利用CWRF模式(Climate-Weather Research and Forecasting model)对国家气候中心BCC_CSM1.1m业务预测模式短期气候预测结果进行中国区域降尺度,并使用1991—2010年3—8月逐日气温降水观测数据评估预测能力。结果表明:CWRF预测地面2 m气...利用CWRF模式(Climate-Weather Research and Forecasting model)对国家气候中心BCC_CSM1.1m业务预测模式短期气候预测结果进行中国区域降尺度,并使用1991—2010年3—8月逐日气温降水观测数据评估预测能力。结果表明:CWRF预测地面2 m气温、降水气候平均态的空间分布比BCC_CSM1.1m更接近观测,分布误差更小;在保持总体技巧不低于BCC_CSM1.1m的同时,CWRF对我国华东和华中地区的降水年际变化预测准确率更高;对不同强度的降水预测CWRF表现均优于BCC_CSM1.1 m模式,尤其在极端降水预测准确率上更优。总之,得益于更高的空间分辨率和优化的低空物理过程模拟,CWRF降尺度可以提高中国夏季跨季度降水预测能力。展开更多
The prediction skill of Arctic Oscillation (AO) in the decadal experiments with the Beijing Climate Center Climate System Model version 1.1 (BCC_CSM1.1) is assessed. As compared with the observations and historical ex...The prediction skill of Arctic Oscillation (AO) in the decadal experiments with the Beijing Climate Center Climate System Model version 1.1 (BCC_CSM1.1) is assessed. As compared with the observations and historical experiments, the contribution of initialization for climate model to predict the seasonal scale AO and its interannual variations is estimated. Results show that the spatial correlation coefficient of AO mode simulated by the decadal experiment is higher than that in the historical experiment. The two groups of experiments reasonably reproduce the characteristics that AO indices are the strongest in winter and the weakest in summer. Compared with historical experiments, the correlation coefficient of the monthly and winter AO indices are higher in the decadal experiments. In particular, the correlation coefficient of monthly AO index between decadal hindcast and observation reached 0.1 significant level. Furthermore, the periodicity of the monthly and spring AO indices are achieved only in the decadal experiments. Therefore, the initial state of model is initialized by using sea temperature data may help to improve the prediction skill of AO in the decadal prediction experiments to some extent.展开更多
This study focuses on model predictive skill with respect to stratospheric sudden warming(SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF's model under the sub-seasonal to se...This study focuses on model predictive skill with respect to stratospheric sudden warming(SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF's model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM(ECMWF) is the hindcast initiated two(three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts.展开更多
The historical simulation of phase five of the Coupled Model Intercomparison Project （CMIP5） ex- periments performed by the Beijing Climate Center cli- mate system model （BCC_CSM1.1） is evaluated regard- ing the t...The historical simulation of phase five of the Coupled Model Intercomparison Project （CMIP5） ex- periments performed by the Beijing Climate Center cli- mate system model （BCC_CSM1.1） is evaluated regard- ing the time evolutions of the global and China mean sur- face air temperature （SAT） and surface climate change over China in recent decades. BCC CSM1.1 has better capability at reproducing the time evolutions of the global and China mean SAT than BCC_CSM1.0. By the year 2005, the BCC_CSM1.1 model simulates a warming am- plitude of approximately I℃ in China over the 1961- 1990 mean, which is consistent with observation. The distributions of the warming trend over China in the four seasons during 1958-2004 are basically reproduced by BCC CSM1.1, with the warmest occurring in winter. Al- though the cooling signal of Southwest China in spring is partly reproduced by BCC_CSM1.1, the cooling trend over central eastern China in summer is omitted by the model. For the precipitation change, BCC_CSM1.1 has good performance in spring, with drought in Southeast China. After removing the linear trend, the interannual correlation map between the model and the observation shows that the model has better capability at reproducing the summer SAT over China and spring precipitation over Southeast China.展开更多
文摘利用CWRF模式(Climate-Weather Research and Forecasting model)对国家气候中心BCC_CSM1.1m业务预测模式短期气候预测结果进行中国区域降尺度,并使用1991—2010年3—8月逐日气温降水观测数据评估预测能力。结果表明:CWRF预测地面2 m气温、降水气候平均态的空间分布比BCC_CSM1.1m更接近观测,分布误差更小;在保持总体技巧不低于BCC_CSM1.1m的同时,CWRF对我国华东和华中地区的降水年际变化预测准确率更高;对不同强度的降水预测CWRF表现均优于BCC_CSM1.1 m模式,尤其在极端降水预测准确率上更优。总之,得益于更高的空间分辨率和优化的低空物理过程模拟,CWRF降尺度可以提高中国夏季跨季度降水预测能力。
基金National Natural Science Foundation of China (41790471, 41175065)National Key Research and Development Program of China (2016YFA0602200, 2012CB955203, 2013CB430202).
文摘The prediction skill of Arctic Oscillation (AO) in the decadal experiments with the Beijing Climate Center Climate System Model version 1.1 (BCC_CSM1.1) is assessed. As compared with the observations and historical experiments, the contribution of initialization for climate model to predict the seasonal scale AO and its interannual variations is estimated. Results show that the spatial correlation coefficient of AO mode simulated by the decadal experiment is higher than that in the historical experiment. The two groups of experiments reasonably reproduce the characteristics that AO indices are the strongest in winter and the weakest in summer. Compared with historical experiments, the correlation coefficient of the monthly and winter AO indices are higher in the decadal experiments. In particular, the correlation coefficient of monthly AO index between decadal hindcast and observation reached 0.1 significant level. Furthermore, the periodicity of the monthly and spring AO indices are achieved only in the decadal experiments. Therefore, the initial state of model is initialized by using sea temperature data may help to improve the prediction skill of AO in the decadal prediction experiments to some extent.
基金supported by the National Key R&D Program of China (Grant Nos. 2016YFA0602104 and 2016YFA0602102)the National Natural Science Foundation of China (Grant Nos. 41705024, 41575041, 41705039 and 41705076)+2 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA17010105)the Startup Foundation for Introducing Talent of NUIST (Grant No. 2016r060)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘This study focuses on model predictive skill with respect to stratospheric sudden warming(SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF's model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM(ECMWF) is the hindcast initiated two(three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts.
基金supported by the National Basic Research Program of China (973 Program,2010CB951903)the National Natural Science Foundation of China (41105054)the China Meteorological Administration (GYHY200706010)
文摘The historical simulation of phase five of the Coupled Model Intercomparison Project （CMIP5） ex- periments performed by the Beijing Climate Center cli- mate system model （BCC_CSM1.1） is evaluated regard- ing the time evolutions of the global and China mean sur- face air temperature （SAT） and surface climate change over China in recent decades. BCC CSM1.1 has better capability at reproducing the time evolutions of the global and China mean SAT than BCC_CSM1.0. By the year 2005, the BCC_CSM1.1 model simulates a warming am- plitude of approximately I℃ in China over the 1961- 1990 mean, which is consistent with observation. The distributions of the warming trend over China in the four seasons during 1958-2004 are basically reproduced by BCC CSM1.1, with the warmest occurring in winter. Al- though the cooling signal of Southwest China in spring is partly reproduced by BCC_CSM1.1, the cooling trend over central eastern China in summer is omitted by the model. For the precipitation change, BCC_CSM1.1 has good performance in spring, with drought in Southeast China. After removing the linear trend, the interannual correlation map between the model and the observation shows that the model has better capability at reproducing the summer SAT over China and spring precipitation over Southeast China.
