利用1999 2010年共12年NCEP CFSv2(NCEP Climate Forecast System version 2)每天4个时次对未来45天预测的回报数据,检验了CFSv2模式对北半球夏季(6 8月)中高纬乌拉尔山区域(10°E70°E)和贝加尔湖-鄂霍次克海区域(110°E 1...利用1999 2010年共12年NCEP CFSv2(NCEP Climate Forecast System version 2)每天4个时次对未来45天预测的回报数据,检验了CFSv2模式对北半球夏季(6 8月)中高纬乌拉尔山区域(10°E70°E)和贝加尔湖-鄂霍次克海区域(110°E 180°E)阻塞高压及其与之相联系的东亚气候的预测能力。分析结果显示,CFSv2可以较好的模拟夏季北半球阻塞高压发生频率的纬向分布特征,但随着预测时效的增加阻塞发生的频率不断降低。CFSv2对两个区域阻塞预测的命中率在7天时效内为50%左右,接近2周之后基本上没有技巧。CFSv2对区域阻塞事件的预测技巧要低于区域阻塞的技巧,贝加尔湖-鄂霍次克海区域阻塞事件的技巧略低于乌拉尔山区域。CFSv2对阻塞爆发和结束的预测超过7天左右,基本没有预测技巧,对乌拉尔山区域阻塞结束日的预测技巧要低于阻塞爆发日的预测技巧。CFSv2在可用的预测时效内可以较好再现与区域阻塞相联系的环流形势以及东亚地区气温、降水异常的分布特征,尤其是夏季乌拉尔山和鄂霍茨克海地区发生阻塞时我国长江流域及其以南地区降水容易偏多的特征。展开更多
The boreal spring Antarctic Oscillation(AAO)has a significant impact on the spring and summer climate in China.This study evaluates the capability of the NCEP's Climate Forecast System,version 2(CFSv2),in predicti...The boreal spring Antarctic Oscillation(AAO)has a significant impact on the spring and summer climate in China.This study evaluates the capability of the NCEP's Climate Forecast System,version 2(CFSv2),in predicting the boreal spring AAO for the period 1983-2015.The results indicate that CFSv2 has poor skill in predicting the spring AAO,failing to predict the zonally symmetric spatial pattern of the AAO,with an insignificant correlation of 0.02 between the predicted and observed AAO Index(AAOI).Considering the interannual increment approach can amplify the prediction signals,we firstly establish a dynamical-statistical model to improve the interannual increment of the AAOI(DY AAOI),with two predictors of CFSv2-forecasted concurrent spring sea surface temperatures and observed preceding autumn sea ice.This dynamical-statistical model demonstrates good capability in predicting DY AAOI,with a significant correlation coeffcient of 0.58 between the observation and prediction during 1983-2015 in the two-year-out cross-validation.Then,we obtain an improved AAOI by adding the improved DY AAOI to the preceding observed AAOI.The improved AAOI shows a significant correlation coeffcient of 0.45 with the observed AAOI during 1983-2015.Moreover,the unrealistic atmospheric response to March-April-May sea ice in CFSv2 may be the possible cause for the failure of CFSv2 to predict the AAO.This study gives new clues regarding AAO prediction and short-term climate prediction.展开更多
利用地基GPS估计PWV(precipitable water vapor)时,除GPS观测数据外,GPS测站地表的气温和气压也是必要参数。针对我国多数GPS网并未配备相应的气象传感器的情况,利用美国环境预报中心气候预报系统第2版提供的逐6h产品,并顾及测站高程转...利用地基GPS估计PWV(precipitable water vapor)时,除GPS观测数据外,GPS测站地表的气温和气压也是必要参数。针对我国多数GPS网并未配备相应的气象传感器的情况,利用美国环境预报中心气候预报系统第2版提供的逐6h产品,并顾及测站高程转换时的平均海平面高改正,提出一种GPS测站气象参数的插值新方法。以香港卫星定位参考站网实测GPS数据进行试验研究,结果表明,平均海平面高对地表气压的插值结果影响较大,而对地表气温的插值结果影响较小;经平均海平面高改正后,地表气压插值结果的平均均方根误差(RMSE)为1.61hPa,地表气温插值结果的平均RMSE为1.93 K;由插值气象参数估计的PWV的平均RMSE为2.76mm,验证了所提方法的有效性。展开更多
Daily output from the hindcasts by the NCEP Climate Forecast System version 2 （CFSv2） is analyzed to understand CFSv2＇s skill in forecasting wintertime atmospheric blocking in the Northern Hemisphere. Prediction sk...Daily output from the hindcasts by the NCEP Climate Forecast System version 2 （CFSv2） is analyzed to understand CFSv2＇s skill in forecasting wintertime atmospheric blocking in the Northern Hemisphere. Prediction skills of sector blocking, sector-blocking episodes, and blocking onset/decay are assessed with a focus on the Euro-Atlantic sector （20°W-45°E） and the Pacific sector （160°E 135°W）. Features of associated circulation and climate patterns are also examined. The CFSv2 well captures the observed features of longitudinal distribution of blocking activity, but underestimates blocking frequency and intensity and shows a decreasing trend in blocking frequency with increasing forecast lead time. Within 14-day lead time, the Euro-Atlantic sector blocking receives a higher skill than the Pacific sector blocking. Skillful forecast （taking the hit rate of 50~ as a criterion） can be obtained up to 9 days in the Euro-Atlantic sector, which is slightly longer than that in the Pacific sector （7 days）. The forecast skill of sector-blocking episodes is slightly lower than that of sector blocking in both sectors, and it is slightly higher in the Euro-Atlantic sector than in the Pacific sector. Compared to block onset, the skill for block decay is lower in the Euro-Atlantic sector, slightly higher in the Pacific sector during the early three days but lower after three days in lead time. In both the Euro-Atlantic and the Pacific sectors, a local dipole pattern in 500-hPa geopotential height associated with blocking is well presented in the CFSv2 prediction, but the wave-train like pattern that is far away from the blocking sector can only maintain in the forecast of relative short lead time. The CFSv2 well reproduces the observed characteristics of local temperature and precipitation anomalies associated with blocking.展开更多
为建立四川省延伸期高温、降水和强降温过程的预报模型,利用第二代气候预报系统(climate forecast system version 2,CFSv2)预报的延伸期逐日环流场和四川省台站逐日降水、最高温度和最低温度,采用动力应用法,通过把预报环流场按预报时...为建立四川省延伸期高温、降水和强降温过程的预报模型,利用第二代气候预报系统(climate forecast system version 2,CFSv2)预报的延伸期逐日环流场和四川省台站逐日降水、最高温度和最低温度,采用动力应用法,通过把预报环流场按预报时效逐日分组,以各组预报环流场与站点要素同期变化显著相关区域的环流场作为预报因子,逐日建立各站点的多因子线性预报方程。将站点预报插值为格点预报,得到四川省延伸期逐日降水、高温和强降温格点预报。3次预报试验和回报结果表明:该方法能够提前11~30天报出大型天气的主要发生时段、落区和强度。该方法对高温和强降温过程的预报效果比降水预报好,随着预报提前时间增加,3种要素预报效果逐渐降低。研究结果对延伸期精细化气象服务具有重要参考价值。展开更多
Extreme high temperatures occur frequently over the densely populated Yangtze River basin(YRB)in China during summer,significantly impacting the local economic development and ecological system.However,accurate predic...Extreme high temperatures occur frequently over the densely populated Yangtze River basin(YRB)in China during summer,significantly impacting the local economic development and ecological system.However,accurate prediction of extreme high-temperature days in this region remains a challenge.Unfortunately,the Climate Forecast System Version 2(CFSv2)exhibits poor performance in this regard.Thus,based on the interannual increment approach,we develop a hybrid seasonal prediction model over the YRB(HM_(YRB))to improve the prediction of extreme high-temperature days in summer.The HM_(YRB)relies on the following four predictors:the observed preceding April-May snowmelt in north western Europe;the snow depth in March over the central Siberian Plateau;the CFSv2-forecasted concurrent summer sea surface temperatures around the Maritime Continent;and the 200-hPa geopotential height over the Tibetan Plateau.The HM_(YRB)indicates good capabilities in predicting the interannual variability and trend of extreme high-temperature days,with a markable correlation coefficient of 0.58 and a percentage of the same sign(PSS)of 76% during 1983-2015 in the one-year-out cross-validation.Additionally,the HM_(YRB) maintains high PSS skill(86%)and robustness in the independent prediction period(2016-2022).Furthermore,the HM_(YRB) shows a good performance for years with high occurrence of extreme high-temperature days,with a hit ratio of 40%.These predictors used in HM_(YRB)are beneficial in terms of the prediction skill for the average daily maximum temperature in summer over the YRB,albeit with biases existing in the magnitude.Our study provides promising insights into the prediction of 2022-like hot extremes over the YRB in China.展开更多
Conflicting results have been presented regarding the link between Arctic sea-ice loss and midlatitude cooling, particularly over Eurasia. This study analyzes uncoupled(atmosphere-only) and coupled(ocean–atmosphere) ...Conflicting results have been presented regarding the link between Arctic sea-ice loss and midlatitude cooling, particularly over Eurasia. This study analyzes uncoupled(atmosphere-only) and coupled(ocean–atmosphere) simulations by the Climate Forecast System, version 2(CFSv2), to examine this linkage during the Northern Hemisphere winter, focusing on the simulation of the observed surface cooling trend over Eurasia during the last three decades. The uncoupled simulations are Atmospheric Model Intercomparison Project(AMIP) runs forced with mean seasonal cycles of sea surface temperature(SST)and sea ice, using combinations of SST and sea ice from different time periods to assess the role that each plays individually,and to assess the role of atmospheric internal variability. Coupled runs are used to further investigate the role of internal variability via the analysis of initialized predictions and the evolution of the forecast with lead time.The AMIP simulations show a mean warming response over Eurasia due to SST changes, but little response to changes in sea ice. Individual runs simulate cooler periods over Eurasia, and this is shown to be concurrent with a stronger Siberian high and warming over Greenland. No substantial differences in the variability of Eurasian surface temperatures are found between the different model configurations. In the coupled runs, the region of significant warming over Eurasia is small at short leads, but increases at longer leads. It is concluded that, although the models have some capability in highlighting the temperature variability over Eurasia, the observed cooling may still be a consequence of internal variability.展开更多
In this study,we assess the prediction for May rainfall over southern China(SC)by using the NCEP CFSv2 outputs.Results show that the CFSv2 is able to depict the climatology of May rainfall and associated circulations....In this study,we assess the prediction for May rainfall over southern China(SC)by using the NCEP CFSv2 outputs.Results show that the CFSv2 is able to depict the climatology of May rainfall and associated circulations.However,the model has a poor skill in predicting interannual variation due to its poor performance in capturing related anomalous circulations.In observation,the above-normal SC rainfall is associated with two anomalous anticyclones over the western tropical Pacific and northeastern China,respectively,with a low-pressure convergence in between.In the CFSv2,however,the anomalous circulations exhibit the patterns in response to the El Ni?o-Southern Oscillation(ENSO),demonstrating that the model overestimates the relationship between May SC rainfall and ENSO.Because of the onset of the South China Sea monsoon,the atmospheric circulation in May over SC is more complex,so the prediction for May SC rainfall is more challenging.In this study,we establish a dynamic-statistical forecast model for May SC rainfall based on the relationship between the interannual variation of rainfall and large-scale ocean-atmosphere variables in the CFSv2.The sea surface temperature anomalies(SSTAs)in the northeastern Pacific and the centraleastern equatorial Pacific,and the 500-h Pa geopotential height anomalies over western Siberia in previous April,which exert great influence on the SC rainfall in May,are chosen as predictors.Furthermore,multiple linear regression is employed between the predictors obtained from the CFSv2 and observed May SC rainfall.Both cross validation and independent test show that the hybrid model significantly improve the model’s skill in predicting the interannual variation of May SC rainfall by two months in advance.展开更多
文摘利用1999 2010年共12年NCEP CFSv2(NCEP Climate Forecast System version 2)每天4个时次对未来45天预测的回报数据,检验了CFSv2模式对北半球夏季(6 8月)中高纬乌拉尔山区域(10°E70°E)和贝加尔湖-鄂霍次克海区域(110°E 180°E)阻塞高压及其与之相联系的东亚气候的预测能力。分析结果显示,CFSv2可以较好的模拟夏季北半球阻塞高压发生频率的纬向分布特征,但随着预测时效的增加阻塞发生的频率不断降低。CFSv2对两个区域阻塞预测的命中率在7天时效内为50%左右,接近2周之后基本上没有技巧。CFSv2对区域阻塞事件的预测技巧要低于区域阻塞的技巧,贝加尔湖-鄂霍次克海区域阻塞事件的技巧略低于乌拉尔山区域。CFSv2对阻塞爆发和结束的预测超过7天左右,基本没有预测技巧,对乌拉尔山区域阻塞结束日的预测技巧要低于阻塞爆发日的预测技巧。CFSv2在可用的预测时效内可以较好再现与区域阻塞相联系的环流形势以及东亚地区气温、降水异常的分布特征,尤其是夏季乌拉尔山和鄂霍茨克海地区发生阻塞时我国长江流域及其以南地区降水容易偏多的特征。
基金supported by the National Key Research and Development Program of China (Grant No. 2016YFA0600703)the funding of the Jiangsu Innovation & Entrepreneurship Team and the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘The boreal spring Antarctic Oscillation(AAO)has a significant impact on the spring and summer climate in China.This study evaluates the capability of the NCEP's Climate Forecast System,version 2(CFSv2),in predicting the boreal spring AAO for the period 1983-2015.The results indicate that CFSv2 has poor skill in predicting the spring AAO,failing to predict the zonally symmetric spatial pattern of the AAO,with an insignificant correlation of 0.02 between the predicted and observed AAO Index(AAOI).Considering the interannual increment approach can amplify the prediction signals,we firstly establish a dynamical-statistical model to improve the interannual increment of the AAOI(DY AAOI),with two predictors of CFSv2-forecasted concurrent spring sea surface temperatures and observed preceding autumn sea ice.This dynamical-statistical model demonstrates good capability in predicting DY AAOI,with a significant correlation coeffcient of 0.58 between the observation and prediction during 1983-2015 in the two-year-out cross-validation.Then,we obtain an improved AAOI by adding the improved DY AAOI to the preceding observed AAOI.The improved AAOI shows a significant correlation coeffcient of 0.45 with the observed AAOI during 1983-2015.Moreover,the unrealistic atmospheric response to March-April-May sea ice in CFSv2 may be the possible cause for the failure of CFSv2 to predict the AAO.This study gives new clues regarding AAO prediction and short-term climate prediction.
文摘利用地基GPS估计PWV(precipitable water vapor)时,除GPS观测数据外,GPS测站地表的气温和气压也是必要参数。针对我国多数GPS网并未配备相应的气象传感器的情况,利用美国环境预报中心气候预报系统第2版提供的逐6h产品,并顾及测站高程转换时的平均海平面高改正,提出一种GPS测站气象参数的插值新方法。以香港卫星定位参考站网实测GPS数据进行试验研究,结果表明,平均海平面高对地表气压的插值结果影响较大,而对地表气温的插值结果影响较小;经平均海平面高改正后,地表气压插值结果的平均均方根误差(RMSE)为1.61hPa,地表气温插值结果的平均RMSE为1.93 K;由插值气象参数估计的PWV的平均RMSE为2.76mm,验证了所提方法的有效性。
基金Supported by the National(Key)Basic Research and Development(973)Program of China(2010CB428606 and 2014CB950900)China Meteorological Administration Special Public Welfare Research Fund(GYHY201206017)+1 种基金National Science and Technology Support Program of China(2009BAC51B05)LASW State Key Laboratory Special Fund(2013LASW-A05)
文摘Daily output from the hindcasts by the NCEP Climate Forecast System version 2 （CFSv2） is analyzed to understand CFSv2＇s skill in forecasting wintertime atmospheric blocking in the Northern Hemisphere. Prediction skills of sector blocking, sector-blocking episodes, and blocking onset/decay are assessed with a focus on the Euro-Atlantic sector （20°W-45°E） and the Pacific sector （160°E 135°W）. Features of associated circulation and climate patterns are also examined. The CFSv2 well captures the observed features of longitudinal distribution of blocking activity, but underestimates blocking frequency and intensity and shows a decreasing trend in blocking frequency with increasing forecast lead time. Within 14-day lead time, the Euro-Atlantic sector blocking receives a higher skill than the Pacific sector blocking. Skillful forecast （taking the hit rate of 50~ as a criterion） can be obtained up to 9 days in the Euro-Atlantic sector, which is slightly longer than that in the Pacific sector （7 days）. The forecast skill of sector-blocking episodes is slightly lower than that of sector blocking in both sectors, and it is slightly higher in the Euro-Atlantic sector than in the Pacific sector. Compared to block onset, the skill for block decay is lower in the Euro-Atlantic sector, slightly higher in the Pacific sector during the early three days but lower after three days in lead time. In both the Euro-Atlantic and the Pacific sectors, a local dipole pattern in 500-hPa geopotential height associated with blocking is well presented in the CFSv2 prediction, but the wave-train like pattern that is far away from the blocking sector can only maintain in the forecast of relative short lead time. The CFSv2 well reproduces the observed characteristics of local temperature and precipitation anomalies associated with blocking.
文摘为建立四川省延伸期高温、降水和强降温过程的预报模型,利用第二代气候预报系统(climate forecast system version 2,CFSv2)预报的延伸期逐日环流场和四川省台站逐日降水、最高温度和最低温度,采用动力应用法,通过把预报环流场按预报时效逐日分组,以各组预报环流场与站点要素同期变化显著相关区域的环流场作为预报因子,逐日建立各站点的多因子线性预报方程。将站点预报插值为格点预报,得到四川省延伸期逐日降水、高温和强降温格点预报。3次预报试验和回报结果表明:该方法能够提前11~30天报出大型天气的主要发生时段、落区和强度。该方法对高温和强降温过程的预报效果比降水预报好,随着预报提前时间增加,3种要素预报效果逐渐降低。研究结果对延伸期精细化气象服务具有重要参考价值。
基金supported by the National Key R&D Program of China(Grant No.2022YFF0801604)。
文摘Extreme high temperatures occur frequently over the densely populated Yangtze River basin(YRB)in China during summer,significantly impacting the local economic development and ecological system.However,accurate prediction of extreme high-temperature days in this region remains a challenge.Unfortunately,the Climate Forecast System Version 2(CFSv2)exhibits poor performance in this regard.Thus,based on the interannual increment approach,we develop a hybrid seasonal prediction model over the YRB(HM_(YRB))to improve the prediction of extreme high-temperature days in summer.The HM_(YRB)relies on the following four predictors:the observed preceding April-May snowmelt in north western Europe;the snow depth in March over the central Siberian Plateau;the CFSv2-forecasted concurrent summer sea surface temperatures around the Maritime Continent;and the 200-hPa geopotential height over the Tibetan Plateau.The HM_(YRB)indicates good capabilities in predicting the interannual variability and trend of extreme high-temperature days,with a markable correlation coefficient of 0.58 and a percentage of the same sign(PSS)of 76% during 1983-2015 in the one-year-out cross-validation.Additionally,the HM_(YRB) maintains high PSS skill(86%)and robustness in the independent prediction period(2016-2022).Furthermore,the HM_(YRB) shows a good performance for years with high occurrence of extreme high-temperature days,with a hit ratio of 40%.These predictors used in HM_(YRB)are beneficial in terms of the prediction skill for the average daily maximum temperature in summer over the YRB,albeit with biases existing in the magnitude.Our study provides promising insights into the prediction of 2022-like hot extremes over the YRB in China.
基金supported by the NOAA Climate Program Office Climate Variability and Predictability Program
文摘Conflicting results have been presented regarding the link between Arctic sea-ice loss and midlatitude cooling, particularly over Eurasia. This study analyzes uncoupled(atmosphere-only) and coupled(ocean–atmosphere) simulations by the Climate Forecast System, version 2(CFSv2), to examine this linkage during the Northern Hemisphere winter, focusing on the simulation of the observed surface cooling trend over Eurasia during the last three decades. The uncoupled simulations are Atmospheric Model Intercomparison Project(AMIP) runs forced with mean seasonal cycles of sea surface temperature(SST)and sea ice, using combinations of SST and sea ice from different time periods to assess the role that each plays individually,and to assess the role of atmospheric internal variability. Coupled runs are used to further investigate the role of internal variability via the analysis of initialized predictions and the evolution of the forecast with lead time.The AMIP simulations show a mean warming response over Eurasia due to SST changes, but little response to changes in sea ice. Individual runs simulate cooler periods over Eurasia, and this is shown to be concurrent with a stronger Siberian high and warming over Greenland. No substantial differences in the variability of Eurasian surface temperatures are found between the different model configurations. In the coupled runs, the region of significant warming over Eurasia is small at short leads, but increases at longer leads. It is concluded that, although the models have some capability in highlighting the temperature variability over Eurasia, the observed cooling may still be a consequence of internal variability.
基金National Natural Science Foundation of China(42088101,41975074)Project of Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies(2020B1212060025)。
文摘In this study,we assess the prediction for May rainfall over southern China(SC)by using the NCEP CFSv2 outputs.Results show that the CFSv2 is able to depict the climatology of May rainfall and associated circulations.However,the model has a poor skill in predicting interannual variation due to its poor performance in capturing related anomalous circulations.In observation,the above-normal SC rainfall is associated with two anomalous anticyclones over the western tropical Pacific and northeastern China,respectively,with a low-pressure convergence in between.In the CFSv2,however,the anomalous circulations exhibit the patterns in response to the El Ni?o-Southern Oscillation(ENSO),demonstrating that the model overestimates the relationship between May SC rainfall and ENSO.Because of the onset of the South China Sea monsoon,the atmospheric circulation in May over SC is more complex,so the prediction for May SC rainfall is more challenging.In this study,we establish a dynamic-statistical forecast model for May SC rainfall based on the relationship between the interannual variation of rainfall and large-scale ocean-atmosphere variables in the CFSv2.The sea surface temperature anomalies(SSTAs)in the northeastern Pacific and the centraleastern equatorial Pacific,and the 500-h Pa geopotential height anomalies over western Siberia in previous April,which exert great influence on the SC rainfall in May,are chosen as predictors.Furthermore,multiple linear regression is employed between the predictors obtained from the CFSv2 and observed May SC rainfall.Both cross validation and independent test show that the hybrid model significantly improve the model’s skill in predicting the interannual variation of May SC rainfall by two months in advance.
