ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Volume 46,Issue 10,2020 Table of Contents
2020, 46(10):1261-1271.
DOI: 10.7519/j.issn.1000-0526.2020.10.001
Abstract:
Based on statistical verification and forecast bias analysis on the rainstorm processes of landed typhoons in 2018, we improve the observationbased ensemble subsetting technique that has been applied on operational forecast, to obtain objective products of typhoon precipitation with higher resolution and forecast accuracy, using multimodel forecasts from several centers, the realtime typhoon locations and track forecasts from National Meteorological Centre. The multimodel forecasts include precipitation and typhoon track ensemble forecasts and operational high resolution forecasts from ECMWF and NCEP, the forecasts of main regional models (GRAPESMeso, GRAPES3 km, RMAPS, SMSWARMS) in China. The results show that the spatial resolution of the improved objective product is significantly promoted compared with the previous version. The forecast accuracy is also significantly improved compared with the operational deterministic forecast from ECMWF and NCEP, and the improvement rate is 15%-20% roughly. The threat score of the improved objective product is also higher than the forecast of regional models, and slightly higher than the QPF of forecaster. In addition, studies have shown that the accuracy of the improved objective product has a high correlation with the selection of reference track. The threat score of objective product based on the average track of 3 to 5 best members is higher than the one based on the average track of all members. The observationbased ensemble subsetting and QPF fusion technique based on probability matching, is helpful for improving 〖JP2〗the typhoon rainstorm forecast of the global and regional models.
Based on statistical verification and forecast bias analysis on the rainstorm processes of landed typhoons in 2018, we improve the observationbased ensemble subsetting technique that has been applied on operational forecast, to obtain objective products of typhoon precipitation with higher resolution and forecast accuracy, using multimodel forecasts from several centers, the realtime typhoon locations and track forecasts from National Meteorological Centre. The multimodel forecasts include precipitation and typhoon track ensemble forecasts and operational high resolution forecasts from ECMWF and NCEP, the forecasts of main regional models (GRAPESMeso, GRAPES3 km, RMAPS, SMSWARMS) in China. The results show that the spatial resolution of the improved objective product is significantly promoted compared with the previous version. The forecast accuracy is also significantly improved compared with the operational deterministic forecast from ECMWF and NCEP, and the improvement rate is 15%-20% roughly. The threat score of the improved objective product is also higher than the forecast of regional models, and slightly higher than the QPF of forecaster. In addition, studies have shown that the accuracy of the improved objective product has a high correlation with the selection of reference track. The threat score of objective product based on the average track of 3 to 5 best members is higher than the one based on the average track of all members. The observationbased ensemble subsetting and QPF fusion technique based on probability matching, is helpful for improving 〖JP2〗the typhoon rainstorm forecast of the global and regional models.
2020, 46(10):1272-1285.
DOI: 10.7519/j.issn.1000-0526.2020.10.002
Abstract:
To comprehensively evaluate the fine gridded forecasts, based on site observation and gridpoint analysis data, the verification of precipitation and temperature forecasts of the 2016-2018 national gridded guidance forecast, provincial and municipal revised feedback gridded forecasts were carried out, and compared with the GRAPES and ECMWF model outputs. The results show that the fine gridded forecast operation can realize the chain of increasing value step by step from numerical model system, national guidance forecast to provincial and municipal revised feedback product. The national guidance precipitation, daily high and low temperature forecasts have a significant improvement on the basis of the model forecast products. Compared to ECMWF model, light rain ETS score of the precipitation is increased by 9%-37%, the maximum increase of rain storm ETS score reaches 41% and the maximum decrease of daily high temperature RMSE reaches 16%. The daily high/low temperature of the provincial and municipal revised feedback products can further have the reduced error on the basis of the national guidance forecast, and the optimal forecast results can be obtained. However, the national guidance products need to be further improved, with emphasis on controlling the false alarm rate of the heavy rain forecast, improving the significant advance deviation of the afternoon precipitation peak, improving the ability to characterize spatially refined precipitation, and improving the forecast statistical model for the lowest temperature. Besides, as the provincial and municipal revised feedback products have failed to correct the national guidance forecast well in the aspects of precipitation and hour temperature forecast, they need to be further strengthened. The fine gridded forecast products can replace the urban weather forecast, which is beneficial to the intensive and efficient forecasting process.
To comprehensively evaluate the fine gridded forecasts, based on site observation and gridpoint analysis data, the verification of precipitation and temperature forecasts of the 2016-2018 national gridded guidance forecast, provincial and municipal revised feedback gridded forecasts were carried out, and compared with the GRAPES and ECMWF model outputs. The results show that the fine gridded forecast operation can realize the chain of increasing value step by step from numerical model system, national guidance forecast to provincial and municipal revised feedback product. The national guidance precipitation, daily high and low temperature forecasts have a significant improvement on the basis of the model forecast products. Compared to ECMWF model, light rain ETS score of the precipitation is increased by 9%-37%, the maximum increase of rain storm ETS score reaches 41% and the maximum decrease of daily high temperature RMSE reaches 16%. The daily high/low temperature of the provincial and municipal revised feedback products can further have the reduced error on the basis of the national guidance forecast, and the optimal forecast results can be obtained. However, the national guidance products need to be further improved, with emphasis on controlling the false alarm rate of the heavy rain forecast, improving the significant advance deviation of the afternoon precipitation peak, improving the ability to characterize spatially refined precipitation, and improving the forecast statistical model for the lowest temperature. Besides, as the provincial and municipal revised feedback products have failed to correct the national guidance forecast well in the aspects of precipitation and hour temperature forecast, they need to be further strengthened. The fine gridded forecast products can replace the urban weather forecast, which is beneficial to the intensive and efficient forecasting process.
3 Study on Artificial Intelligence Technology and Its Application to Chongqing Operational Nowcasting
2020, 46(10):1286-1296.
DOI: 10.7519/j.issn.1000-0526.2020.10.003
Abstract:
Previous researches showed that the application of artificial intelligence (AI) techniques could substantially improve severe convective weather nowcasting capabilities. Cooperating with Baidu Inc., Chongqing Meteorological Service preliminarily implemented the intelligent nowcasting model of threedimensional radar echo using TrajGRU technique based on the radar data of 2008-2018. Together with the ground observation data and the Unet technique, the intelligent identification model of thunderstorm gale and hail were established. The AI techniques above were used to operational thunderstorm gale, hail and precipitation nowcasting. Compared to the operational products of the Severe Weather Automatic Nowcast (SWAN) system, AI products showed obvious improvement in the prediction of radar echo evolution. The intelligent prediction ability of radar echo decreased with time at a lower speed than that of the traditional extrapolation method, and the prediction for longer lead times was improved. Verification showed that AI precipitation forecast had a higher skill than SWAN to a certain extent. During the 2019 trial operational application period, the lead times of intelligent forecast model for thunderstorm gale and hail forecast were 77 min and 37 min, respectively. The research and application of AI techniques in the early warning of severe convective weather in Chongqing have achieved initial results.
Previous researches showed that the application of artificial intelligence (AI) techniques could substantially improve severe convective weather nowcasting capabilities. Cooperating with Baidu Inc., Chongqing Meteorological Service preliminarily implemented the intelligent nowcasting model of threedimensional radar echo using TrajGRU technique based on the radar data of 2008-2018. Together with the ground observation data and the Unet technique, the intelligent identification model of thunderstorm gale and hail were established. The AI techniques above were used to operational thunderstorm gale, hail and precipitation nowcasting. Compared to the operational products of the Severe Weather Automatic Nowcast (SWAN) system, AI products showed obvious improvement in the prediction of radar echo evolution. The intelligent prediction ability of radar echo decreased with time at a lower speed than that of the traditional extrapolation method, and the prediction for longer lead times was improved. Verification showed that AI precipitation forecast had a higher skill than SWAN to a certain extent. During the 2019 trial operational application period, the lead times of intelligent forecast model for thunderstorm gale and hail forecast were 77 min and 37 min, respectively. The research and application of AI techniques in the early warning of severe convective weather in Chongqing have achieved initial results.
2020, 46(10):1297-1309.
DOI: 10.7519/j.issn.1000-0526.2020.10.004
Abstract:
In this study， the physical PM2.5 remote sensing (PMRS) method was used to invert the FY-4A observation data, and through the fusion with the surface station data, the near-surface PM2.5 gridding observation data in China were obtained. A grid map of the relationship between PM2.5 and PM10 was established under different conditions of clean, haze and dust background, and PM10 concentration in China was further estimated. The results showed that there is a similar correlation between columnar volume-to-extinction ratio of fine particulates (VEf) and fine mode fraction (FMF) in different regions. With FMF=0.4 as the boundary, two fitting equations of VEf are established respectively. The estimated correlation (r2) between VEf and AERONET observation is higher than 0.85. During the haze period, the PM2.5 mass concentration obtained by PMRS has a good match with the observation site distribution, which can basically reflect the high concentration area of pollution. In single point test, the remote sensing result has a certain correlation with the surface observation, with r2 reaching 0.39 in the region of Beijing-Tianjin-Hebei. However, to some extent there is still overestimation or underestimation in the value of inversion compared to surface observation data. In order to solve this problem, the study combines the satellite inversion grid results with the surface observation site, and finally obtains a 0.25°×0.25° national PM2.5 gridding observation data that are in good agreement with the surface observation data. The r2 between PM10 and PM2.5 is higher than 0.7 under different weather conditions. Among them, the value PM10/PM2.5>3 matches with the sand source area and the high dust area in China during the dust period. During the haze period, PM10/PM2.5 is close to 1, and the value is between 1 and 2 during cleaning period for most stations. Through the grid map of the relationship between PM2.5 and PM10, according to different weather backgrounds, the gridded surface PM10 in China is obtained, and the results can better reflect the dust process in Northwest China.
In this study， the physical PM2.5 remote sensing (PMRS) method was used to invert the FY-4A observation data, and through the fusion with the surface station data, the near-surface PM2.5 gridding observation data in China were obtained. A grid map of the relationship between PM2.5 and PM10 was established under different conditions of clean, haze and dust background, and PM10 concentration in China was further estimated. The results showed that there is a similar correlation between columnar volume-to-extinction ratio of fine particulates (VEf) and fine mode fraction (FMF) in different regions. With FMF=0.4 as the boundary, two fitting equations of VEf are established respectively. The estimated correlation (r2) between VEf and AERONET observation is higher than 0.85. During the haze period, the PM2.5 mass concentration obtained by PMRS has a good match with the observation site distribution, which can basically reflect the high concentration area of pollution. In single point test, the remote sensing result has a certain correlation with the surface observation, with r2 reaching 0.39 in the region of Beijing-Tianjin-Hebei. However, to some extent there is still overestimation or underestimation in the value of inversion compared to surface observation data. In order to solve this problem, the study combines the satellite inversion grid results with the surface observation site, and finally obtains a 0.25°×0.25° national PM2.5 gridding observation data that are in good agreement with the surface observation data. The r2 between PM10 and PM2.5 is higher than 0.7 under different weather conditions. Among them, the value PM10/PM2.5>3 matches with the sand source area and the high dust area in China during the dust period. During the haze period, PM10/PM2.5 is close to 1, and the value is between 1 and 2 during cleaning period for most stations. Through the grid map of the relationship between PM2.5 and PM10, according to different weather backgrounds, the gridded surface PM10 in China is obtained, and the results can better reflect the dust process in Northwest China.
2020, 46(10):1310-1319.
DOI: 10.7519/j.issn.1000-0526.2020.10.005
Abstract:
Precipitation is the main cause of geological disasters. Geological disaster meteorological risk mainly exists in casualties, property damages and the expected loss of interrupted economic activities that are caused by geological disasters. Geological disaster meteorological risk degree can be expressed as the product of disaster probability of precipitation factor times environment potential risk degree, and further times vulnerability degree in numerical data. The effective rainfall data are selected as precipitation factor, and hereby, the geological disaster probability fitting equations of effective rainfall for nine regions are established. The potential risk of geological disaster is evaluated by the information method of the underlying surface environments and the vulnerability degree is employed to a simplified assessing model, which was related to three aspects of GDP, landuse and population. Then, the geological disaster meteorological risk forecasting model is constructed. By using the products of QPE and QPF in high resolution, the mesh refinement business test of risk model is established. Compared with geological disaster records, the results are illustrated to be reliable.
Precipitation is the main cause of geological disasters. Geological disaster meteorological risk mainly exists in casualties, property damages and the expected loss of interrupted economic activities that are caused by geological disasters. Geological disaster meteorological risk degree can be expressed as the product of disaster probability of precipitation factor times environment potential risk degree, and further times vulnerability degree in numerical data. The effective rainfall data are selected as precipitation factor, and hereby, the geological disaster probability fitting equations of effective rainfall for nine regions are established. The potential risk of geological disaster is evaluated by the information method of the underlying surface environments and the vulnerability degree is employed to a simplified assessing model, which was related to three aspects of GDP, landuse and population. Then, the geological disaster meteorological risk forecasting model is constructed. By using the products of QPE and QPF in high resolution, the mesh refinement business test of risk model is established. Compared with geological disaster records, the results are illustrated to be reliable.
2020, 46(10):1320-1329.
DOI: 10.7519/j.issn.1000-0526.2020.10.006
Abstract:
In order to promote the construction of fine gridded forecasting of marine meteorology, National Meteorological Centre began to develop the objective forecasting method of sea fog in 2013. The objective forecasting method of sea fog based on ingredientsbased methodology has been continuously improved. The method of sea fog forecasting based on decision tree method and the product of sea fog forecast index forecasting have been developed. The main sea fog processes in the northern part of China offshore sea can be well forecasted based on objective methods. The average 24 h fog occurrence TS score of objective method in the northern part of China offshore sea in 2018 is about 0.25. Sea fog prediction method based on ingredientsbased methodology was applied into the generation rules of weather phenomena background fields, and the objective method results have provided strong support for subjective forecasting. The 24 h dense fog TS scores of subjective sea fog prediction results in 2018 based on fine gridded prediction get close to 0.25 in the central and southern Yellow Sea, and 0.15 in the Beibu Gulf.
In order to promote the construction of fine gridded forecasting of marine meteorology, National Meteorological Centre began to develop the objective forecasting method of sea fog in 2013. The objective forecasting method of sea fog based on ingredientsbased methodology has been continuously improved. The method of sea fog forecasting based on decision tree method and the product of sea fog forecast index forecasting have been developed. The main sea fog processes in the northern part of China offshore sea can be well forecasted based on objective methods. The average 24 h fog occurrence TS score of objective method in the northern part of China offshore sea in 2018 is about 0.25. Sea fog prediction method based on ingredientsbased methodology was applied into the generation rules of weather phenomena background fields, and the objective method results have provided strong support for subjective forecasting. The 24 h dense fog TS scores of subjective sea fog prediction results in 2018 based on fine gridded prediction get close to 0.25 in the central and southern Yellow Sea, and 0.15 in the Beibu Gulf.
2020, 46(10):1330-1339.
DOI: 10.7519/j.issn.1000-0526.2020.10.007
Abstract:
This study uses a spatial analysis and visualization technology to intelligently and similarly search for the regularity of the temporal and spatial variation of typhoons from 1949 to 2018 to form a comprehensive quantitative judgment system based on three key indicators, which are spatial location, feature elements and temporal rule, and to establish initially a unified judgment standard. According to path similarity determination, the method based on the combination of multiple dynamic fitting curves and similar deviation is proposed. The research results show that the comprehensive quantitative judgment system can effectively reduce the uncertainty of single index. And the dynamic judgment method can effectively solve the problem of observation point mismatch. Take Typhoon Mangkhut (1822) as an example. Firstly, we use retrieval methods 〖JP2〗as data cleaning, feature extraction and quick retrieval creation to narrow searching〖JP〗 range, retrieving 10 possible typhoons with similarity to the target, and then we use the comprehensive quantitative judgment method, confirming 7 similar typhoons. During the judgment process, three targets can be achieved, including the multidimensional spatiotemporal data being drilled down step by step based on customized conditions, the quantitative comprehensive intelligent retrieval and the visualization of similarity results. This can provide important reference for typhoon forecast and early warning operation.
This study uses a spatial analysis and visualization technology to intelligently and similarly search for the regularity of the temporal and spatial variation of typhoons from 1949 to 2018 to form a comprehensive quantitative judgment system based on three key indicators, which are spatial location, feature elements and temporal rule, and to establish initially a unified judgment standard. According to path similarity determination, the method based on the combination of multiple dynamic fitting curves and similar deviation is proposed. The research results show that the comprehensive quantitative judgment system can effectively reduce the uncertainty of single index. And the dynamic judgment method can effectively solve the problem of observation point mismatch. Take Typhoon Mangkhut (1822) as an example. Firstly, we use retrieval methods 〖JP2〗as data cleaning, feature extraction and quick retrieval creation to narrow searching〖JP〗 range, retrieving 10 possible typhoons with similarity to the target, and then we use the comprehensive quantitative judgment method, confirming 7 similar typhoons. During the judgment process, three targets can be achieved, including the multidimensional spatiotemporal data being drilled down step by step based on customized conditions, the quantitative comprehensive intelligent retrieval and the visualization of similarity results. This can provide important reference for typhoon forecast and early warning operation.
2020, 46(10):1340-1350.
DOI: 10.7519/j.issn.1000-0526.2020.10.008
Abstract:
Seamless smart gridded forecast is the important content and support for the China Meteorological Administration modern weather operation. To enhance the application of gridded forecast in the forecast service operation, and improve the efficiency of the fine gridded forecast data visualization and analysis, we designed and implemented the Gridded Forecast Application Analysis Platform, analyzed the characteristics of the seamless gridded forecast data and the platform, adopted the browser/servce (B/S) design mode, and took key technologies such as the realtime distributed process computation, WebGL and GIS spatial analysis, achieving the functions such as the efficiently massive gridded forecast data process and analysis, web service, visualization, impact analysis, mapping and so on. This platform has already been stably applied in national and provincial meteorological decision service operations, such as, typoon, storm and other disasters emergency service, which has illustrated the platform’s strong practicability.
Seamless smart gridded forecast is the important content and support for the China Meteorological Administration modern weather operation. To enhance the application of gridded forecast in the forecast service operation, and improve the efficiency of the fine gridded forecast data visualization and analysis, we designed and implemented the Gridded Forecast Application Analysis Platform, analyzed the characteristics of the seamless gridded forecast data and the platform, adopted the browser/servce (B/S) design mode, and took key technologies such as the realtime distributed process computation, WebGL and GIS spatial analysis, achieving the functions such as the efficiently massive gridded forecast data process and analysis, web service, visualization, impact analysis, mapping and so on. This platform has already been stably applied in national and provincial meteorological decision service operations, such as, typoon, storm and other disasters emergency service, which has illustrated the platform’s strong practicability.
2020, 46(10):1351-1361.
DOI: 10.7519/j.issn.1000-0526.2020.10.009
Abstract:
Correcting and interpreting the model’s temperature forecast is an important means of improve the accuracy rate of objective temperature forecast in the context of model’s system error and impact of terrain. In this paper bias correction and the quasisymmetrical mixed running training period MOS forecast systems are developed based on ECMWF fineresolution model products. With the different methods an optimal consensus forecast method of temperature is designed. The accuracy rates of different models and different objective methods of daily maximum and minimum temperatures are compared. The results show that bias running correction of daily maximum and minimum temperature forecast in 10 to 30 days can improve the ECMWF fineresolution model’s temperature forecast. Bias running correction can significantly improve the daily maximum and minimum temperature forecasts of the models in short range, especially for the central mountainous area and check stations of Shandong Province. Bias running correction of daily minimum temperature can give higher improvement of the model’s forecast than that of daily maximum temperature. The MOS system can improve the daily maximum and minimum temperature forecasts too, while the accuracy rates of ECMWF fineresolution model, bias correction and MOS temperature objective forecast are different for different regions and different seasons in Shandong Province. Running optimal consensus forecast method can give further improvement of daily maximum and minimum temperature forecasts by integrating the advantages of different objective methods.
Correcting and interpreting the model’s temperature forecast is an important means of improve the accuracy rate of objective temperature forecast in the context of model’s system error and impact of terrain. In this paper bias correction and the quasisymmetrical mixed running training period MOS forecast systems are developed based on ECMWF fineresolution model products. With the different methods an optimal consensus forecast method of temperature is designed. The accuracy rates of different models and different objective methods of daily maximum and minimum temperatures are compared. The results show that bias running correction of daily maximum and minimum temperature forecast in 10 to 30 days can improve the ECMWF fineresolution model’s temperature forecast. Bias running correction can significantly improve the daily maximum and minimum temperature forecasts of the models in short range, especially for the central mountainous area and check stations of Shandong Province. Bias running correction of daily minimum temperature can give higher improvement of the model’s forecast than that of daily maximum temperature. The MOS system can improve the daily maximum and minimum temperature forecasts too, while the accuracy rates of ECMWF fineresolution model, bias correction and MOS temperature objective forecast are different for different regions and different seasons in Shandong Province. Running optimal consensus forecast method can give further improvement of daily maximum and minimum temperature forecasts by integrating the advantages of different objective methods.
2020, 46(10):1362-1374.
DOI: 10.7519/j.issn.1000-0526.2020.10.010
Abstract:
The formation and evolution of the supercell that happened in Chengdu on 7 August 2016 were discussed. Based on Chengdu Doppler Weather Radar， windprofiling radar， and densely laidout automatic station observation， the contributing factors of the mesoanticyclone were studied in this paper. The results are as follows. The mesoanticyclonic supercell was formed under the northerly airflow in the west of the upper cold vortex, with strong cold advection in middle and upper levels. The convective instability energy (CAPE) reached 5 〖KG-*5〗029.7 J·kg-1, the temperature difference between 500 hPa and 850 hPa was 29℃, and the wind shear vector difference between 500 hPa and 925 hPa was about 16 m·s-1. The sounding as a whole took on the shape of a bell mouth, in which the upper level was dry and cold while the lower level was warm and wet. The existence of lowerlevel inversion was conducive to energy accumulation. Thunderstorms were triggered by westward winds under the forced uplift of Longquan Mountains, while downward flow produced cold outflow and triggered new cells continuously on the north side.Thunderstorms and new cells merged into supercell. The mesoanticyclonic supercell storm was accompanied by the echo characteristics such as lowlevel strong convergence, mesoanticyclone, rear inflow, rear inflow gap, vortex couple, etc. The formation of mesoanticyclone in S1 supercell storm was formed via merging the lower and middle levels. For lowlevel mesoanticyclones, small eddies were generated when thunderstorm and cells merged. The baroclinic vorticity was caused by the intrusion of dry cold air and warm wet updraft, which caused convergence to rotate. Thunderstorm developed strongly under strong convergence, and strong upward motion caused vertical vorticity to stretch, increasing rotation. For midlevel mesoanticyclones, the horizontal vorticity in the height range of 3-4 km was about 1.2×10-2 s-1, which was beneficial to the formation of horizontal vortex tubes. Vortex couples were generated under the strong updraft and downward airflow. The anticyclones were developed by counterclockwise rotation of midlevel and highlevel winds.
The formation and evolution of the supercell that happened in Chengdu on 7 August 2016 were discussed. Based on Chengdu Doppler Weather Radar， windprofiling radar， and densely laidout automatic station observation， the contributing factors of the mesoanticyclone were studied in this paper. The results are as follows. The mesoanticyclonic supercell was formed under the northerly airflow in the west of the upper cold vortex, with strong cold advection in middle and upper levels. The convective instability energy (CAPE) reached 5 〖KG-*5〗029.7 J·kg-1, the temperature difference between 500 hPa and 850 hPa was 29℃, and the wind shear vector difference between 500 hPa and 925 hPa was about 16 m·s-1. The sounding as a whole took on the shape of a bell mouth, in which the upper level was dry and cold while the lower level was warm and wet. The existence of lowerlevel inversion was conducive to energy accumulation. Thunderstorms were triggered by westward winds under the forced uplift of Longquan Mountains, while downward flow produced cold outflow and triggered new cells continuously on the north side.Thunderstorms and new cells merged into supercell. The mesoanticyclonic supercell storm was accompanied by the echo characteristics such as lowlevel strong convergence, mesoanticyclone, rear inflow, rear inflow gap, vortex couple, etc. The formation of mesoanticyclone in S1 supercell storm was formed via merging the lower and middle levels. For lowlevel mesoanticyclones, small eddies were generated when thunderstorm and cells merged. The baroclinic vorticity was caused by the intrusion of dry cold air and warm wet updraft, which caused convergence to rotate. Thunderstorm developed strongly under strong convergence, and strong upward motion caused vertical vorticity to stretch, increasing rotation. For midlevel mesoanticyclones, the horizontal vorticity in the height range of 3-4 km was about 1.2×10-2 s-1, which was beneficial to the formation of horizontal vortex tubes. Vortex couples were generated under the strong updraft and downward airflow. The anticyclones were developed by counterclockwise rotation of midlevel and highlevel winds.
2020, 46(10):1375-1384.
DOI: 10.7519/j.issn.1000-0526.2020.10.011
Abstract:
In boreal spring 2020 (March-April-May), the average temperature in China is 11.5℃ ranking the fifth since 1961.The temperature is above or near average in most China. The mean precipitation is 137 mm, lower by 4% than climatology. The characteristic precipitation in East China is featured with enhanced precipitation in North and South China and suppressed in central China. The positive anomalies are mainly in most of Northeast, eastern North China, eastern Inner Mongolia, southern Jiangnan and most of South China. The negative is pronounced in the JiangHuai Region. The subseasonal variation of precipitation is significant. During boreal spring (mainly in April and May) in midhigh latitudes, the signal of the pattern in the upper troposphere is two troughs and one ridge which is characterized by one blockage over west Lake Baikal and two troughs located over northwest Ural Mountains and the Sea of Japan, respectively. In low troposphere northerly anomaly prevails in eastern China with strong meridional circulation. An anticyclone in low troposphere is located at Northwest Pacific Ocean while the WesternNorth Pacific subtropical high (WPSH) is much stronger and its ridge line is more southwestward. The water vapor is divergent over most Eastern China with deficient precipitation. In March 2020 the zonal circulation dominates midhigh latitudes of Asia and WPSH exhibits stronger and northward, resulting in positive precipitation anomaly in Jiangnan and South China. The influence of tropical SST forcing shows that the Indian Ocean Basin warming (IOBW) and West Pacific play important roles in the sustained strengthening and westward trend of WPSH in spring in the decaying 2019/2020 weak Modoki ENSO. The North Atlantic SST dipole (NASD) mode shows good spatial persistence from February-March to April-May 2020. NASD in early boreal spring can be an important predictor that impacts the midhigh latitude circulation with blocking over west Lake Baikal during April-May.
In boreal spring 2020 (March-April-May), the average temperature in China is 11.5℃ ranking the fifth since 1961.The temperature is above or near average in most China. The mean precipitation is 137 mm, lower by 4% than climatology. The characteristic precipitation in East China is featured with enhanced precipitation in North and South China and suppressed in central China. The positive anomalies are mainly in most of Northeast, eastern North China, eastern Inner Mongolia, southern Jiangnan and most of South China. The negative is pronounced in the JiangHuai Region. The subseasonal variation of precipitation is significant. During boreal spring (mainly in April and May) in midhigh latitudes, the signal of the pattern in the upper troposphere is two troughs and one ridge which is characterized by one blockage over west Lake Baikal and two troughs located over northwest Ural Mountains and the Sea of Japan, respectively. In low troposphere northerly anomaly prevails in eastern China with strong meridional circulation. An anticyclone in low troposphere is located at Northwest Pacific Ocean while the WesternNorth Pacific subtropical high (WPSH) is much stronger and its ridge line is more southwestward. The water vapor is divergent over most Eastern China with deficient precipitation. In March 2020 the zonal circulation dominates midhigh latitudes of Asia and WPSH exhibits stronger and northward, resulting in positive precipitation anomaly in Jiangnan and South China. The influence of tropical SST forcing shows that the Indian Ocean Basin warming (IOBW) and West Pacific play important roles in the sustained strengthening and westward trend of WPSH in spring in the decaying 2019/2020 weak Modoki ENSO. The North Atlantic SST dipole (NASD) mode shows good spatial persistence from February-March to April-May 2020. NASD in early boreal spring can be an important predictor that impacts the midhigh latitude circulation with blocking over west Lake Baikal during April-May.
2020, 46(10):1385-1392.
DOI: 10.7519/j.issn.1000-0526.2020.10.012
Abstract:
The main characteristics of the general atmospheric circulation in July 2020 are shown as follows. The polar vortex splits into multiple centers distributed around the polar which were stronger than normal in the Northern Hemisphere. Compared to the normal, the western Pacific subtropical high was stronger and the position of which was further west and south. The western Pacific subtropical high was located in the middle and lower reaches of the Yangtze River and south of the Yangtze River during the first and middle dekads, and obviously extended westward and northward shifting between north and south during the last dekad of this month. The monthly mean precipitation of China in July was 125.7 mm, more than the normal by 4.2%. The positive anomaly of precipitation was significantly more than 1 to 2 times in northern part of Jiangnan, Jianghuai, Jianghan, Huanghuai, and the Southwest China. However, the negative anomaly of rainfall was 50% in the Northeast China and the South China. There were seven regional torrential rain processes in this month, seen mainly in the middle and lower reaches of the Yangtze River, Huanghuai and Southwest China. The daily precipitation of 103 stations reached or exceeded the extreme values of the same period. Severe flood disaster occurred in the middle and lower reaches of the Yangtze River and the Huaihe River Basin. The monthly mean temperature of China was 22.1℃, slightly higher than the usual. The mean maximum temperature in southern Fujian, Guangdong, and eastern Hainan was 2-4℃ higher than normal. During middle and last dekads, largescale persistent high temperature weather occurred in Jiangnan and South China, where 81 stations located in the coasts of Fujian and Guangdong, southern Hunan, and central and eastern Sichuan experienced extreme high temperatures. In terms of typhoon, it was the first time that there was no typhoon event in July 2020, which is the first time since 1949, so it is called “typhoon absence”.
The main characteristics of the general atmospheric circulation in July 2020 are shown as follows. The polar vortex splits into multiple centers distributed around the polar which were stronger than normal in the Northern Hemisphere. Compared to the normal, the western Pacific subtropical high was stronger and the position of which was further west and south. The western Pacific subtropical high was located in the middle and lower reaches of the Yangtze River and south of the Yangtze River during the first and middle dekads, and obviously extended westward and northward shifting between north and south during the last dekad of this month. The monthly mean precipitation of China in July was 125.7 mm, more than the normal by 4.2%. The positive anomaly of precipitation was significantly more than 1 to 2 times in northern part of Jiangnan, Jianghuai, Jianghan, Huanghuai, and the Southwest China. However, the negative anomaly of rainfall was 50% in the Northeast China and the South China. There were seven regional torrential rain processes in this month, seen mainly in the middle and lower reaches of the Yangtze River, Huanghuai and Southwest China. The daily precipitation of 103 stations reached or exceeded the extreme values of the same period. Severe flood disaster occurred in the middle and lower reaches of the Yangtze River and the Huaihe River Basin. The monthly mean temperature of China was 22.1℃, slightly higher than the usual. The mean maximum temperature in southern Fujian, Guangdong, and eastern Hainan was 2-4℃ higher than normal. During middle and last dekads, largescale persistent high temperature weather occurred in Jiangnan and South China, where 81 stations located in the coasts of Fujian and Guangdong, southern Hunan, and central and eastern Sichuan experienced extreme high temperatures. In terms of typhoon, it was the first time that there was no typhoon event in July 2020, which is the first time since 1949, so it is called “typhoon absence”.
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ISSN:1000-0526 CN:11-2282/P