Wind gusts are common environmental hazards that can damage buildings,bridges,aircraft,and cruise ships and interrupt electric power distribution,air traffic,waterway transport and port operations.Accurately predictin...Wind gusts are common environmental hazards that can damage buildings,bridges,aircraft,and cruise ships and interrupt electric power distribution,air traffic,waterway transport and port operations.Accurately predicting peak wind gusts in numerical models is essential for saving lives and preventing economic losses.This study investigates the climatology of peak wind gusts and their associated gust factors(GFs)using observations in the coastal and open ocean of the northern South China Sea(NSCS),where severe gust-producing weather occurs throughout the year.The stratified climatology demonstrates that the peak wind gust and GF vary with seasons and particularly with weather types.Based on the inversely proportional relationship between the GF and mean wind speed(MWS),a variety of GF models are constructed through least squares regression analysis.Peak gust speed(PGS)forecasts are obtained through the GF models by multiplying the GFs by observed wind speeds rather than forecasted wind speeds.The errors are thus entirely due to the representation of the GF models.The GF models are improved with weather-adaptive GFs,as evaluated by the stratified MWS.Nevertheless,these weather-adaptive GF models show negative bias for predicting stronger PGSs due to insufficient data representation of the extreme wind gusts.The evaluation of the above models provides insight into maximizing the performance of GF models.This study further proposes a stratified process for forecasting peak wind gusts for routine operations.展开更多
This paper presents a new correction method, "instant correction method(ICM)", to improve the accuracy of numerical prediction products(NPP) and provide weather variables at grid cells. The ICM makes use of ...This paper presents a new correction method, "instant correction method(ICM)", to improve the accuracy of numerical prediction products(NPP) and provide weather variables at grid cells. The ICM makes use of the continuity in time of the forecast errors at different forecast times to improve the accuracy of large scale NPP. To apply the ICM in China, an ensemble correction scheme is designed to correct the T213 NPP(the most popular NPP in China) through different statistical methods. The corrected T213 NPP(ICM T213 NPP) are evaluated by four popular indices: Correlation coefficient, climate anomalies correlation coefficient, root-mean-square-errors(RMSE), and confidence intervals(CI). The results show that the ICM T213 NPP are more accurate than the original T213 NPP in both the training period(2003–2008) and the validation period(2009–2010). Applications in China over the past three years indicate that the ICM is simple, fast, and reliable. Because of its low computing cost, end users in need of more accurate short-range weather forecasts around China can benefit greatly from the method.展开更多
基金National Key R&D Program of China(2023YFC3008002)National Natural Science Foundation of China(41805035)+1 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515011288)Key Innovation Team of China Meteorological Administration(CMA2023ZD08)。
文摘Wind gusts are common environmental hazards that can damage buildings,bridges,aircraft,and cruise ships and interrupt electric power distribution,air traffic,waterway transport and port operations.Accurately predicting peak wind gusts in numerical models is essential for saving lives and preventing economic losses.This study investigates the climatology of peak wind gusts and their associated gust factors(GFs)using observations in the coastal and open ocean of the northern South China Sea(NSCS),where severe gust-producing weather occurs throughout the year.The stratified climatology demonstrates that the peak wind gust and GF vary with seasons and particularly with weather types.Based on the inversely proportional relationship between the GF and mean wind speed(MWS),a variety of GF models are constructed through least squares regression analysis.Peak gust speed(PGS)forecasts are obtained through the GF models by multiplying the GFs by observed wind speeds rather than forecasted wind speeds.The errors are thus entirely due to the representation of the GF models.The GF models are improved with weather-adaptive GFs,as evaluated by the stratified MWS.Nevertheless,these weather-adaptive GF models show negative bias for predicting stronger PGSs due to insufficient data representation of the extreme wind gusts.The evaluation of the above models provides insight into maximizing the performance of GF models.This study further proposes a stratified process for forecasting peak wind gusts for routine operations.
基金partially supported by the National Natural Science Foundation of China(Grant No.91125010)
文摘This paper presents a new correction method, "instant correction method(ICM)", to improve the accuracy of numerical prediction products(NPP) and provide weather variables at grid cells. The ICM makes use of the continuity in time of the forecast errors at different forecast times to improve the accuracy of large scale NPP. To apply the ICM in China, an ensemble correction scheme is designed to correct the T213 NPP(the most popular NPP in China) through different statistical methods. The corrected T213 NPP(ICM T213 NPP) are evaluated by four popular indices: Correlation coefficient, climate anomalies correlation coefficient, root-mean-square-errors(RMSE), and confidence intervals(CI). The results show that the ICM T213 NPP are more accurate than the original T213 NPP in both the training period(2003–2008) and the validation period(2009–2010). Applications in China over the past three years indicate that the ICM is simple, fast, and reliable. Because of its low computing cost, end users in need of more accurate short-range weather forecasts around China can benefit greatly from the method.
