The summer rainfall over the middle-lower reaches of the Yangtze River valley (YRSR) has been estimated with a multi-linear regression model using principal atmospheric modes derived from a 500 hPa geopotential height...The summer rainfall over the middle-lower reaches of the Yangtze River valley (YRSR) has been estimated with a multi-linear regression model using principal atmospheric modes derived from a 500 hPa geopotential height and a 700 hPa zonal vapor flux over the domain of East Asia and the West Pacific.The model was developed using data from 1958 92 and validated with an independent prediction from 1993 2008.The independent prediction was efficient in predicting the YRSR with a correlation coefficient of 0.72 and a relative root mean square error of 18%.The downscaling model was applied to two general circulation models (GCMs) of Flexible Global Ocean-Atmosphere-Land System Model (FGOALS) and Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 (GFDL-CM2.1) to project rainfall for present and future climate under B1 and A1B emission scenarios.The downscaled results pro-vided a closer representation of the observation compared to the raw models in the present climate.In addition,compared to the inconsistent prediction directly from dif-ferent GCMs,the downscaled results provided a consistent projection for this half-century,which indicated a clear increase in the YRSR.Under the B1 emission scenario,the rainfall could increase by an average of 11.9% until 2011 25 and 17.2% until 2036 50 from the current state;under the A1B emission scenario,rainfall could increase by an average of 15.5% until 2011 25 and 25.3% until 2036 50 from the current state.Moreover,the increased rate was faster in the following decade (2011 25) than the latter of this half-century (2036 50) under both emissions.展开更多
A joint statistical-dynamical method addressing both the internal decadal variability and effect of anthropogenic forcing was developed to predict the decadal components of East Asian surface air temperature(EATs)for ...A joint statistical-dynamical method addressing both the internal decadal variability and effect of anthropogenic forcing was developed to predict the decadal components of East Asian surface air temperature(EATs)for three decades(2010–2040).As previous studies have revealed that the internal variability of EATs(EATs_int)is influenced mainly by the ocean,we first analyzed the lead-lag connections between EATs_int and three sea surface temperature(SST)multidecadal modes using instrumental records from 1901 to 1999.Based on the lead-lag connections,a multiple linear regression was constructed with the three SST modes as predictors.The hindcast for the years from 2000 to 2005 indicated the regression model had high skill in simulating the observational EATs_int.Therefore,the prediction for EATs_int(Re_EATs_int)was obtained by the regression model based on quasi-periods of the decadal oceanic modes.External forcing from greenhouse gases is likely associated with global warming.Using monthly global land surface air temperature from historical and projection simulations under the Representative Concentration Pathway(RCP)4.5 scenario of 19 Coupled General Circulation Models participating in the fifth phase of the Coupled Model Intercomparison Project(CMIP5),we predicted the curve of EATs(EATs_trend)relative to1970–1999 by a second-order fit.EATs_int and EATs_trend were combined to form the reconstructed EATs(Re_EATs).It was expected that a fluctuating evolution of Re_EATs would decrease slightly from 2015 to 2030 and increase gradually thereafter.Compared with the decadal prediction in CMIP5 models,Re_EATs was qualitatively in agreement with the predictions of most of the models and the multi-model ensemble mean,indicating that the joint statistical-dynamical approach for EAT is rational.展开更多
基金supported by the National Basic Research Program of China (Grant No.2010CB950400)the National Natural Science Foundation of China (Key Project,Grant No.41030961)the Australia-China Bilateral Climate Change Partnerships Program of the Australian Department of Climate Change
文摘The summer rainfall over the middle-lower reaches of the Yangtze River valley (YRSR) has been estimated with a multi-linear regression model using principal atmospheric modes derived from a 500 hPa geopotential height and a 700 hPa zonal vapor flux over the domain of East Asia and the West Pacific.The model was developed using data from 1958 92 and validated with an independent prediction from 1993 2008.The independent prediction was efficient in predicting the YRSR with a correlation coefficient of 0.72 and a relative root mean square error of 18%.The downscaling model was applied to two general circulation models (GCMs) of Flexible Global Ocean-Atmosphere-Land System Model (FGOALS) and Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 (GFDL-CM2.1) to project rainfall for present and future climate under B1 and A1B emission scenarios.The downscaled results pro-vided a closer representation of the observation compared to the raw models in the present climate.In addition,compared to the inconsistent prediction directly from dif-ferent GCMs,the downscaled results provided a consistent projection for this half-century,which indicated a clear increase in the YRSR.Under the B1 emission scenario,the rainfall could increase by an average of 11.9% until 2011 25 and 17.2% until 2036 50 from the current state;under the A1B emission scenario,rainfall could increase by an average of 15.5% until 2011 25 and 25.3% until 2036 50 from the current state.Moreover,the increased rate was faster in the following decade (2011 25) than the latter of this half-century (2036 50) under both emissions.
基金supported by the National Natural Science Foundation of China(Grant Nos.41375085,41421004)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA05090406)
文摘A joint statistical-dynamical method addressing both the internal decadal variability and effect of anthropogenic forcing was developed to predict the decadal components of East Asian surface air temperature(EATs)for three decades(2010–2040).As previous studies have revealed that the internal variability of EATs(EATs_int)is influenced mainly by the ocean,we first analyzed the lead-lag connections between EATs_int and three sea surface temperature(SST)multidecadal modes using instrumental records from 1901 to 1999.Based on the lead-lag connections,a multiple linear regression was constructed with the three SST modes as predictors.The hindcast for the years from 2000 to 2005 indicated the regression model had high skill in simulating the observational EATs_int.Therefore,the prediction for EATs_int(Re_EATs_int)was obtained by the regression model based on quasi-periods of the decadal oceanic modes.External forcing from greenhouse gases is likely associated with global warming.Using monthly global land surface air temperature from historical and projection simulations under the Representative Concentration Pathway(RCP)4.5 scenario of 19 Coupled General Circulation Models participating in the fifth phase of the Coupled Model Intercomparison Project(CMIP5),we predicted the curve of EATs(EATs_trend)relative to1970–1999 by a second-order fit.EATs_int and EATs_trend were combined to form the reconstructed EATs(Re_EATs).It was expected that a fluctuating evolution of Re_EATs would decrease slightly from 2015 to 2030 and increase gradually thereafter.Compared with the decadal prediction in CMIP5 models,Re_EATs was qualitatively in agreement with the predictions of most of the models and the multi-model ensemble mean,indicating that the joint statistical-dynamical approach for EAT is rational.
