High spatiotemporal resolution infrared radiances from FY-4A/AGRI(Advanced Geostationary Radiation Imager)can provide crucial information for rapidly developing severe convective weather.This study established a symme...High spatiotemporal resolution infrared radiances from FY-4A/AGRI(Advanced Geostationary Radiation Imager)can provide crucial information for rapidly developing severe convective weather.This study established a symmetric observation error model that differentiates between land and sea for FY-4A/AGRI all-sky assimilation,developed an all-sky assimilation scheme for FY-4A/AGRI based on hydrometeor control variables,and investigated the impacts of all-sky FY-4A/AGRI water vapor channels at different altitudes and rapid-update assimilation at different frequencies on the assimilation and forecasting of a severe convective weather event.Results show that simultaneous assimilation of two water vapor channels can enhance precipitation forecasts compared to single-channel assimilation,which is mainly attributable to a more accurate analysis of water vapor and hydrometeor information.Experiments with different assimilation frequencies demonstrate that the hourly assimilation frequency,compared to other frequencies,incorporates the high-frequency information from AGRI while reducing the impact of spurious oscillations caused by excessively high-frequency assimilation.This hourly assimilation frequency reduces the incoordination among thermal,dynamical,and water vapor conditions caused by excessively fast or slow assimilation frequencies,thus improving the forecast accuracy compared to other frequencies.展开更多
AGRIS (The Agricultural Sciences and Technology) is a booklist-style international agricultural database which is established by the international agricultural technology information system subordinate to FAO. It embo...AGRIS (The Agricultural Sciences and Technology) is a booklist-style international agricultural database which is established by the international agricultural technology information system subordinate to FAO. It embodies continued publications, documents, corpuses, books, technology reports, patents, maps, meeting papers, and other literatures, which are collected by 135 countries and regions, 146 branches of AGRIS, and 22 international organizations. Its content comprises all the agricultural fields in the world, as well as forestry, economy, aquatic sciences, fishery, human dietetics, and so on. This database is an international intelligence communication system maintained by FAO, which updates quarterly and increases by 0.13 million records annually, with large data amount.展开更多
Cloud detection is critical for satellite remote sensing algorithms and downstream applications.This study evaluates the official cloud mask(CLM)product of the Advanced Geostationary Radiation Imager(AGRI)on the Fengy...Cloud detection is critical for satellite remote sensing algorithms and downstream applications.This study evaluates the official cloud mask(CLM)product of the Advanced Geostationary Radiation Imager(AGRI)on the Fengyun-4A(FY-4A)satellite using two years of data from the Cloud Aerosol Lidar with Orthogonal Polarization(CALIOP)over China.The evaluation reveals moderate performance,with an accuracy(ACC)of 79%for daytime and 80%for nighttime.However,the FY-4A CLM struggles with high false-positive rates(FPRs of 35%during the day and 23%at night),often misclassifying clear skies as clouds.To address this issue,a random forest(RF)-based cloud detection algorithm is developed,using collocated CALIOP observations as reference labels for model development and validation.The models are divided into daytime and nighttime categories based on the solar zenith angle.Feature engineering demonstrates that adding temporal information,spatial texture information,and dynamic surface features reduces FPR values significantly.The ACC of the daytime(nighttime)model improved by up to 13.6%(10.2%).The proposed RF models achieve exceptional cloud detection,with ACC and true-positive rates(TPR)exceeding 90%with an FPR below 10%for both day and night,outperforming the FY-4A CLM.Compared to MODIS and FY-4A CLM,the RF-based models demonstrate superior accuracy in identifying clouds under challenging conditions such as dust,snow,and high pollution.This study offers a promising alternative to enhance cloud detection for the FY-4A imager.展开更多
静止卫星具有可连续高频率观测的特点,被广泛应用于数值天气预报中,以获得更精细、更真实的数值模式初始条件。基于WRF框架的陕西省区域数值模式系统,针对2022年7月陕西一次强降水过程,利用三维变分直接同化方法,协同常规观测资料,同化...静止卫星具有可连续高频率观测的特点,被广泛应用于数值天气预报中,以获得更精细、更真实的数值模式初始条件。基于WRF框架的陕西省区域数值模式系统,针对2022年7月陕西一次强降水过程,利用三维变分直接同化方法,协同常规观测资料,同化风云四号A星所探测的两个水汽通道辐射率资料。通过设计三组对比试验:(1)不同化任何资料的控制试验(CTRL);(2)仅同化常规观测资料的试验(CONV);(3)同化常规观测与AGRI水汽通道的试验(AGRI),系统评估了晴空区FY-4A卫星两个水汽通道辐射资料同化对降水预报的改进效果。结果表明,经过一系列的质量控制和偏差订正,通道9(10)同化前观测亮温和背景场亮温差值(observation minus background,简称OMB)的平均值由0.76(0.78)K减小到0.04(-0.02)K,同化后观测亮温和分析场亮温差值(observation minus analysis,简称OMA)的平均值进一步缩小为0.01(0.01)K;通道9(10)同化前观测亮温和背景场场亮温差OMB标准差为0.83(0.84)K,同化后观测亮温和分析场亮温差OMA的标准差为0.43(0.49)K,说明同化AGRI水汽通道辐射资料改善了模式的初始场。通过协同同化FY-4A AGRI水汽通道辐射率资料与常规观测资料,显著改善了降水预报性能,常规观测资料通过调整风场优化了天气系统配置,使降水落区与实况更加接近,AGRI水汽通道资料同化修正了中高层比湿场,使强降水中心的强度预报误差降低20%。展开更多
AGRIS (The Agricultural Sciences and Technology) is a booklist-style international agricultural database which is established by the international agricultural technology information system subordinate to FAO. It embo...AGRIS (The Agricultural Sciences and Technology) is a booklist-style international agricultural database which is established by the international agricultural technology information system subordinate to FAO. It embodies continued publications, documents, corpuses, books, technology reports, patents, maps, meeting papers, and other literatures, which are collected by 135 countries and regions, 146 branches of AGRIS, and 22 international organizations.展开更多
AGRIS(The Agricultural Sciences and Technology)is a booklist-style international agricultural database which is established by the international agricultural technology information system subordinate to FAO.It embodie...AGRIS(The Agricultural Sciences and Technology)is a booklist-style international agricultural database which is established by the international agricultural technology information system subordinate to FAO.It embodies continued publications,documents,corpuses.展开更多
基金supported by the National Key R&D Program of China(Grant No.2022YFC3080500)the National Natural Science Foundation of China(Grant Nos.U2142208,42475158,and 42105149)the High-Performance Computing Center of Nanjing University of Information Science&Technology for supporting this work。
文摘High spatiotemporal resolution infrared radiances from FY-4A/AGRI(Advanced Geostationary Radiation Imager)can provide crucial information for rapidly developing severe convective weather.This study established a symmetric observation error model that differentiates between land and sea for FY-4A/AGRI all-sky assimilation,developed an all-sky assimilation scheme for FY-4A/AGRI based on hydrometeor control variables,and investigated the impacts of all-sky FY-4A/AGRI water vapor channels at different altitudes and rapid-update assimilation at different frequencies on the assimilation and forecasting of a severe convective weather event.Results show that simultaneous assimilation of two water vapor channels can enhance precipitation forecasts compared to single-channel assimilation,which is mainly attributable to a more accurate analysis of water vapor and hydrometeor information.Experiments with different assimilation frequencies demonstrate that the hourly assimilation frequency,compared to other frequencies,incorporates the high-frequency information from AGRI while reducing the impact of spurious oscillations caused by excessively high-frequency assimilation.This hourly assimilation frequency reduces the incoordination among thermal,dynamical,and water vapor conditions caused by excessively fast or slow assimilation frequencies,thus improving the forecast accuracy compared to other frequencies.
文摘AGRIS (The Agricultural Sciences and Technology) is a booklist-style international agricultural database which is established by the international agricultural technology information system subordinate to FAO. It embodies continued publications, documents, corpuses, books, technology reports, patents, maps, meeting papers, and other literatures, which are collected by 135 countries and regions, 146 branches of AGRIS, and 22 international organizations. Its content comprises all the agricultural fields in the world, as well as forestry, economy, aquatic sciences, fishery, human dietetics, and so on. This database is an international intelligence communication system maintained by FAO, which updates quarterly and increases by 0.13 million records annually, with large data amount.
基金supported by the National Natural Science of the Foundation of China(Grant Nos.42075079,42105128,42275091)the Central Regional Weather Modification Capacity Building Project of the China Meteorological Administration,Weather Modification Research Experiment in the Catchment Area of Danjiangkou Reservoir(Grant No.ZQC-H22255)the Opening Foundation of Key Laboratory of Smart Earth(Grant No.KF2023YB03-02).
文摘Cloud detection is critical for satellite remote sensing algorithms and downstream applications.This study evaluates the official cloud mask(CLM)product of the Advanced Geostationary Radiation Imager(AGRI)on the Fengyun-4A(FY-4A)satellite using two years of data from the Cloud Aerosol Lidar with Orthogonal Polarization(CALIOP)over China.The evaluation reveals moderate performance,with an accuracy(ACC)of 79%for daytime and 80%for nighttime.However,the FY-4A CLM struggles with high false-positive rates(FPRs of 35%during the day and 23%at night),often misclassifying clear skies as clouds.To address this issue,a random forest(RF)-based cloud detection algorithm is developed,using collocated CALIOP observations as reference labels for model development and validation.The models are divided into daytime and nighttime categories based on the solar zenith angle.Feature engineering demonstrates that adding temporal information,spatial texture information,and dynamic surface features reduces FPR values significantly.The ACC of the daytime(nighttime)model improved by up to 13.6%(10.2%).The proposed RF models achieve exceptional cloud detection,with ACC and true-positive rates(TPR)exceeding 90%with an FPR below 10%for both day and night,outperforming the FY-4A CLM.Compared to MODIS and FY-4A CLM,the RF-based models demonstrate superior accuracy in identifying clouds under challenging conditions such as dust,snow,and high pollution.This study offers a promising alternative to enhance cloud detection for the FY-4A imager.
文摘静止卫星具有可连续高频率观测的特点,被广泛应用于数值天气预报中,以获得更精细、更真实的数值模式初始条件。基于WRF框架的陕西省区域数值模式系统,针对2022年7月陕西一次强降水过程,利用三维变分直接同化方法,协同常规观测资料,同化风云四号A星所探测的两个水汽通道辐射率资料。通过设计三组对比试验:(1)不同化任何资料的控制试验(CTRL);(2)仅同化常规观测资料的试验(CONV);(3)同化常规观测与AGRI水汽通道的试验(AGRI),系统评估了晴空区FY-4A卫星两个水汽通道辐射资料同化对降水预报的改进效果。结果表明,经过一系列的质量控制和偏差订正,通道9(10)同化前观测亮温和背景场亮温差值(observation minus background,简称OMB)的平均值由0.76(0.78)K减小到0.04(-0.02)K,同化后观测亮温和分析场亮温差值(observation minus analysis,简称OMA)的平均值进一步缩小为0.01(0.01)K;通道9(10)同化前观测亮温和背景场场亮温差OMB标准差为0.83(0.84)K,同化后观测亮温和分析场亮温差OMA的标准差为0.43(0.49)K,说明同化AGRI水汽通道辐射资料改善了模式的初始场。通过协同同化FY-4A AGRI水汽通道辐射率资料与常规观测资料,显著改善了降水预报性能,常规观测资料通过调整风场优化了天气系统配置,使降水落区与实况更加接近,AGRI水汽通道资料同化修正了中高层比湿场,使强降水中心的强度预报误差降低20%。
文摘AGRIS (The Agricultural Sciences and Technology) is a booklist-style international agricultural database which is established by the international agricultural technology information system subordinate to FAO. It embodies continued publications, documents, corpuses, books, technology reports, patents, maps, meeting papers, and other literatures, which are collected by 135 countries and regions, 146 branches of AGRIS, and 22 international organizations.
文摘AGRIS(The Agricultural Sciences and Technology)is a booklist-style international agricultural database which is established by the international agricultural technology information system subordinate to FAO.It embodies continued publications,documents,corpuses.
