While steady improvements have been achieved for the track forecasts of typhoons,there has been a lack of improvement for intensity forecasts.One challenge for intensity forecasts is to capture the rapid intensificati...While steady improvements have been achieved for the track forecasts of typhoons,there has been a lack of improvement for intensity forecasts.One challenge for intensity forecasts is to capture the rapid intensification(RI),whose nonlinear characteristics impose great difficulties for numerical models.The ensemble sensitivity analysis(ESA)method is used here to analyze the initial conditions that contribute to typhoon intensity forecasts,especially with RI.Six RI processes from five typhoons(Chaba,Haima,Meranti,Sarika,and Songda)in 2016,are applied with ESA,which also gives a composite initial condition that favors subsequent RI.Results from individual cases have generally similar patterns of ESA,but with different magnitudes,when various cumulus parameterization schemes are applied.To draw the initial conditions with statistical significance,sample-mean azimuthal components of ESA are obtained.Results of the composite sensitivity show that typhoons that experience RI in 24 h favor enhanced primary circulation from low to high levels,intensified secondary circulation with increased radial inflow at lower levels and increased radial outflow at upper levels,a prominent warm core at around 300 hPa,and increased humidity at low levels.As the forecast lead time increases,the patterns of ESA are retained,while the sensitivity magnitudes decay.Given the general and quantitative composite sensitivity along with associated uncertainties for different cumulus parameterization schemes,appropriate sampling of the composite sensitivity in numerical models could be beneficial to capturing the RI and improving the forecasting of typhoon intensity.展开更多
This study examines the effectiveness of adaptive observation experiments using the ensemble transformation sensitivity(ETS) method to improve precipitation forecasts during heavy rainfall events in South China and th...This study examines the effectiveness of adaptive observation experiments using the ensemble transformation sensitivity(ETS) method to improve precipitation forecasts during heavy rainfall events in South China and the Sichuan Basin. High-resolution numerical models are employed to simulate adaptive observations. By identifying the sensitive areas of key weather system positions 42 hours before heavy rainfall events, the adaptive observations improve the prediction of jet streams, strong winds, and shear lines, which are essential for accurate heavy rainfall forecasting. This improvement is reflected in both the precipitation structure and location accuracy within the verification region. In South China, targeted observations enhance rainfall predictions by improving water vapor transport. In the Sichuan Basin, adaptive observations refine water vapor transport and adjust vortex dynamics. This research highlights the importance of accurately predicting shear lines and jet streams for forecasting heavy rainfall in these areas. Overall, this study found that adaptive observation enhances the precipitation forecast skills of the structure and location for heavy rainfall in South China and the Sichuan Basin, emphasizing their potential utility in operational numerical weather prediction.展开更多
A heavy rainstorm occurred in Henan Province,China,between 19 and 21 July,2021,with a record-breaking 201.9 mm of precipitation in 1 h.To explore the key factors that led to forecasting errors for this extreme rainsto...A heavy rainstorm occurred in Henan Province,China,between 19 and 21 July,2021,with a record-breaking 201.9 mm of precipitation in 1 h.To explore the key factors that led to forecasting errors for this extreme rainstorm,as well as the dominant contributor affecting its predictability,we employed the Global/Regional Assimilation and Prediction System-Regional Ensemble Prediction System(GRAPES-REPS)to investigate the impact of the upper tropospheric cold vortex,middle-low vortex,and low-level jet on predictability and forecasting errors.The results showed that heavy rainfall was influenced by the following stable atmospheric circulation systems:subtropical highs,continental highs,and Typhoon In-Fa.Severe convection was caused by abundant water vapor,orographic uplift,and mesoscale vortices.Multiscale weather systems contributed to maintaining extreme rainfall in Henan for a long duration.The prediction ability of the optimal member of GRAPES-REPS was attributed to effective prediction of the intensity and evolution characteristics of the upper tropospheric cold vortex,middle-low vortex,and low-level jet.Conversely,the prediction deviation of unstable and dynamic conditions in the lower level of the worst member led to a decline in the forecast quality of rainfall intensity and its rainfall area.This indicates that heavy rainfall was strongly related to the short-wave throughput,upper tropospheric cold vortex,vortex,and boundary layer jet.Moreover,we observed severe uncertainty in GRAPES-REPS forecasts for rainfall caused by strong convection,whereas the predictability of rainfall caused by topography was high.Compared with the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System,GRAPES-REPS exhibits a better forecast ability for heavy rainfall,with some ensemble members able to better predict extreme precipitation.展开更多
基金supported by the National Natural Science Foundation of China[grant numbers 42192553 and 41922036]the Fundamental Research Funds for the Central Universities–Cemac“GeoX”Interdisciplinary Program[grant number 020714380207]。
文摘While steady improvements have been achieved for the track forecasts of typhoons,there has been a lack of improvement for intensity forecasts.One challenge for intensity forecasts is to capture the rapid intensification(RI),whose nonlinear characteristics impose great difficulties for numerical models.The ensemble sensitivity analysis(ESA)method is used here to analyze the initial conditions that contribute to typhoon intensity forecasts,especially with RI.Six RI processes from five typhoons(Chaba,Haima,Meranti,Sarika,and Songda)in 2016,are applied with ESA,which also gives a composite initial condition that favors subsequent RI.Results from individual cases have generally similar patterns of ESA,but with different magnitudes,when various cumulus parameterization schemes are applied.To draw the initial conditions with statistical significance,sample-mean azimuthal components of ESA are obtained.Results of the composite sensitivity show that typhoons that experience RI in 24 h favor enhanced primary circulation from low to high levels,intensified secondary circulation with increased radial inflow at lower levels and increased radial outflow at upper levels,a prominent warm core at around 300 hPa,and increased humidity at low levels.As the forecast lead time increases,the patterns of ESA are retained,while the sensitivity magnitudes decay.Given the general and quantitative composite sensitivity along with associated uncertainties for different cumulus parameterization schemes,appropriate sampling of the composite sensitivity in numerical models could be beneficial to capturing the RI and improving the forecasting of typhoon intensity.
基金jointly supported by the Guangdong Province University Student Innovation and Entrepreneurship Project (580520049)the Guangdong Ocean University Scientific Research Startup Fund (R20021)the Key Laboratory of Plateau and Basin Rainstorm and Drought Disasters in Sichuan Province Open Research Fund (SZKT201902)。
文摘This study examines the effectiveness of adaptive observation experiments using the ensemble transformation sensitivity(ETS) method to improve precipitation forecasts during heavy rainfall events in South China and the Sichuan Basin. High-resolution numerical models are employed to simulate adaptive observations. By identifying the sensitive areas of key weather system positions 42 hours before heavy rainfall events, the adaptive observations improve the prediction of jet streams, strong winds, and shear lines, which are essential for accurate heavy rainfall forecasting. This improvement is reflected in both the precipitation structure and location accuracy within the verification region. In South China, targeted observations enhance rainfall predictions by improving water vapor transport. In the Sichuan Basin, adaptive observations refine water vapor transport and adjust vortex dynamics. This research highlights the importance of accurately predicting shear lines and jet streams for forecasting heavy rainfall in these areas. Overall, this study found that adaptive observation enhances the precipitation forecast skills of the structure and location for heavy rainfall in South China and the Sichuan Basin, emphasizing their potential utility in operational numerical weather prediction.
基金supported by the National Natural Science Foundation of China(Grant No.U2242213)the National Key R&D Program of China(No.2017YFC1502000).
文摘A heavy rainstorm occurred in Henan Province,China,between 19 and 21 July,2021,with a record-breaking 201.9 mm of precipitation in 1 h.To explore the key factors that led to forecasting errors for this extreme rainstorm,as well as the dominant contributor affecting its predictability,we employed the Global/Regional Assimilation and Prediction System-Regional Ensemble Prediction System(GRAPES-REPS)to investigate the impact of the upper tropospheric cold vortex,middle-low vortex,and low-level jet on predictability and forecasting errors.The results showed that heavy rainfall was influenced by the following stable atmospheric circulation systems:subtropical highs,continental highs,and Typhoon In-Fa.Severe convection was caused by abundant water vapor,orographic uplift,and mesoscale vortices.Multiscale weather systems contributed to maintaining extreme rainfall in Henan for a long duration.The prediction ability of the optimal member of GRAPES-REPS was attributed to effective prediction of the intensity and evolution characteristics of the upper tropospheric cold vortex,middle-low vortex,and low-level jet.Conversely,the prediction deviation of unstable and dynamic conditions in the lower level of the worst member led to a decline in the forecast quality of rainfall intensity and its rainfall area.This indicates that heavy rainfall was strongly related to the short-wave throughput,upper tropospheric cold vortex,vortex,and boundary layer jet.Moreover,we observed severe uncertainty in GRAPES-REPS forecasts for rainfall caused by strong convection,whereas the predictability of rainfall caused by topography was high.Compared with the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System,GRAPES-REPS exhibits a better forecast ability for heavy rainfall,with some ensemble members able to better predict extreme precipitation.
