The Northeast China Cold Vortex(NECV)is a significant atmospheric circulation system that triggers severe weather in mid-to-high latitudes of Asia.Fengyun-4B(FY-4B)satellite provides 15-min atmospheric motion vector(A...The Northeast China Cold Vortex(NECV)is a significant atmospheric circulation system that triggers severe weather in mid-to-high latitudes of Asia.Fengyun-4B(FY-4B)satellite provides 15-min atmospheric motion vector(AMV)and 2-h three-dimensional temperature profiles,enabling unprecedented high spatiotemporal resolution for real-time vortex tracking.This study evaluates the effectiveness of FY-4B AMV and temperature products in tracking 24 NECVs in 2023,among which two strong NECVs in winter and summer 2023 were carefully examined.We first assessed the accuracy of wind speed and direction of the AMVs in the NECV monitoring region by comparing them with radiosonde observations,revealing reasonable correlation coefficients(CC),mean absolute errors(MAE),and root mean square errors(RMSE).NECVs and their centers were identified by using AMV data from four channels(CH09,CH10,CH11,and CH13)within the 200–500-hPa layer,employing the“8-point method”that sets specific criteria for the wind directions at 8 surrounding points to ensure a consistent cyclonic pattern around the central point.The NECV centers identified from AMVs are found to be close(mean distance of 181.9 km)to those determined by ERA5 geopotential height.The retrieved FY-4B temperature data are also evaluated against radiosonde observations,showing a high CC of 0.996 and RMSE of 1.87 K,indicating reliable temperature retrievals for NECV tracking.Based on the FY-4B/Geostationary Interferometric Infrared Sounder(GIIRS)500-hPa temperature,the NECV cold centers are obtained and cross-validated against ERA5 reanalysis temperature at 500 hPa,revealing a mean distance deviation of 140.6 km.The real-time operational NECV monitoring based on the FY-4B AMV and temperature products on high spatiotemporal resolutions in this study provides valuable information for disaster prevention and mitigation.展开更多
In order to improve the operational application ability of the Fengyun-4A(FY-4A)new sounding dataset,in this paper,validation of the FY-4A Geosynchronous Interferometric Infrared Sounder(FY-4A/GIIRS)temperature was ca...In order to improve the operational application ability of the Fengyun-4A(FY-4A)new sounding dataset,in this paper,validation of the FY-4A Geosynchronous Interferometric Infrared Sounder(FY-4A/GIIRS)temperature was carried out using the balloon sounding temperature from meteorological sounding stations.More than 350,000 samples were obtained through time–space matching,and the results show that the FY-4A/GIIRS temperature mean bias(MB)is 0.07°C,the mean absolute error(MAE)is 1.80°C,the root-mean-square error(RMSE)is 2.546°C,and the correlation coefficient(RR)is 0.95.The FY-4A/GIIRS temperature error is relatively larger in the upper and lower troposphere,and relatively smaller in the middle troposphere;that is,the temperature at 500 hPa is better than that at 850 hPa.The temporal variation is smaller in the upper and middle troposphere than in the lower troposphere.The reconstruction of missing data of FY-4A/GIIRS temperature in cloudy areas is also carried out and the results are evaluated.The spatial distribution of reconstructed FY-4A/GIIRS temperature and the fifth generation ECMWF reanalysis(ERA5)data is consistent and completely retains the minimum temperature center with high precision of FY-4A/GIIRS.There are more detailed characteristics of intensity and position at the cold center than that of the reanalysis data.Therefore,an operational satellite retrieval temperature product with time–space continuity and high accuracy is formed.The reconstructed FY-4A/GIIRS temperature is used to monitor a strong cold wave event in November 2021.The results show that the product effectively monitors the movement and intensity of cold air activities,and it also has good indication for the phase transition of rain and snow triggered by cold wave.展开更多
Methods of rainstorm disaster risk monitoring(RDRM)based on retrieved satellite rainfall data are studied.Due to significant regional differences,the global rainstorm disasters are not only affected by geography(such ...Methods of rainstorm disaster risk monitoring(RDRM)based on retrieved satellite rainfall data are studied.Due to significant regional differences,the global rainstorm disasters are not only affected by geography(such as topography and surface properties),but also by climate events.It is necessary to study rainstorm disaster-causing factors,hazard-formative environments,and hazard-affected incidents based on the climate distribution of precipitation and rainstorms worldwide.According to a global flood disaster dataset for the last 20 years,the top four flood disaster causes(accounting for 96.8%in total)related to rainstorms,from most to least influential,are heavy rain(accounting for 61.6%),brief torrential rain(16.7%),monsoonal rain(9.4%),and tropical cyclone/storm rain(9.1%).A dynamic global rainstorm disaster threshold is identified by using global climate data based on 3319 rainstorm-induced floods and rainfall data retrieved by satellites in the last 20 years.Taking the 7-day accumulated rainfall,3-and 12-h maximum rainfall,24-h rainfall,rainstorm threshold,and others as the main parameters,a rainstorm intensity index is constructed.Calculation and global mapping of hazard-formative environmental factor and hazard-affected body factor of rainstorm disasters are performed based on terrain and river data,population data,and economic data.Finally,a satellite remote sensing RDRM model is developed,incorporating the above three factors(rainstorm intensity index,hazard-formative environment factor,and hazard-affected body factor).The results show that the model can well capture the rainstorm disasters that happened in the middle and lower reaches of the Yangtze River in China and in South Asia in 2020.展开更多
基金Supported by the China Meteorological Administration Northeast China Cold Vortex Research Key Laboratory(2023SYIAEKFZD04)Research Project of China Meteorological Administration Training Centre(2024CMATCQN03 and2024CMATCPY01)。
文摘The Northeast China Cold Vortex(NECV)is a significant atmospheric circulation system that triggers severe weather in mid-to-high latitudes of Asia.Fengyun-4B(FY-4B)satellite provides 15-min atmospheric motion vector(AMV)and 2-h three-dimensional temperature profiles,enabling unprecedented high spatiotemporal resolution for real-time vortex tracking.This study evaluates the effectiveness of FY-4B AMV and temperature products in tracking 24 NECVs in 2023,among which two strong NECVs in winter and summer 2023 were carefully examined.We first assessed the accuracy of wind speed and direction of the AMVs in the NECV monitoring region by comparing them with radiosonde observations,revealing reasonable correlation coefficients(CC),mean absolute errors(MAE),and root mean square errors(RMSE).NECVs and their centers were identified by using AMV data from four channels(CH09,CH10,CH11,and CH13)within the 200–500-hPa layer,employing the“8-point method”that sets specific criteria for the wind directions at 8 surrounding points to ensure a consistent cyclonic pattern around the central point.The NECV centers identified from AMVs are found to be close(mean distance of 181.9 km)to those determined by ERA5 geopotential height.The retrieved FY-4B temperature data are also evaluated against radiosonde observations,showing a high CC of 0.996 and RMSE of 1.87 K,indicating reliable temperature retrievals for NECV tracking.Based on the FY-4B/Geostationary Interferometric Infrared Sounder(GIIRS)500-hPa temperature,the NECV cold centers are obtained and cross-validated against ERA5 reanalysis temperature at 500 hPa,revealing a mean distance deviation of 140.6 km.The real-time operational NECV monitoring based on the FY-4B AMV and temperature products on high spatiotemporal resolutions in this study provides valuable information for disaster prevention and mitigation.
基金Supported by the National Natural Science Foundation of China(42175014)National Key Research and Development Program of China(2021YFB3900400).
文摘In order to improve the operational application ability of the Fengyun-4A(FY-4A)new sounding dataset,in this paper,validation of the FY-4A Geosynchronous Interferometric Infrared Sounder(FY-4A/GIIRS)temperature was carried out using the balloon sounding temperature from meteorological sounding stations.More than 350,000 samples were obtained through time–space matching,and the results show that the FY-4A/GIIRS temperature mean bias(MB)is 0.07°C,the mean absolute error(MAE)is 1.80°C,the root-mean-square error(RMSE)is 2.546°C,and the correlation coefficient(RR)is 0.95.The FY-4A/GIIRS temperature error is relatively larger in the upper and lower troposphere,and relatively smaller in the middle troposphere;that is,the temperature at 500 hPa is better than that at 850 hPa.The temporal variation is smaller in the upper and middle troposphere than in the lower troposphere.The reconstruction of missing data of FY-4A/GIIRS temperature in cloudy areas is also carried out and the results are evaluated.The spatial distribution of reconstructed FY-4A/GIIRS temperature and the fifth generation ECMWF reanalysis(ERA5)data is consistent and completely retains the minimum temperature center with high precision of FY-4A/GIIRS.There are more detailed characteristics of intensity and position at the cold center than that of the reanalysis data.Therefore,an operational satellite retrieval temperature product with time–space continuity and high accuracy is formed.The reconstructed FY-4A/GIIRS temperature is used to monitor a strong cold wave event in November 2021.The results show that the product effectively monitors the movement and intensity of cold air activities,and it also has good indication for the phase transition of rain and snow triggered by cold wave.
基金Supported by the National Key Research and Development Program of China(2018YFC1506500)Open Research Fund of Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province(SZKT2016001)。
文摘Methods of rainstorm disaster risk monitoring(RDRM)based on retrieved satellite rainfall data are studied.Due to significant regional differences,the global rainstorm disasters are not only affected by geography(such as topography and surface properties),but also by climate events.It is necessary to study rainstorm disaster-causing factors,hazard-formative environments,and hazard-affected incidents based on the climate distribution of precipitation and rainstorms worldwide.According to a global flood disaster dataset for the last 20 years,the top four flood disaster causes(accounting for 96.8%in total)related to rainstorms,from most to least influential,are heavy rain(accounting for 61.6%),brief torrential rain(16.7%),monsoonal rain(9.4%),and tropical cyclone/storm rain(9.1%).A dynamic global rainstorm disaster threshold is identified by using global climate data based on 3319 rainstorm-induced floods and rainfall data retrieved by satellites in the last 20 years.Taking the 7-day accumulated rainfall,3-and 12-h maximum rainfall,24-h rainfall,rainstorm threshold,and others as the main parameters,a rainstorm intensity index is constructed.Calculation and global mapping of hazard-formative environmental factor and hazard-affected body factor of rainstorm disasters are performed based on terrain and river data,population data,and economic data.Finally,a satellite remote sensing RDRM model is developed,incorporating the above three factors(rainstorm intensity index,hazard-formative environment factor,and hazard-affected body factor).The results show that the model can well capture the rainstorm disasters that happened in the middle and lower reaches of the Yangtze River in China and in South Asia in 2020.
