerotiorum for oilseed rape and daily meteorological data from 1995 to 2019 in Chizhou and Tongcheng, Anhui Province, by the means of linear correlation and regression analysis. Then the fitting test and validation are carried out for the model. The results show that the key period of stem infected is from the late March to the early May. Precipitation is the main meteorological factor affecting the occurrence of Sclerotinia sclerotiorum, and the appropriate temperature could promote the occurrence of Sclerotinia.The comprehensive meteorological index formed by introducing the precipitation coefficient and temperature coefficient, could effectively indicate the comprehensive effect of precipitation and temperature on the Sclerotinia sclerotiorum. The accuracies of the evaluation model for simulation and validation are 86.2% and 85.0% in Chizhou, and 83.8% and 85.0% in Tongcheng, respectively. Therefore, the model established in this study can be used for the monitoring and evaluation of Sclerotinia sclerotiorum in the areas along the Yangtze River in Anhui Province.
2021, 47(10):1255-1265.
DOI: 10.7519/j.issn.1000-0526.2021.10.008
Abstract:
Based on the artificial and automatic observed data at Nanchang Changbei Airport, the conventional surface observations and sounding data provided by China Meteorological Administration, and the hourly air quality index (AQI) data of 9 stations in Nanchang from China National Environmental Monitoring Centre, 76 fog events from September 2013 to September 2017 at Changbei Airport are classified and statistically analyzed. The results show that the fogs of Changbei Airport mainly occur in November to May, they mostly form in the period 04:00-10:00 BT, and dissipate in 06:00-14:00 BT, mostly lasting less than 4 hours. Rain fog occurs most, followed by radiation fog and advection-radiation fog, and advection fog appears the least. The fogs of Changbei Airport are closely related to the air quality. The AQI often has an upward trend before fog occurs, with the value ranging within 54-100. The AQI in rain fogs is the largest, often accompanied by mild to severe pollution. Rain fogs mainly occur between the low-level warm and wet shear lines and the inverted trough on surface in autumn, winter and spring. They often form after continuous light rain or drizzle.The visibility maintains at a low level, mostly 600-800 m, for a long time before the fogs are formed, and keeps stable. Radiation fogs usually occur in the weak high pressure from late autumn to early spring of the next year. They often form in the morning after rain stops and the sky clears, and gradually dissipates after sunrise. They last longer if the bottom of inversion layer is higher. Radiation fogs form after the gradual increase of humidity, and the visibility is mostly 200-600 m. Advection-radiation fogs mainly occur in the weak warm advection behind the high pressure moving east to the sea in early winter and spring. They form generally after the rapid increase of humidity, and the visibility is mostly 200-700 m. Advection fogs usually occur in the surface saddle pressure field south of the low-level shear line in spring and summer. They are generated after the end of rain induced by a north lift of the shear line, and the visibility is mostly 400-600 m.
Based on the artificial and automatic observed data at Nanchang Changbei Airport, the conventional surface observations and sounding data provided by China Meteorological Administration, and the hourly air quality index (AQI) data of 9 stations in Nanchang from China National Environmental Monitoring Centre, 76 fog events from September 2013 to September 2017 at Changbei Airport are classified and statistically analyzed. The results show that the fogs of Changbei Airport mainly occur in November to May, they mostly form in the period 04:00-10:00 BT, and dissipate in 06:00-14:00 BT, mostly lasting less than 4 hours. Rain fog occurs most, followed by radiation fog and advection-radiation fog, and advection fog appears the least. The fogs of Changbei Airport are closely related to the air quality. The AQI often has an upward trend before fog occurs, with the value ranging within 54-100. The AQI in rain fogs is the largest, often accompanied by mild to severe pollution. Rain fogs mainly occur between the low-level warm and wet shear lines and the inverted trough on surface in autumn, winter and spring. They often form after continuous light rain or drizzle.The visibility maintains at a low level, mostly 600-800 m, for a long time before the fogs are formed, and keeps stable. Radiation fogs usually occur in the weak high pressure from late autumn to early spring of the next year. They often form in the morning after rain stops and the sky clears, and gradually dissipates after sunrise. They last longer if the bottom of inversion layer is higher. Radiation fogs form after the gradual increase of humidity, and the visibility is mostly 200-600 m. Advection-radiation fogs mainly occur in the weak warm advection behind the high pressure moving east to the sea in early winter and spring. They form generally after the rapid increase of humidity, and the visibility is mostly 200-700 m. Advection fogs usually occur in the surface saddle pressure field south of the low-level shear line in spring and summer. They are generated after the end of rain induced by a north lift of the shear line, and the visibility is mostly 400-600 m.
2021, 47(10):1266-1276.
DOI: 10.7519/j.issn.1000-0526.2021.10.009
Abstract:
Operational positioning and intensity estimation, track, intensity and landfall point forecast errors of the typhoons over Western North Pacific and South China Sea in 2019 are evaluated. The results show that the overall errors of typhoon mean positioning and intensity estimation in 2019 were a little larger than in 2018, being 24.7 km and 2.5 m·s-1, respectively. Since 2013, the overall track forecast performance within 72 h did not show substantive improvement for both subjective and objective forecast methods. In 2019, the mean values of extreme error were up to 2.1-3.9 times as much as their annual mean track errors. The intensity forecast performance of CMA within 3 days is better than that of the other official typhoon forecast agencies. The landfall points of Typhoon Lekima at Wenling, Zhejiang Province and Qingdao, Shandong Province and the landfall points of Typhoon Bailu at Pingdong, Taiwan Province and Dongshan, Fujian Province were successfully predicted by all the official typhoon forecast agencies in 2019.
Operational positioning and intensity estimation, track, intensity and landfall point forecast errors of the typhoons over Western North Pacific and South China Sea in 2019 are evaluated. The results show that the overall errors of typhoon mean positioning and intensity estimation in 2019 were a little larger than in 2018, being 24.7 km and 2.5 m·s-1, respectively. Since 2013, the overall track forecast performance within 72 h did not show substantive improvement for both subjective and objective forecast methods. In 2019, the mean values of extreme error were up to 2.1-3.9 times as much as their annual mean track errors. The intensity forecast performance of CMA within 3 days is better than that of the other official typhoon forecast agencies. The landfall points of Typhoon Lekima at Wenling, Zhejiang Province and Qingdao, Shandong Province and the landfall points of Typhoon Bailu at Pingdong, Taiwan Province and Dongshan, Fujian Province were successfully predicted by all the official typhoon forecast agencies in 2019.
2021, 47(10):1277-1288.
DOI: 10.7519/j.issn.1000-0526.2021.10.010
Abstract:
Based on the precipitation and temperature data of national stations in China, NCEP/NCAR reanalysis and sea surface temperature data, the features and possible causes of climate anomalies in spring 2021 (March-April-May) in China are analyzed in this paper. In 2021, China experienced the fourth warmest spring since 1961 with an average temperature anomaly of 1.2℃, except that Central China was cooler than normal in April. The precipitation was near normal with a national average of 145.3 mm, but which the sub-seasonal periodic variation was quite significant, which is closely related to the periodic adjustment of circulation. From March to April, the mid-latitude circulation over Asia maintained an anomalous pattern of positive geopotential height (GPH) anomalies in the east of Lake Baikal but negative anomalies over the Ural Mountains. The Western Pacific subtropical high (WPSH) was weaker and further eastward than normal, which was conducive to water vapor transportation from the Northwest Pacific to the north of the Yangtze River, resulting in more precipitation in northern China but less precipitation in South China and Southwest China. However, the above patterns reversed in May, with positive GPH anomalies over the Ural Mountains and negative anomalies in Northeast Asia as well as the intensified and further northwestward WPSH. Correspondingly, the warm and humid southwesterly flow at lower-level strengthened, and the water vapor convergence and upward movement developed in southern China. This pattern was favorable for less precipitation in northern China while more precipitation in southern China, especially for frequent heavy rainstorms and severe convective weathers in the regions south of the Yangtze River. From mid-April, blocking activities in mid-high latitudes occurred frequently, causing a low-temperature anomaly in central China temporarily, and also becoming one of the important factors for the severe convective weather in southern China. The adjustment of atmospheric circulation in late spring is related to the interaction between high and low latitude circulation and the tropical SST evolution. In mid-April, the Arctic Area warmed up and the high ridge over the Ural Mountains strengthened, resulting in the above circulation transition in late spring. Meanwhile, with the rapid warming of the tropical Inian Ocean in May, the low latitude circulation situation in East Asia responding to the La Ni〖AKn~D〗a Event in the early stage was also significantly adjusted, thus leading to the significant variation in the distribution of sub-seasonal precipitation.
Based on the precipitation and temperature data of national stations in China, NCEP/NCAR reanalysis and sea surface temperature data, the features and possible causes of climate anomalies in spring 2021 (March-April-May) in China are analyzed in this paper. In 2021, China experienced the fourth warmest spring since 1961 with an average temperature anomaly of 1.2℃, except that Central China was cooler than normal in April. The precipitation was near normal with a national average of 145.3 mm, but which the sub-seasonal periodic variation was quite significant, which is closely related to the periodic adjustment of circulation. From March to April, the mid-latitude circulation over Asia maintained an anomalous pattern of positive geopotential height (GPH) anomalies in the east of Lake Baikal but negative anomalies over the Ural Mountains. The Western Pacific subtropical high (WPSH) was weaker and further eastward than normal, which was conducive to water vapor transportation from the Northwest Pacific to the north of the Yangtze River, resulting in more precipitation in northern China but less precipitation in South China and Southwest China. However, the above patterns reversed in May, with positive GPH anomalies over the Ural Mountains and negative anomalies in Northeast Asia as well as the intensified and further northwestward WPSH. Correspondingly, the warm and humid southwesterly flow at lower-level strengthened, and the water vapor convergence and upward movement developed in southern China. This pattern was favorable for less precipitation in northern China while more precipitation in southern China, especially for frequent heavy rainstorms and severe convective weathers in the regions south of the Yangtze River. From mid-April, blocking activities in mid-high latitudes occurred frequently, causing a low-temperature anomaly in central China temporarily, and also becoming one of the important factors for the severe convective weather in southern China. The adjustment of atmospheric circulation in late spring is related to the interaction between high and low latitude circulation and the tropical SST evolution. In mid-April, the Arctic Area warmed up and the high ridge over the Ural Mountains strengthened, resulting in the above circulation transition in late spring. Meanwhile, with the rapid warming of the tropical Inian Ocean in May, the low latitude circulation situation in East Asia responding to the La Ni〖AKn~D〗a Event in the early stage was also significantly adjusted, thus leading to the significant variation in the distribution of sub-seasonal precipitation.
2021, 47(10):1289-1296.
DOI: 10.7519/j.issn.1000-0526.2021.10.011
Abstract:
The general atmospheric circulation in July 2021 was mainly characterized by polar vortexes in Arctic Region with two centers stronger than normal, and the western North Pacific subtropical high was located more weastern and northern to the climatological location with stronger intensity. The national averaged monthly mean temperature in China was 23.1℃, 1.3℃ higher than the climatology (21.8℃). The national averaged monthly precipitation in China was 124.4 mm, 3.2% more than the climatology (120.6 mm). There were seven severe rain processes in July 2021, of which the most extreme one occurred in Henan Province, where observed precipitations at many sites broke the historical records. Among the three tropical cyclones active over the South China Sea and western North Pacific, No.2106 Typhoon Yanhua and No.2107 Typhoon Chapaka made landfall in China. The total landing numbers of typhoon were equal to normal. In addition, the long-lasting and wide-spreading high temperature events occurred in South China, south of Yangtze River, Xinjiang, and western part of the Inner Mongolia with daily maximum temperature at many sites breaking the historical records.
The general atmospheric circulation in July 2021 was mainly characterized by polar vortexes in Arctic Region with two centers stronger than normal, and the western North Pacific subtropical high was located more weastern and northern to the climatological location with stronger intensity. The national averaged monthly mean temperature in China was 23.1℃, 1.3℃ higher than the climatology (21.8℃). The national averaged monthly precipitation in China was 124.4 mm, 3.2% more than the climatology (120.6 mm). There were seven severe rain processes in July 2021, of which the most extreme one occurred in Henan Province, where observed precipitations at many sites broke the historical records. Among the three tropical cyclones active over the South China Sea and western North Pacific, No.2106 Typhoon Yanhua and No.2107 Typhoon Chapaka made landfall in China. The total landing numbers of typhoon were equal to normal. In addition, the long-lasting and wide-spreading high temperature events occurred in South China, south of Yangtze River, Xinjiang, and western part of the Inner Mongolia with daily maximum temperature at many sites breaking the historical records.
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ISSN:1000-0526 CN:11-2282/P