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
The infrared channels of the FY-4B advanced geosynchronous radiation imagers(AGRI) play a crucial role in temperature and humidity analyses for mesoscale numerical weather prediction, particularly in enhancing the ini...The infrared channels of the FY-4B advanced geosynchronous radiation imagers(AGRI) play a crucial role in temperature and humidity analyses for mesoscale numerical weather prediction, particularly in enhancing the initial field quality and the forecasting accuracy of the model. This study assimilated FY-4B AGRI data into the CMA-MESO model and analyzed the bias characteristics and correction methods. Analysis of the AGRI data revealed a clear diurnal variation in the bias, which was positively correlated with the solar elevation angle. However, the diurnal variation in the bias lagged behind the solar elevation angle, likely owing to temperature changes and delayed instrument responses resulting from solar radiation. To address this issue, we propose a correction method that utilizes the solar elevation angle after an optimal time shift. Using the time-shifted solar elevation angle as a predictor effectively reduces the diurnal variation in bias and significantly improves the correction effect. This approach provides theoretical support for the assimilation of FY-4B AGRI data into mesoscale numerical weather predictions, thereby enhancing the reliability of the assimilation results.展开更多
This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager(AGRI)radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West...This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager(AGRI)radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West Pacific Ocean using the 3DVar data assimilation(DA)method along with the WRF model.A channel-sensitive cloud detection scheme based on the particle filter(PF)algorithm is developed and examined against a cloud detection scheme using the multivariate and minimum residual(MMR)algorithm and another traditional cloud mask–dependent cloud detection scheme.Results show that both channel-sensitive cloud detection schemes are effective,while the PF scheme is able to reserve more pixels than the MMR scheme for the same channel.In general,the added value of AGRI radiances is confirmed when comparing with the control experiment without AGRI radiances.Moreover,it is found that the analysis fields of the PF experiment are mostly improved in terms of better depicting the typhoon,including the temperature,moisture,and dynamical conditions.The typhoon track forecast skill is improved with AGRI radiance DA,which could be explained by better simulating the upper trough.The impact of assimilating AGRI radiances on typhoon intensity forecasts is small.On the other hand,improved rainfall forecasts from AGRI DA experiments are found along with reduced errors for both the thermodynamic and moisture fields,albeit the improvements are limited.展开更多
Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land-atmosphere interaction.In this study,Fengyun-4A(FY-4A)Advanced Geostationary R...Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land-atmosphere interaction.In this study,Fengyun-4A(FY-4A)Advanced Geostationary Radiation Imager(AGRI)satellite data and the China Land Data Assimilation System(CLDAS)meteorological forcing dataset CLDAS-V2.0 were applied for the retrieval of broadband albedo,land surface temperature(LST),radiation flux components,and turbulent heat fluxes over the Tibetan Plateau(TP).The FY-4A/AGRI and CLDAS-V2.0 data from 12 March 2018 to 30 April 2018 were first used to estimate the hourly turbulent heat fluxes over the TP.The time series data of in-situ measurements from the Tibetan Observation and Research Platform were divided into two halves-one for developing retrieval algorithms for broadband albedo and LST based on FY-4A,and the other for the cross validation.Results show the root-mean-square errors(RMSEs)of the FY-4A retrieved broadband albedo and LST were 0.0309 and 3.85 K,respectively,which verifies the applicability of the retrieval method.The RMSEs of the downwelling/upwelling shortwave radiation flux and downwelling/upwelling longwave radiation flux were 138.87/32.78 W m^(−2)and 51.55/17.92 W m^(−2),respectively,and the RMSEs of net radiation flux,sensible heat flux,and latent heat flux were 58.88 W m^(−2),82.56 W m^(−2)and 72.46 W m^(−2),respectively.The spatial distributions and diurnal variations of LST and turbulent heat fluxes were further analyzed in detail.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.
基金National Key Research and Development Program of China (2022YFC3004004)National Natural Science Foundation of China (42075155,12241104)National Natural Science Foundation of China Joint Fund (U2342213)。
文摘The infrared channels of the FY-4B advanced geosynchronous radiation imagers(AGRI) play a crucial role in temperature and humidity analyses for mesoscale numerical weather prediction, particularly in enhancing the initial field quality and the forecasting accuracy of the model. This study assimilated FY-4B AGRI data into the CMA-MESO model and analyzed the bias characteristics and correction methods. Analysis of the AGRI data revealed a clear diurnal variation in the bias, which was positively correlated with the solar elevation angle. However, the diurnal variation in the bias lagged behind the solar elevation angle, likely owing to temperature changes and delayed instrument responses resulting from solar radiation. To address this issue, we propose a correction method that utilizes the solar elevation angle after an optimal time shift. Using the time-shifted solar elevation angle as a predictor effectively reduces the diurnal variation in bias and significantly improves the correction effect. This approach provides theoretical support for the assimilation of FY-4B AGRI data into mesoscale numerical weather predictions, thereby enhancing the reliability of the assimilation results.
基金primarily supported by the Chinese National Natural Science Foundation of China(Grant No. G42192553)Open Fund of Fujian Key Laboratory ofSevere Weather and Key Laboratory of Straits Severe Weather(Grant No. 2023KFKT03)+6 种基金the Open Project Fund of China Meteorological Administration Basin Heavy Rainfall Key Laboratory(Grant No. 2023BHR-Y20)the Open Fund of the State Key Laboratory of Remote Sensing Science (Grant No. OFSLRSS202321)the Program of Shanghai Academic/Technology Research Leader(Grant No. 21XD1404500)the Shanghai Typhoon Research Foundation (Grant No. TFJJ202107)the Chinese National Natural Science Foundation of China (Grant No. G41805016)the National Meteorological Center Foundation (Grant No. FY-APP-2021.0207)the High Performance Computing Center of Nanjing University of Information Science&Technology for their support of this work
文摘This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager(AGRI)radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West Pacific Ocean using the 3DVar data assimilation(DA)method along with the WRF model.A channel-sensitive cloud detection scheme based on the particle filter(PF)algorithm is developed and examined against a cloud detection scheme using the multivariate and minimum residual(MMR)algorithm and another traditional cloud mask–dependent cloud detection scheme.Results show that both channel-sensitive cloud detection schemes are effective,while the PF scheme is able to reserve more pixels than the MMR scheme for the same channel.In general,the added value of AGRI radiances is confirmed when comparing with the control experiment without AGRI radiances.Moreover,it is found that the analysis fields of the PF experiment are mostly improved in terms of better depicting the typhoon,including the temperature,moisture,and dynamical conditions.The typhoon track forecast skill is improved with AGRI radiance DA,which could be explained by better simulating the upper trough.The impact of assimilating AGRI radiances on typhoon intensity forecasts is small.On the other hand,improved rainfall forecasts from AGRI DA experiments are found along with reduced errors for both the thermodynamic and moisture fields,albeit the improvements are limited.
基金This research was jointly funded by the Second Tibetan Plateau Scientific Expedition and Research Pro-gram(Grant No.2019QZKK010305)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA20060101)+2 种基金the National Natural Science Foundation of China(Grant Nos.41875031,91837208,41522501 and 41275028)the Chinese Academy of Sciences Basic Frontier Sci-ence Research Program from 0 to 1 Original Innovation Project(Grant No.ZDBS-LY-DQC005-01)the Chinese Academy of Sciences(Grant No.QYZDJ-SSW-DQC019).
文摘Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land-atmosphere interaction.In this study,Fengyun-4A(FY-4A)Advanced Geostationary Radiation Imager(AGRI)satellite data and the China Land Data Assimilation System(CLDAS)meteorological forcing dataset CLDAS-V2.0 were applied for the retrieval of broadband albedo,land surface temperature(LST),radiation flux components,and turbulent heat fluxes over the Tibetan Plateau(TP).The FY-4A/AGRI and CLDAS-V2.0 data from 12 March 2018 to 30 April 2018 were first used to estimate the hourly turbulent heat fluxes over the TP.The time series data of in-situ measurements from the Tibetan Observation and Research Platform were divided into two halves-one for developing retrieval algorithms for broadband albedo and LST based on FY-4A,and the other for the cross validation.Results show the root-mean-square errors(RMSEs)of the FY-4A retrieved broadband albedo and LST were 0.0309 and 3.85 K,respectively,which verifies the applicability of the retrieval method.The RMSEs of the downwelling/upwelling shortwave radiation flux and downwelling/upwelling longwave radiation flux were 138.87/32.78 W m^(−2)and 51.55/17.92 W m^(−2),respectively,and the RMSEs of net radiation flux,sensible heat flux,and latent heat flux were 58.88 W m^(−2),82.56 W m^(−2)and 72.46 W m^(−2),respectively.The spatial distributions and diurnal variations of LST and turbulent heat fluxes were further analyzed in detail.
