Journal of Tropical Meteorology takes as its prime commitment the integration of theoretic and applied study in the field of tropical meteorology and the presentation of advanced techniques and successful experience o...Journal of Tropical Meteorology takes as its prime commitment the integration of theoretic and applied study in the field of tropical meteorology and the presentation of advanced techniques and successful experience of weather forecasting for the tropics, with particular reference to air-sea and mid- and low- latitude- interactions, low-frequency oscillations and teleconnections, low-latitude general circulation anomalies and governing mechanisms, effects of tropical general circulation on global weather and climate, monsoon dynamics and kinetics of tropical cyclones.展开更多
This study investigates multi-model ensemble forecasts of track and intensity of tropical cyclones over the western Pacific, based on forecast outputs from the China Meteorological Administration, European Centre for ...This study investigates multi-model ensemble forecasts of track and intensity of tropical cyclones over the western Pacific, based on forecast outputs from the China Meteorological Administration, European Centre for Medium-Range Weather Forecasts, Japan Meteorological Agency and National Centers for Environmental Prediction in the THORPEX Interactive Grand Global Ensemble(TIGGE) datasets. The multi-model ensemble schemes, namely the bias-removed ensemble mean(BREM) and superensemble(SUP), are compared with the ensemble mean(EMN) and single-model forecasts. Moreover, a new model bias estimation scheme is investigated and applied to the BREM and SUP schemes. The results showed that, compared with single-model forecasts and EMN, the multi-model ensembles of the BREM and SUP schemes can have smaller errors in most cases. However, there were also circumstances where BREM was less skillful than EMN, indicating that using a time-averaged error as model bias is not optimal. A new model bias estimation scheme of the biweight mean is introduced. Through minimizing the negative influence of singular errors, this scheme can obtain a more accurate model bias estimation and improve the BREM forecast skill. The application of the biweight mean in the bias calculation of SUP also resulted in improved skill. The results indicate that the modification of multi-model ensemble schemes through this bias estimation method is feasible.展开更多
A hybrid GSI （Grid-point Statistical Interpolation）-ETKF （Ensemble Transform Kalman Filter） data assimila- tion system has been recently developed for the WRF （Weather Research and Forecasting） model and tested ...A hybrid GSI （Grid-point Statistical Interpolation）-ETKF （Ensemble Transform Kalman Filter） data assimila- tion system has been recently developed for the WRF （Weather Research and Forecasting） model and tested with simu- lated observations for tropical cyclone （TC） forecast. This system is based on the existing GSI but with ensemble back- ground information incorporated. As a follow-up, this work extends the new system to assimilate real observations to further understand the hybrid scheme. As a first effort to explore the system with real observations, relatively coarse grid resolution （27 km） is used. A case study of typhoon Muifa （2011） is performed to assimilate real observations in- cluding conventional in-situ and satellite data. The hybrid system with flow-dependent ensemble eovariance shows sig- nificant improvements with respect to track forecast compared to the standard GSI system which in theory is three di- mensional variational analysis （3DVAR）. By comparing the analyses, analysis increments and forecasts, the hybrid sys- tem is found to be potentially able to recognize the existence of TC vortex, adjust its position systematically, better de- scribe the asymmetric structure of typhoon Muifa and maintain the dynamic and thermodynamic balance in typhoon ini- tial field. In addition, a cold-start hybrid approach by using the global ensembles to provide flow-dependent error is test- ed and similar results are revealed with those from cycled GSI-ETKF approach.展开更多
By using 1958-2001 NOAA extended reconstructed sea surface temperature(SST) data, ERA40 reanalysis soil moisture data and precipitation data of 444 stations in China(east of 100°E), the possible relationships amo...By using 1958-2001 NOAA extended reconstructed sea surface temperature(SST) data, ERA40 reanalysis soil moisture data and precipitation data of 444 stations in China(east of 100°E), the possible relationships among South China Sea(SCS) SST anomaly(SSTA), soil moisture anomalies(SMA) and summer precipitation in eastern China as well as their possible physical processes are investigated. Results show that the SSTA of SCS bears an evidently negative correlation with spring soil moisture in the east part of Southwest China. More(less) precipitation happens in the Yangtze River basin and less(more) in the Southeast China in summer when the SSTA of SCS is higher(lower) than normal and the soil in the east part of Southwest China is dry(wet) in spring. Further analysis shows that when the SSTA of SCS is high(low), the southwesterly wind at low level is weak(strong), decreasing(increasing) the water vapor transport in South China, resulting in reduced(increased) spring precipitation in the east part of Southwest China and more(less) soil moisture in spring. Through the evaporation feedback mechanism, the dry(wet) soil makes the surface temperature higher(lower) in summer, causing the westward extension(eastward retreat) of the West Pacific Subtropical High, eventually leading to the summer precipitation anomalies.展开更多
文摘Journal of Tropical Meteorology takes as its prime commitment the integration of theoretic and applied study in the field of tropical meteorology and the presentation of advanced techniques and successful experience of weather forecasting for the tropics, with particular reference to air-sea and mid- and low- latitude- interactions, low-frequency oscillations and teleconnections, low-latitude general circulation anomalies and governing mechanisms, effects of tropical general circulation on global weather and climate, monsoon dynamics and kinetics of tropical cyclones.
基金Special Research Program for Public Welfare(Meteorology)of China(GYHY200906009,GYHY201006015,GYHY200906007)National Natural Science Foundation of China(4107503541475044)
文摘This study investigates multi-model ensemble forecasts of track and intensity of tropical cyclones over the western Pacific, based on forecast outputs from the China Meteorological Administration, European Centre for Medium-Range Weather Forecasts, Japan Meteorological Agency and National Centers for Environmental Prediction in the THORPEX Interactive Grand Global Ensemble(TIGGE) datasets. The multi-model ensemble schemes, namely the bias-removed ensemble mean(BREM) and superensemble(SUP), are compared with the ensemble mean(EMN) and single-model forecasts. Moreover, a new model bias estimation scheme is investigated and applied to the BREM and SUP schemes. The results showed that, compared with single-model forecasts and EMN, the multi-model ensembles of the BREM and SUP schemes can have smaller errors in most cases. However, there were also circumstances where BREM was less skillful than EMN, indicating that using a time-averaged error as model bias is not optimal. A new model bias estimation scheme of the biweight mean is introduced. Through minimizing the negative influence of singular errors, this scheme can obtain a more accurate model bias estimation and improve the BREM forecast skill. The application of the biweight mean in the bias calculation of SUP also resulted in improved skill. The results indicate that the modification of multi-model ensemble schemes through this bias estimation method is feasible.
基金Project for Public Welfare(Meteorology)of China(GYHY201206006)973 Program(2013CB430305)+2 种基金National Natural Science Foundation of China(41575107)Project of Shanghai Meteorological Bureau(YJ201401)Key Project of Science and Technology Commission of Shanghai Municipality(13231203300)
文摘A hybrid GSI （Grid-point Statistical Interpolation）-ETKF （Ensemble Transform Kalman Filter） data assimila- tion system has been recently developed for the WRF （Weather Research and Forecasting） model and tested with simu- lated observations for tropical cyclone （TC） forecast. This system is based on the existing GSI but with ensemble back- ground information incorporated. As a follow-up, this work extends the new system to assimilate real observations to further understand the hybrid scheme. As a first effort to explore the system with real observations, relatively coarse grid resolution （27 km） is used. A case study of typhoon Muifa （2011） is performed to assimilate real observations in- cluding conventional in-situ and satellite data. The hybrid system with flow-dependent ensemble eovariance shows sig- nificant improvements with respect to track forecast compared to the standard GSI system which in theory is three di- mensional variational analysis （3DVAR）. By comparing the analyses, analysis increments and forecasts, the hybrid sys- tem is found to be potentially able to recognize the existence of TC vortex, adjust its position systematically, better de- scribe the asymmetric structure of typhoon Muifa and maintain the dynamic and thermodynamic balance in typhoon ini- tial field. In addition, a cold-start hybrid approach by using the global ensembles to provide flow-dependent error is test- ed and similar results are revealed with those from cycled GSI-ETKF approach.
基金National Science Foundation of China(41230422)Special Funds for Public Welfare of China(GYHY 201206017)+3 种基金NCET ProgramNatural Science Foundation of Jiangsu Province of China(BK2004001)Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)Research Innovation Program for College Graduates of Jiangsu Province(CXZZ13_0499)
文摘By using 1958-2001 NOAA extended reconstructed sea surface temperature(SST) data, ERA40 reanalysis soil moisture data and precipitation data of 444 stations in China(east of 100°E), the possible relationships among South China Sea(SCS) SST anomaly(SSTA), soil moisture anomalies(SMA) and summer precipitation in eastern China as well as their possible physical processes are investigated. Results show that the SSTA of SCS bears an evidently negative correlation with spring soil moisture in the east part of Southwest China. More(less) precipitation happens in the Yangtze River basin and less(more) in the Southeast China in summer when the SSTA of SCS is higher(lower) than normal and the soil in the east part of Southwest China is dry(wet) in spring. Further analysis shows that when the SSTA of SCS is high(low), the southwesterly wind at low level is weak(strong), decreasing(increasing) the water vapor transport in South China, resulting in reduced(increased) spring precipitation in the east part of Southwest China and more(less) soil moisture in spring. Through the evaporation feedback mechanism, the dry(wet) soil makes the surface temperature higher(lower) in summer, causing the westward extension(eastward retreat) of the West Pacific Subtropical High, eventually leading to the summer precipitation anomalies.
