In this study, a method of analogue-based correction of errors(ACE) was introduced to improve El Ni?o-Southern Oscillation(ENSO) prediction produced by climate models. The ACE method is based on the hypothesis that th...In this study, a method of analogue-based correction of errors(ACE) was introduced to improve El Ni?o-Southern Oscillation(ENSO) prediction produced by climate models. The ACE method is based on the hypothesis that the flow-dependent model prediction errors are to some degree similar under analogous historical climate states, and so the historical errors can be used to effectively reduce such flow-dependent errors. With this method, the unknown errors in current ENSO predictions can be empirically estimated by using the known prediction errors which are diagnosed by the same model based on historical analogue states. The authors first propose the basic idea for applying the ACE method to ENSO prediction and then establish an analogue-dynamical ENSO prediction system based on an operational climate prediction model. The authors present some experimental results which clearly show the possibility of correcting the flow-dependent errors in ENSO prediction, and thus the potential of applying the ACE method to operational ENSO prediction based on climate models.展开更多
El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate worldwide.In the past,extensive an...El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate worldwide.In the past,extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies.A hierarchy of coupled ocean-atmo sphere models has been formulated;in terms of their complexity,they can be categorized into intermediate coupled models(ICMs),hybrid coupled models(HCMs),and fully coupled general circulation models(CGCMs).ENSO modeling has made significant progress over the past decades,reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in advance.Meanwhile,ENSO exhibits great diversity and complexity as observed in nature,which still cannot be adequately captured by current state-of-the-art coupled models,presenting a challenge to ENSO modeling.We primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China;some selected representative examples are presented here to review the current status of ENSO model developments and applications,which have been actively pursued with noticeable progress being made recently.As ENSO simulations are very sensitive to model formulations and process representations etc.,dedicated efforts have been devoted to ENSO model developments and improvements.Now,different ocean-atmosphere coupled models have been available in China,which exhibit good model performances and have already had a variety of applications to climate modeling,including the Coupled Model Intercomparison Project Phase 6(CMIP6).Nevertheless,large biases and uncertainties still exist in ENSO simulations and predictions,and there are clear rooms for their improvements,which are still an active area of researches and applications.Here,model performances of ENSO simulations are assessed in terms of advantages and disadvantages with these differently formulated coupled models,pinpointing to the areas where they need to be further improved for ENSO studies.These analyses provide valuable guidance for future improvements in ENSO simulations and predictions.展开更多
The temporal variability and spatial pattern of the Arctic Oscillation(AO)simulated in the historical experiment of26 coupled climate models participating in the Coupled Model Intercomparison Project Phase 5(CMIP5)are...The temporal variability and spatial pattern of the Arctic Oscillation(AO)simulated in the historical experiment of26 coupled climate models participating in the Coupled Model Intercomparison Project Phase 5(CMIP5)are evaluated.Spectral analysis of the monthly AO index indicates that 23 out of the 26 CMIP5 models exhibit no statistically significant spectral peak in the historical experiment,as seen in the observations.These models are able to reproduce the AO pattern in the sea level pressure anomaly field during boreal winter,but the intensity of the AO pattern tends to be overestimated in all the models.The zonal-mean zonal wind anomalies associated with the AO is dominated by a meridional dipole in the mid-high latitudes of the Northern Hemisphere during boreal winter,which is well reproduced by only a few models.Most models show significant biases in both strength and location of the dipole compared to the observation.In considering the temporal variability as well as spatial structures in both horizontal and vertical directions,the MPI-ESM-P model reproduces an AO pattern that resembles the observation the best.展开更多
This study investigates the relationship between summer low-frequency rainfall over southern China and tropical intraseasonal oscillation(ISO) in the atmosphere by examining systematically the propagation features of ...This study investigates the relationship between summer low-frequency rainfall over southern China and tropical intraseasonal oscillation(ISO) in the atmosphere by examining systematically the propagation features of the tropical ISO in terms of focusing on five large-scale low-frequency rainfall regimes in summer over southern China. It is demonstrated that there is a close linkage between the five rainfall regimes over southern China and the northward propagation of the tropical ISO. The moist ISO signals, which influence the low-frequency rainfall events in different regions of southern China, mainly propagate northwestward from the tropical ocean to the southeast of China. The southeast China rainfall regime is intimately associated with the moist ISO signals propagating northwestward from the equatorial mid-western Pacific Ocean. For both the Yangtze River regime and South of Yangtze River regime, the moist ISO signals over the northern South China Sea show an evident northward propagation towards the Yangtze River region, and then propagate westward. It is further found that the interaction between the northward propagation of low-latitude ISO signals and the southward propagation of high-latitude ISO signals can also make a clear influence on the low-frequency rainfall in southern China. For the Southern China regime, the moist ISO signals show a significant northward propagation from the Philippines. Moreover, for the rainless regime, southern China is under dry ISO signals' control, and the latter shows no clear propagation to southern China. This study may provide insights for the extended-range forecasting of summer rainfall in southern China.展开更多
基金jointly supported by the National Basic Research Program of China(973 Program,Grant No.2015CB453203)the China Meteorological Special Project(Grant No.GYHY201406022)the LCS/CMA Open Funds for Young Scholars(2014)
基金supported by the Integration and Application Project for Key Meteorology Techniques in China Meteorological Administration (Grant No. CMAGJ2014M64)the China Meteorological Special Project (Grant No. GYHY2012 06016)the National Basic Research Program of China (973 Program, Grant No. 2010CB950404)
文摘In this study, a method of analogue-based correction of errors(ACE) was introduced to improve El Ni?o-Southern Oscillation(ENSO) prediction produced by climate models. The ACE method is based on the hypothesis that the flow-dependent model prediction errors are to some degree similar under analogous historical climate states, and so the historical errors can be used to effectively reduce such flow-dependent errors. With this method, the unknown errors in current ENSO predictions can be empirically estimated by using the known prediction errors which are diagnosed by the same model based on historical analogue states. The authors first propose the basic idea for applying the ACE method to ENSO prediction and then establish an analogue-dynamical ENSO prediction system based on an operational climate prediction model. The authors present some experimental results which clearly show the possibility of correcting the flow-dependent errors in ENSO prediction, and thus the potential of applying the ACE method to operational ENSO prediction based on climate models.
基金the National Key Research and Development Program of China (Nos.2017YFC1404102,2017YFC1404100)the Strategic Priority Research Program of Chinese Academy of Sciences (Nos.XDB 40000000,XDB 42000000)+4 种基金the National Natural Science Foundation of China (Nos.41690122(41690120),41705082,41421005)the Shandong Taishan Scholarship,the China Postdoctoral Science Foundation (Nos.2018M640659,2019M662453)YU Yongqiang is jointly supported by the Strategic Priority Research Program of Chinese Academy of Sciences (Nos.XDA 19060102.XDB 42000000)REN Hong-Li is jointly supported by the China National Science Foundation (No.41975094)the China National Key Research and Development Program on Monitoring,Early Warning and Prevention of Major Natural Disaster (No.2018YFC1506004)
文摘El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate worldwide.In the past,extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies.A hierarchy of coupled ocean-atmo sphere models has been formulated;in terms of their complexity,they can be categorized into intermediate coupled models(ICMs),hybrid coupled models(HCMs),and fully coupled general circulation models(CGCMs).ENSO modeling has made significant progress over the past decades,reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in advance.Meanwhile,ENSO exhibits great diversity and complexity as observed in nature,which still cannot be adequately captured by current state-of-the-art coupled models,presenting a challenge to ENSO modeling.We primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China;some selected representative examples are presented here to review the current status of ENSO model developments and applications,which have been actively pursued with noticeable progress being made recently.As ENSO simulations are very sensitive to model formulations and process representations etc.,dedicated efforts have been devoted to ENSO model developments and improvements.Now,different ocean-atmosphere coupled models have been available in China,which exhibit good model performances and have already had a variety of applications to climate modeling,including the Coupled Model Intercomparison Project Phase 6(CMIP6).Nevertheless,large biases and uncertainties still exist in ENSO simulations and predictions,and there are clear rooms for their improvements,which are still an active area of researches and applications.Here,model performances of ENSO simulations are assessed in terms of advantages and disadvantages with these differently formulated coupled models,pinpointing to the areas where they need to be further improved for ENSO studies.These analyses provide valuable guidance for future improvements in ENSO simulations and predictions.
基金supported by the National Basic Research Program of China(No.2010CB950501&2010CB950404)the National Natural Science Foundation of China(No.41205058)the China Postdoctoral Sci-ence Foundation(No.2012M510634)
文摘The temporal variability and spatial pattern of the Arctic Oscillation(AO)simulated in the historical experiment of26 coupled climate models participating in the Coupled Model Intercomparison Project Phase 5(CMIP5)are evaluated.Spectral analysis of the monthly AO index indicates that 23 out of the 26 CMIP5 models exhibit no statistically significant spectral peak in the historical experiment,as seen in the observations.These models are able to reproduce the AO pattern in the sea level pressure anomaly field during boreal winter,but the intensity of the AO pattern tends to be overestimated in all the models.The zonal-mean zonal wind anomalies associated with the AO is dominated by a meridional dipole in the mid-high latitudes of the Northern Hemisphere during boreal winter,which is well reproduced by only a few models.Most models show significant biases in both strength and location of the dipole compared to the observation.In considering the temporal variability as well as spatial structures in both horizontal and vertical directions,the MPI-ESM-P model reproduces an AO pattern that resembles the observation the best.
基金jointly supported by the China Meteorological Special Projects[grant number GYHY201506013]the National Basic Reaseach Program of China(973)[grant number2015CB453203]+1 种基金the National Natural Science Foundation of China[grant numbers 41405080 and 41375062]partly supported by the UK-China Research&Innovation Partnership Fund through the Met Office Climate Science for Service Partnership China as part of the Newton Fund
基金973 Program of China(2015CB453203,2013CB430203)China Meteorological Special Project(GYHY201406022)China National Science Foundation(41505065,41375062)
文摘This study investigates the relationship between summer low-frequency rainfall over southern China and tropical intraseasonal oscillation(ISO) in the atmosphere by examining systematically the propagation features of the tropical ISO in terms of focusing on five large-scale low-frequency rainfall regimes in summer over southern China. It is demonstrated that there is a close linkage between the five rainfall regimes over southern China and the northward propagation of the tropical ISO. The moist ISO signals, which influence the low-frequency rainfall events in different regions of southern China, mainly propagate northwestward from the tropical ocean to the southeast of China. The southeast China rainfall regime is intimately associated with the moist ISO signals propagating northwestward from the equatorial mid-western Pacific Ocean. For both the Yangtze River regime and South of Yangtze River regime, the moist ISO signals over the northern South China Sea show an evident northward propagation towards the Yangtze River region, and then propagate westward. It is further found that the interaction between the northward propagation of low-latitude ISO signals and the southward propagation of high-latitude ISO signals can also make a clear influence on the low-frequency rainfall in southern China. For the Southern China regime, the moist ISO signals show a significant northward propagation from the Philippines. Moreover, for the rainless regime, southern China is under dry ISO signals' control, and the latter shows no clear propagation to southern China. This study may provide insights for the extended-range forecasting of summer rainfall in southern China.
