This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two win...This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing.At the same time,the wind speed predicted by the EC model is also included for comparative analysis.The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A.The CMA-GD model exhibits a monthly average correlation coefficient of 0.56,root mean square error of 2.72 m s^(-1),and average absolute error of 2.11 m s^(-1).In contrast,the EC model shows a monthly average correlation coefficient of 0.51,root mean square error of 2.83 m s^(-1),and average absolute error of 2.21 m s^(-1).Conversely,in Wind Farm B,the EC model outperforms the CMA-GD model.The CMA-GD model achieves a monthly average correlation coefficient of 0.55,root mean square error of 2.61 m s^(-1),and average absolute error of 2.13 m s^(-1).By contrast,the EC model displays a monthly average correlation coefficient of 0.63,root mean square error of 2.04 m s^(-1),and average absolute error of 1.67 m s^(-1).展开更多
In the present study,the performances of the NWP models on two heavy rainfalls on 20 July and 22 August 2021 over Henan Province were investigated.The impacts of the water vapor transport to the extreme rainfall were ...In the present study,the performances of the NWP models on two heavy rainfalls on 20 July and 22 August 2021 over Henan Province were investigated.The impacts of the water vapor transport to the extreme rainfall were further discussed.The results showed that the regional model system in the Guangzhou Meteorological Service generally showed high scores on the extreme rainfall over Henan.The maximum 24h accumulative rainfall by the 24h forecasts by the CMA-GD reached 556 mm over Henan Province.The 24-h and 48-h Threat Score(TS)of heavy rainfall reached 0.56 and 0.64.The comparisons of the Fraction Skill Score(FSS)verifications of the heavy rainfall by CMA-GD and CMA-TRAMS at the radium of 40km reached 0.96 and 0.87.The water vapor transport to the extreme rainfall showed that the vertically integrated water vapor transport(IVT)of the whole layer before the occurrence of the heavy rainfall exhibited a double-eyes distribution in case 7·20.The north eye over Henan reached the same magnitude of IVT as the typhoon eye(Cempaka)over south China.The IVT over the lower troposphere(<500 hPa)showed an overwhelming magnitude than the upper level,especially in the planetary boundary layer(<700 hPa).More practical technique needs to be developed to improve its performances on the forecasting of extreme rainfall,as well as more experiments need to be conducted to examine the effects of the specific terrain and physical schemes on the extreme rainfall.展开更多
By deriving the discrete equation of the parameterized equation for the New Medium-Range Forecast(NMRF)boundary layer scheme in the GRAPES model,the adjusted discrete equation for temperature is obviously different fr...By deriving the discrete equation of the parameterized equation for the New Medium-Range Forecast(NMRF)boundary layer scheme in the GRAPES model,the adjusted discrete equation for temperature is obviously different from the original equation under the background of hydrostatic equilibrium and adiabatic hypothesis.In the present research,three discrete equations for temperature in the NMRF boundary layer scheme are applied,namely the original(hereafter NMRF),the adjustment(hereafter NMRF-gocp),and the one in the YSU boundary-layer scheme(hereafter NMRF-TZ).The results show that the deviations of height,temperature,U and V wind in the boundary layer in the NMRF-gocp and NMRF-TZ experiments are smaller than those in the NMRF experiment and the deviations in the NMRF-gocp experiment are the smallest.The deviations of humidity are complex for the different forecasting lead time in the three experiments.Moreover,there are obvious diurnal variations of deviations from these variables,where the diurnal variations of deviations from height and temperature are similar and those from U and V wind are also similar.However,the diurnal variation of humidity is relatively complicated.The root means square errors of 2m temperature(T2m)and 10m speed(V10m)from the three experiments show that the error of NMRF-gocp is the smallest and that of NMRF is the biggest.There is also a diurnal variation of T2m and V10m,where T2m has double peaks and V10m has only one peak.Comparison of the discrete equations between NMRF and NMRF-gocp experiments shows that the deviation of temperature is likely to be caused by the calculation of vertical eddy diffusive coefficients of heating,which also leads to the deviations of other elements.展开更多
This study evaluated the forecast skill of CMA-GD 3 km and CMA-GD 1 km with hourly Rapid Update Cycle(RUC)for five monsoon precipitation events in South China from 2018 to 2020,using the fraction skill score(FSS)of th...This study evaluated the forecast skill of CMA-GD 3 km and CMA-GD 1 km with hourly Rapid Update Cycle(RUC)for five monsoon precipitation events in South China from 2018 to 2020,using the fraction skill score(FSS)of the neighborhood spatial verification method.The results revealed that,among the 24-lead-hour forecasts in CMA-GD 3 km,the FSS for the 0.1 mm precipitation threshold increased linearly with the lead time from 3 to 1 hour,while there was no significant improvement in other lead times.For the 5 mm precipitation threshold,the forecast skill was highest for the latest 1-hour lead time,while the FSS showed slight variation between lead times of 24 hours and 8 hours.The FSS for 10 mm and 20 mm precipitation thresholds were similar to that of 5 mm,with the difference that the best score occurred at the 2-hour lead time.Among the 6-lead-hour forecasts in CMA-GD 1 km,the forecasts of the latest 1-hour lead time were the best choices for four precipitation thresholds.When comparing CMA-GD 3 km and CMA-GD 1 km,it was found that CMA-GD 3 km had better skill for forecasts of 0.1 mm and 5 mm precipitation at 2-hour and 1-hour lead times,while CMA-GD 1 km had better skill for all other forecasts,including the forecast of 20 mm precipitation nearly all lead hours(including 3-to 6-hour,and 1-hour lead times).The results suggest that the increased resolution of the model may be beneficial for precipitation forecasts in South China,especially for short-duration heavy precipitation over a longer lead hours.However,the limited sample size of this study calls for further evaluation using more cases to validate the results′generality.展开更多
In real-time operations,the minutely/hourly updated high-resolution rapid refresh(HRRR)system is one of the most expensive numerical weather prediction(NWP)models.Based on a twenty-member HRRR-time-lagged-ensemble(HRR...In real-time operations,the minutely/hourly updated high-resolution rapid refresh(HRRR)system is one of the most expensive numerical weather prediction(NWP)models.Based on a twenty-member HRRR-time-lagged-ensemble(HRRR-TLE)system developed from two real-time convection-permitting HRRR models,CMA-GD(R3)and CMA-SH3,from the China Meteorological Administration(CMA),this study proposes an optimized probability-matching(OPM)technique to improve 0−12 h quantitative precipitation forecasts(QPFs)based on the correlation and error relationships between ensemble forecasts and observations during the training window.Then,a series of sensitivity experiments using different cost functions and optimized ratios was conducted to further improve OPM predictions.The results indicate that:(1)In the HRRR-TLE system,there is no always optimal member in both weak rain and severe rain forecasts,as measured by the equitable threat score(ETS)and bias extent(BE)at four thresholds(1+,5+,10+,and 20+mm h^(-1);e.g.,“1+”means≥1).(2)Compared with the HRRR-TLE system,the QPFs generated by the traditional PM technique showed a notable increase in ETS and a decrease in BE at all of the above thresholds.Compared with the traditional probability-matching method(PM),OPM can generate more skillful forecasts on both spatial representations and rain rates by using the sliding-weight method and optimized ensembles,respectively.(3)In particular,in the 20+mm h^(-1)forecasts,which are often difficult to predict,the ETS of the optimal OPM test,with a 20%optimization ratio and symmetric mean absolute percentage error cost function,increased by 64.6%,and the BE decreased by 5.7%,relative to PM.Moreover,OPM shows good stability in both daytime and nighttime periods.展开更多
基金National Key Research and Development Program of the Ministry of Science(2018YFB1502801)Hubei Provincial Natural Science Foundation(2022CFD017)Innovation and Development Project of China Meteorological Administration(CXFZ2023J044)。
文摘This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing.At the same time,the wind speed predicted by the EC model is also included for comparative analysis.The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A.The CMA-GD model exhibits a monthly average correlation coefficient of 0.56,root mean square error of 2.72 m s^(-1),and average absolute error of 2.11 m s^(-1).In contrast,the EC model shows a monthly average correlation coefficient of 0.51,root mean square error of 2.83 m s^(-1),and average absolute error of 2.21 m s^(-1).Conversely,in Wind Farm B,the EC model outperforms the CMA-GD model.The CMA-GD model achieves a monthly average correlation coefficient of 0.55,root mean square error of 2.61 m s^(-1),and average absolute error of 2.13 m s^(-1).By contrast,the EC model displays a monthly average correlation coefficient of 0.63,root mean square error of 2.04 m s^(-1),and average absolute error of 1.67 m s^(-1).
基金National Key Research and Development Program of China(2018YFC1507602)National Natural Science Foundation of China(42175105,41505084)Project of Guangzhou Science and Technology(2019B111101002)。
文摘In the present study,the performances of the NWP models on two heavy rainfalls on 20 July and 22 August 2021 over Henan Province were investigated.The impacts of the water vapor transport to the extreme rainfall were further discussed.The results showed that the regional model system in the Guangzhou Meteorological Service generally showed high scores on the extreme rainfall over Henan.The maximum 24h accumulative rainfall by the 24h forecasts by the CMA-GD reached 556 mm over Henan Province.The 24-h and 48-h Threat Score(TS)of heavy rainfall reached 0.56 and 0.64.The comparisons of the Fraction Skill Score(FSS)verifications of the heavy rainfall by CMA-GD and CMA-TRAMS at the radium of 40km reached 0.96 and 0.87.The water vapor transport to the extreme rainfall showed that the vertically integrated water vapor transport(IVT)of the whole layer before the occurrence of the heavy rainfall exhibited a double-eyes distribution in case 7·20.The north eye over Henan reached the same magnitude of IVT as the typhoon eye(Cempaka)over south China.The IVT over the lower troposphere(<500 hPa)showed an overwhelming magnitude than the upper level,especially in the planetary boundary layer(<700 hPa).More practical technique needs to be developed to improve its performances on the forecasting of extreme rainfall,as well as more experiments need to be conducted to examine the effects of the specific terrain and physical schemes on the extreme rainfall.
基金National Key R&D Program of China(2018YFC1506902)National Natural Science Foundation of China(42175105,U2142213)Special Fund of China Meteorological Administration for Innovation and Development(CXFZ2021Z006)。
文摘By deriving the discrete equation of the parameterized equation for the New Medium-Range Forecast(NMRF)boundary layer scheme in the GRAPES model,the adjusted discrete equation for temperature is obviously different from the original equation under the background of hydrostatic equilibrium and adiabatic hypothesis.In the present research,three discrete equations for temperature in the NMRF boundary layer scheme are applied,namely the original(hereafter NMRF),the adjustment(hereafter NMRF-gocp),and the one in the YSU boundary-layer scheme(hereafter NMRF-TZ).The results show that the deviations of height,temperature,U and V wind in the boundary layer in the NMRF-gocp and NMRF-TZ experiments are smaller than those in the NMRF experiment and the deviations in the NMRF-gocp experiment are the smallest.The deviations of humidity are complex for the different forecasting lead time in the three experiments.Moreover,there are obvious diurnal variations of deviations from these variables,where the diurnal variations of deviations from height and temperature are similar and those from U and V wind are also similar.However,the diurnal variation of humidity is relatively complicated.The root means square errors of 2m temperature(T2m)and 10m speed(V10m)from the three experiments show that the error of NMRF-gocp is the smallest and that of NMRF is the biggest.There is also a diurnal variation of T2m and V10m,where T2m has double peaks and V10m has only one peak.Comparison of the discrete equations between NMRF and NMRF-gocp experiments shows that the deviation of temperature is likely to be caused by the calculation of vertical eddy diffusive coefficients of heating,which also leads to the deviations of other elements.
文摘利用T-mode斜交旋转主成分分析法,对湖南2021年汛期(4—9月)逐小时850 hPa风场进行环流分型,在此基础上开展同期华南快速循环同化模式(CMA-GD-R3)小时降水预报性能检验。结果表明:影响湖南2021年汛期的主要环流型为西南涡切变型、切变型、副热带高压边缘南风型和台风外围东风型4类;模式小时降水预报的晴雨准确率和分级降水TS评分日变化特征明显,晴雨准确率夜间高于白天,分级降水TS评分峰值出现在早晨,各环流型的临近时效降水预报效果较好,短时强降水发生频次最高的西南涡切变型晴雨准确率较低,副热带高压边缘南风型在较大量级降水表现相对较差;SAL(structure amplitude and location)检验显示,西南涡切变型、切变型过程模式位置预报较接近实况,强度预报表现为前弱后强,副热带高压边缘南风型过程预报落区分散,位置预报不稳定,整体强度较实况明显偏弱,台风外围东风型过程在短时预报时效落区接近实况,强度预报显著偏弱,该方法能较客观地反映模式降水预报空间偏差。
基金China Meteorological Administration Innovation Development Special Project(CXFZ2022J006)Guangzhou Science and Technology Plan Project(202103000030)+1 种基金China Meteorological Administration Review and Summary Special Project(FPZJ2023-091)Guangzhou Municipal Science and Technology Planning Project of China(202103000030)。
文摘This study evaluated the forecast skill of CMA-GD 3 km and CMA-GD 1 km with hourly Rapid Update Cycle(RUC)for five monsoon precipitation events in South China from 2018 to 2020,using the fraction skill score(FSS)of the neighborhood spatial verification method.The results revealed that,among the 24-lead-hour forecasts in CMA-GD 3 km,the FSS for the 0.1 mm precipitation threshold increased linearly with the lead time from 3 to 1 hour,while there was no significant improvement in other lead times.For the 5 mm precipitation threshold,the forecast skill was highest for the latest 1-hour lead time,while the FSS showed slight variation between lead times of 24 hours and 8 hours.The FSS for 10 mm and 20 mm precipitation thresholds were similar to that of 5 mm,with the difference that the best score occurred at the 2-hour lead time.Among the 6-lead-hour forecasts in CMA-GD 1 km,the forecasts of the latest 1-hour lead time were the best choices for four precipitation thresholds.When comparing CMA-GD 3 km and CMA-GD 1 km,it was found that CMA-GD 3 km had better skill for forecasts of 0.1 mm and 5 mm precipitation at 2-hour and 1-hour lead times,while CMA-GD 1 km had better skill for all other forecasts,including the forecast of 20 mm precipitation nearly all lead hours(including 3-to 6-hour,and 1-hour lead times).The results suggest that the increased resolution of the model may be beneficial for precipitation forecasts in South China,especially for short-duration heavy precipitation over a longer lead hours.However,the limited sample size of this study calls for further evaluation using more cases to validate the results′generality.
基金Natural Science Foundation of Hunan Province(2021JC0009)National Natural Science Foundation of China(42375002,42105146)Key Projects of Hunan Meteorological Bureau(XQKJ22A004)。
文摘In real-time operations,the minutely/hourly updated high-resolution rapid refresh(HRRR)system is one of the most expensive numerical weather prediction(NWP)models.Based on a twenty-member HRRR-time-lagged-ensemble(HRRR-TLE)system developed from two real-time convection-permitting HRRR models,CMA-GD(R3)and CMA-SH3,from the China Meteorological Administration(CMA),this study proposes an optimized probability-matching(OPM)technique to improve 0−12 h quantitative precipitation forecasts(QPFs)based on the correlation and error relationships between ensemble forecasts and observations during the training window.Then,a series of sensitivity experiments using different cost functions and optimized ratios was conducted to further improve OPM predictions.The results indicate that:(1)In the HRRR-TLE system,there is no always optimal member in both weak rain and severe rain forecasts,as measured by the equitable threat score(ETS)and bias extent(BE)at four thresholds(1+,5+,10+,and 20+mm h^(-1);e.g.,“1+”means≥1).(2)Compared with the HRRR-TLE system,the QPFs generated by the traditional PM technique showed a notable increase in ETS and a decrease in BE at all of the above thresholds.Compared with the traditional probability-matching method(PM),OPM can generate more skillful forecasts on both spatial representations and rain rates by using the sliding-weight method and optimized ensembles,respectively.(3)In particular,in the 20+mm h^(-1)forecasts,which are often difficult to predict,the ETS of the optimal OPM test,with a 20%optimization ratio and symmetric mean absolute percentage error cost function,increased by 64.6%,and the BE decreased by 5.7%,relative to PM.Moreover,OPM shows good stability in both daytime and nighttime periods.
