Medium to long-term precipitation forecasting plays a pivotal role in water resource management and development of warning systems.Recently,the Copernicus Climate Change Service(C3S)database has been releasing monthly...Medium to long-term precipitation forecasting plays a pivotal role in water resource management and development of warning systems.Recently,the Copernicus Climate Change Service(C3S)database has been releasing monthly forecasts for lead times of up to three months for public use.This study evaluated the ensemble forecasts of three C3S models over the period 1993-2017 in Iran’s eight classified precipitation clusters for one-to three-month lead times.Probabilistic and non-probabilistic criteria were used for evaluation.Furthermore,the skill of selected models was analyzed in dry and wet periods in different precipitation clusters.The results indicated that the models performed best in western precipitation clusters,while in the northern humid cluster the models had negative skill scores.All models were better at forecasting upper-tercile events in dry seasons and lower-tercile events in wet seasons.Moreover,with increasing lead time,the forecast skill of the models worsened.In terms of forecasting in dry and wet years,the forecasts of the models were generally close to observations,albeit they underestimated several severe dry periods and overestimated a few wet periods.Moreover,the multi-model forecasts generated via multivariate regression of the forecasts of the three models yielded better results compared with those of individual models.In general,the ECMWF and UKMO models were found to be appropriate for one-month-ahead precipitation forecasting in most clusters of Iran.For the clusters considered in Iran and for the long-range system versions considered,the Météo France model had lower skill than the other models.展开更多
Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relie...Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relief.Currently,the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated.In this study,precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products(the fifth generation of European Centre for Medium-Range Weather Forecasts(ECMWF)atmospheric reanalysis of the global climate(ERA5),Global Precipitation Climatology Centre(GPCC),Climatic Research Unit gridded Time Series Version 4.07(CRU TS v4.07,hereafter CRU),and Tropical Rainfall Measuring Mission(TRMM))based on the following statistical indicators:correlation coefficient,root mean square error(RMSE),relative bias(RB),mean absolute error(MAE),probability of detection(POD),false alarm ratio(FAR),and equitable threat score(ETS).The results showed that precipitation in Northwest China was generally high in the east and low in the west,and exhibited an increasing trend from 1979 to 2020.Compared with the station observations,ERA5 showed a larger spatial distribution difference than the other products.The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity.The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations.The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation.At the monthly scale,GPCC performed well but underestimated precipitation in the Tarim Basin(RB=-4.11%),while ERA5 and TRMM exhibited poor accuracy in high-altitude regions.ERA5 had a large bias(RB≥120.00%)in winter months and a strong dispersion(RMSE≥35.00 mm)in sum展开更多
The tropical cyclone(TC)named Amos(2016)that impacted the Samoan Islands on 23 April 2016 was a particularly dif f icult storm to forecast.Both the intensity changes and the track of Amos represent a signif icant chal...The tropical cyclone(TC)named Amos(2016)that impacted the Samoan Islands on 23 April 2016 was a particularly dif f icult storm to forecast.Both the intensity changes and the track of Amos represent a signif icant challenge for forecasters and this is briefl y summarized in this report.Model forecasts initially indicated that the cyclone would track south of the Samoan Islands.However,the forecasts generally changed to a direct hit over Samoa as a Category 4 storm at approximately 0000 U TC 24April based on model cycles initialized at 0000 UTC 23 April.TC Amos’central pressure dropped from 983 hPa to 957 hPa between 0000 UTC 21 April and 0000 UTC 23April.The models did not pick up on this rapid intensif ication until the intensif ication had already begun around0000 UTC 21 April.The models also struggled to capture the rapid weakening of TC Amos due to vertical wind shear that began 0000 UTC 24 April as the cyclone continued to move north of the islands.Because of the initially ominous track forecasts for TC Amos to hit land,preparations for a Category 3 or Category 4 cyclone were underway in the Samoan islands and the population prepared for the worst.After the center of the storm moved north of the islands as a weaker storm than anticipated,the residents of the Samoan Islands were both surprised and relieved that the cyclone only gave a"glancing blow"to the islands and that the impacts were not as bad as originally feared.An in-depth evaluation of this particular tropical cyclone helps to shed some light on model def iciencies and can be used to help determine future model changes.展开更多
文摘数值气象预报与水文模型相结合能有效延长洪水预报的预见期,对中小流域山洪预警具有重要意义。为了研究高分辨率数值气象预报模式在中小流域洪水预报中的应用潜力,以福建省桃溪流域为研究对象,评估了数值气象预报模式GRAPES-RAFS(Rapid Analysis and Forecast System)在不同起报时刻的短期降雨预报能力,采用两种偏差校正方法(线性放缩法(LS)和分位数匹配法(QM))对降雨预报数据进行偏差校正处理,并分别用校正前和校正后的数据驱动新安江模型,评估预报降水在场次洪水预报中的适用性。评估结果表明,GRAPES-RAFS中小流域降雨过程具有较好的预报能力,但高估了降雨量,所有评价指标具有较好的一致性;采用两种偏差校正方法均能显著降低降雨预报的偏差,12场降雨的平均相对偏差从60.33%分别降低至18.00%(LS方法)和21.33%(QM方法);未经校正的GRAPES-RAFS预报降雨直接用于洪水预报的效果表现不佳,洪峰被明显高估,但降雨偏差校正能显著提升洪水预报的精度。总体而言,偏差校正后表现较好的降雨场次对应表现较好的洪水场次,且两种偏差校正方法表现相近。
文摘Medium to long-term precipitation forecasting plays a pivotal role in water resource management and development of warning systems.Recently,the Copernicus Climate Change Service(C3S)database has been releasing monthly forecasts for lead times of up to three months for public use.This study evaluated the ensemble forecasts of three C3S models over the period 1993-2017 in Iran’s eight classified precipitation clusters for one-to three-month lead times.Probabilistic and non-probabilistic criteria were used for evaluation.Furthermore,the skill of selected models was analyzed in dry and wet periods in different precipitation clusters.The results indicated that the models performed best in western precipitation clusters,while in the northern humid cluster the models had negative skill scores.All models were better at forecasting upper-tercile events in dry seasons and lower-tercile events in wet seasons.Moreover,with increasing lead time,the forecast skill of the models worsened.In terms of forecasting in dry and wet years,the forecasts of the models were generally close to observations,albeit they underestimated several severe dry periods and overestimated a few wet periods.Moreover,the multi-model forecasts generated via multivariate regression of the forecasts of the three models yielded better results compared with those of individual models.In general,the ECMWF and UKMO models were found to be appropriate for one-month-ahead precipitation forecasting in most clusters of Iran.For the clusters considered in Iran and for the long-range system versions considered,the Météo France model had lower skill than the other models.
基金supported by the National Key Research and Development Program of China(2023YFC3206300)the National Natural Science Foundation of China(42477529,42371145,42261026)+2 种基金the China-Pakistan Joint Program of the Chinese Academy of Sciences(046GJHZ2023069MI)the Gansu Provincial Science and Technology Program(22ZD6FA005)the National Cryosphere Desert Data Center(E01Z790201).
文摘Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relief.Currently,the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated.In this study,precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products(the fifth generation of European Centre for Medium-Range Weather Forecasts(ECMWF)atmospheric reanalysis of the global climate(ERA5),Global Precipitation Climatology Centre(GPCC),Climatic Research Unit gridded Time Series Version 4.07(CRU TS v4.07,hereafter CRU),and Tropical Rainfall Measuring Mission(TRMM))based on the following statistical indicators:correlation coefficient,root mean square error(RMSE),relative bias(RB),mean absolute error(MAE),probability of detection(POD),false alarm ratio(FAR),and equitable threat score(ETS).The results showed that precipitation in Northwest China was generally high in the east and low in the west,and exhibited an increasing trend from 1979 to 2020.Compared with the station observations,ERA5 showed a larger spatial distribution difference than the other products.The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity.The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations.The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation.At the monthly scale,GPCC performed well but underestimated precipitation in the Tarim Basin(RB=-4.11%),while ERA5 and TRMM exhibited poor accuracy in high-altitude regions.ERA5 had a large bias(RB≥120.00%)in winter months and a strong dispersion(RMSE≥35.00 mm)in sum
文摘The tropical cyclone(TC)named Amos(2016)that impacted the Samoan Islands on 23 April 2016 was a particularly dif f icult storm to forecast.Both the intensity changes and the track of Amos represent a signif icant challenge for forecasters and this is briefl y summarized in this report.Model forecasts initially indicated that the cyclone would track south of the Samoan Islands.However,the forecasts generally changed to a direct hit over Samoa as a Category 4 storm at approximately 0000 U TC 24April based on model cycles initialized at 0000 UTC 23 April.TC Amos’central pressure dropped from 983 hPa to 957 hPa between 0000 UTC 21 April and 0000 UTC 23April.The models did not pick up on this rapid intensif ication until the intensif ication had already begun around0000 UTC 21 April.The models also struggled to capture the rapid weakening of TC Amos due to vertical wind shear that began 0000 UTC 24 April as the cyclone continued to move north of the islands.Because of the initially ominous track forecasts for TC Amos to hit land,preparations for a Category 3 or Category 4 cyclone were underway in the Samoan islands and the population prepared for the worst.After the center of the storm moved north of the islands as a weaker storm than anticipated,the residents of the Samoan Islands were both surprised and relieved that the cyclone only gave a"glancing blow"to the islands and that the impacts were not as bad as originally feared.An in-depth evaluation of this particular tropical cyclone helps to shed some light on model def iciencies and can be used to help determine future model changes.
