Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors.The traditional precipitation det...Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors.The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally,without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the all-sky approach.In this study,the 3D precipitation detection method is adopted to assimilate Microwave Temperature Sounder-2(MWTS-Ⅱ)onboard the Fengyun-3D,which can dynamically detect the channels above precipitating clouds by considering the near-real-time cloud parameters.Cycling data assimilation and forecasting experiments for Typhoons Lekima(2019)and Mitag(2019)are carried out.Compared with the control experiment,the quantity of assimilated data with the 3D precipitation detection increases by approximately 23%.The quality of the additional MWTS-Ⅱradiance data is close to the clear-sky data.The case studies show that the average root-mean-square errors(RMSE)of prognostic variables are reduced by 1.7%in the upper troposphere,leading to an average reduction of4.53%in typhoon track forecasts.The detailed diagnoses of Typhoon Lekima(2019)further show that the additional MWTS-Ⅱradiances brought by the 3D precipitation detection facilitate portraying a more reasonable circulation situation,thus providing more precise structures.This paper preliminarily proves that 3D precipitation detection has potential added value for increasing satellite data utilization and improving typhoon forecasts.展开更多
Prediction skill for the seasonal tropical cyclone(TC)activity in the Northern Hemisphere is investigated using the coupled climate forecast system(version 1.0)of Nanjing University of Information Science and Technolo...Prediction skill for the seasonal tropical cyclone(TC)activity in the Northern Hemisphere is investigated using the coupled climate forecast system(version 1.0)of Nanjing University of Information Science and Technology(NUISTCFS1.0).This assessment is based on the seven-month(May to November)hindcasts consisting of nine ensemble members during 1982–2019.The predictions are compared with the Japanese 55-year Reanalysis and observed tropical storms in the Northern Hemisphere.The results show that the overall distributions of the TC genesis and track densities in model hindcasts agree well with the observations,although the seasonal mean TC frequency and accumulated cyclone energy(ACE)are underestimated in all basins due to the low resolution(T106)of the atmospheric component in the model.NUIST-CFS1.0 closely predicts the interannual variations of TC frequency and ACE in the North Atlantic(NA)and eastern North Pacific(ENP),which have a good relationship with indexes based on the sea surface temperature.In the western North Pacific(WNP),NUIST-CFS1.0 can closely capture ACE,which is significantly correlated with the El Ni?o–Southern Oscillation(ENSO),while it has difficulty forecasting the interannual variation of TC frequency in this area.When the WNP is further divided into eastern and western subregions,the model displays improved TC activity forecasting ability.Additionally,it is found that biases in predicted TC genesis locations lead to inaccurately represented TC–environment relationships,which may affect the capability of the model in reproducing the interannual variations of TC activity.展开更多
基金jointly sponsored by the National Key Research and Development Program of China(Grant Nos.2018YFC1506701 and 2017YFC1502102)the National Natural Science Foundation of China(Grant No.41675102)。
文摘Precipitation detection is an essential step in radiance assimilation because the uncertainties in precipitation would affect the radiative transfer calculation and observation errors.The traditional precipitation detection method for microwave only detects clouds and precipitation horizontally,without considering the three-dimensional distribution of clouds.Extending precipitation detection from 2D to 3D is expected to bring more useful information to the data assimilation without using the all-sky approach.In this study,the 3D precipitation detection method is adopted to assimilate Microwave Temperature Sounder-2(MWTS-Ⅱ)onboard the Fengyun-3D,which can dynamically detect the channels above precipitating clouds by considering the near-real-time cloud parameters.Cycling data assimilation and forecasting experiments for Typhoons Lekima(2019)and Mitag(2019)are carried out.Compared with the control experiment,the quantity of assimilated data with the 3D precipitation detection increases by approximately 23%.The quality of the additional MWTS-Ⅱradiance data is close to the clear-sky data.The case studies show that the average root-mean-square errors(RMSE)of prognostic variables are reduced by 1.7%in the upper troposphere,leading to an average reduction of4.53%in typhoon track forecasts.The detailed diagnoses of Typhoon Lekima(2019)further show that the additional MWTS-Ⅱradiances brought by the 3D precipitation detection facilitate portraying a more reasonable circulation situation,thus providing more precise structures.This paper preliminarily proves that 3D precipitation detection has potential added value for increasing satellite data utilization and improving typhoon forecasts.
基金supported in part by the National Key Research and Development Program of China(Grant No.2020YFA0608000)the Nature Science Foundation of China(Grant Nos.42005002,42030605,and 42105003)。
文摘Prediction skill for the seasonal tropical cyclone(TC)activity in the Northern Hemisphere is investigated using the coupled climate forecast system(version 1.0)of Nanjing University of Information Science and Technology(NUISTCFS1.0).This assessment is based on the seven-month(May to November)hindcasts consisting of nine ensemble members during 1982–2019.The predictions are compared with the Japanese 55-year Reanalysis and observed tropical storms in the Northern Hemisphere.The results show that the overall distributions of the TC genesis and track densities in model hindcasts agree well with the observations,although the seasonal mean TC frequency and accumulated cyclone energy(ACE)are underestimated in all basins due to the low resolution(T106)of the atmospheric component in the model.NUIST-CFS1.0 closely predicts the interannual variations of TC frequency and ACE in the North Atlantic(NA)and eastern North Pacific(ENP),which have a good relationship with indexes based on the sea surface temperature.In the western North Pacific(WNP),NUIST-CFS1.0 can closely capture ACE,which is significantly correlated with the El Ni?o–Southern Oscillation(ENSO),while it has difficulty forecasting the interannual variation of TC frequency in this area.When the WNP is further divided into eastern and western subregions,the model displays improved TC activity forecasting ability.Additionally,it is found that biases in predicted TC genesis locations lead to inaccurately represented TC–environment relationships,which may affect the capability of the model in reproducing the interannual variations of TC activity.
