This analysis of the multi-model aerosol optical depth (AOD) in eastern China using the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) datasets shows that the global models underestimate the ...This analysis of the multi-model aerosol optical depth (AOD) in eastern China using the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) datasets shows that the global models underestimate the AOD by 33% and 44% in southern and northern China, respectively, and decrease the relative humidity (RH) of the air in the surface layer to 71%–80%, which is less than the RH of 77%–92% in reanalysis meteorological datasets. This indicates that the low biases in the RH partially account for the errors in the AOD. The AOD is recalculated based on the model aerosol concentrations and the reanalysis humidity data. Improving the mean value of the RH increases the multi-model annual mean AOD by 45% in southern China and by 33% in June–August in northern China. This method of improving the AOD is successful in most of the ACCMIP models, but it is unlikely to be successful in GISS-E2-R, in which the plot of its AOD efficiency against RH strongly deviates from the rest of the models. The effect of the improvement in the modeled RH on the AOD depends on the concentration of aerosols. The shape error in the frequency distribution of the RH is likely to be more important than the error in the mean value of the RH, but this requires further research.展开更多
Five General Circulation Model(GCM) climate projections under the RCP8.5 emission scenario were used to drive the Variable Infiltration Capacity(VIC) hydrologic model to investigate the impacts of climate change on hy...Five General Circulation Model(GCM) climate projections under the RCP8.5 emission scenario were used to drive the Variable Infiltration Capacity(VIC) hydrologic model to investigate the impacts of climate change on hydrologic cycle over continental China in the 21 st century. The bias-corrected climatic variables were generated for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change(IPCC AR5) by the Inter-Sectoral Impact Model Intercomparison Project(ISIMIP). Results showed much larger fractional changes of annual mean Evapotranspiration(ET) per unit warming than the corresponding fractional changes of Precipitation(P) per unit warming across the country, especially for South China, which led to a notable decrease of surface water variability(P-E). Specifically, negative trends for annual mean runoff up to -0.33%/ year and soil moisture trends varying between -0.02% to -0.13%/year were found for most river basins across China. Coincidentally, interannual variability for both runoff and soil moisture exhibited significant positive trends for almost all river basins across China, implying an increase in extremes relative to the mean conditions. Noticeably, the largest positive trends for runoff variability and soil moisture variability, which were up to 0.41%/year and 0.90%/year, both occurred in Southwest China. In addition to the regional contrast, intra-seasonal variation was also large for the runoff mean and runoff variability changes, but small for the soil moisture mean and variability changes. Our results suggest that future climate change could further exacerbate existing water-related risks(e.g., floods and droughts) across China as indicated by the marked decrease of surface water amounts combined with a steady increase of interannual variability throughout the 21 st century. This study highlights the regional contrast and intra-seasonal variations for the projected hydrologic changes and could provide a multi-scale guidance for assessing effective adaptation strategies for China on a river basin, regional, or as a whole.展开更多
基金jointly supported by the National Key Research and Development Program of China [grant number2016YFE0201400]the Basic Research Program of the State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry,Institute of Atmospheric Physics,Chinese Academy of Sciences [grant number 7-082999]
文摘This analysis of the multi-model aerosol optical depth (AOD) in eastern China using the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) datasets shows that the global models underestimate the AOD by 33% and 44% in southern and northern China, respectively, and decrease the relative humidity (RH) of the air in the surface layer to 71%–80%, which is less than the RH of 77%–92% in reanalysis meteorological datasets. This indicates that the low biases in the RH partially account for the errors in the AOD. The AOD is recalculated based on the model aerosol concentrations and the reanalysis humidity data. Improving the mean value of the RH increases the multi-model annual mean AOD by 45% in southern China and by 33% in June–August in northern China. This method of improving the AOD is successful in most of the ACCMIP models, but it is unlikely to be successful in GISS-E2-R, in which the plot of its AOD efficiency against RH strongly deviates from the rest of the models. The effect of the improvement in the modeled RH on the AOD depends on the concentration of aerosols. The shape error in the frequency distribution of the RH is likely to be more important than the error in the mean value of the RH, but this requires further research.
基金supported by the National Natural Science Foundation of China(Grant No.41171031)National Basic Research Program of China(Grant No.2012CB955403)+3 种基金Hundred Talents Program of the Chinese Academy of Sciences conducted under the framework of ISI-MIPThe ISIMIP Fast Track Project was funded by the German Federal Ministry of Education and Research(BMBF)(Grant No.01LS1201A)supported by Office of Science of the U.S.Department of Energy through the Regional and Global Climate Modeling ProgramPNNL is operated for the US DOE by Battelle Memorial Institute(Grant No.DE-AC05-76RL01830)
文摘Five General Circulation Model(GCM) climate projections under the RCP8.5 emission scenario were used to drive the Variable Infiltration Capacity(VIC) hydrologic model to investigate the impacts of climate change on hydrologic cycle over continental China in the 21 st century. The bias-corrected climatic variables were generated for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change(IPCC AR5) by the Inter-Sectoral Impact Model Intercomparison Project(ISIMIP). Results showed much larger fractional changes of annual mean Evapotranspiration(ET) per unit warming than the corresponding fractional changes of Precipitation(P) per unit warming across the country, especially for South China, which led to a notable decrease of surface water variability(P-E). Specifically, negative trends for annual mean runoff up to -0.33%/ year and soil moisture trends varying between -0.02% to -0.13%/year were found for most river basins across China. Coincidentally, interannual variability for both runoff and soil moisture exhibited significant positive trends for almost all river basins across China, implying an increase in extremes relative to the mean conditions. Noticeably, the largest positive trends for runoff variability and soil moisture variability, which were up to 0.41%/year and 0.90%/year, both occurred in Southwest China. In addition to the regional contrast, intra-seasonal variation was also large for the runoff mean and runoff variability changes, but small for the soil moisture mean and variability changes. Our results suggest that future climate change could further exacerbate existing water-related risks(e.g., floods and droughts) across China as indicated by the marked decrease of surface water amounts combined with a steady increase of interannual variability throughout the 21 st century. This study highlights the regional contrast and intra-seasonal variations for the projected hydrologic changes and could provide a multi-scale guidance for assessing effective adaptation strategies for China on a river basin, regional, or as a whole.
