This paper describes a dynamical downscaling simulation over China using the nested model system,which consists of the modified Weather Research and Forecasting Model(WRF)nested with the NCAR Community Atmosphere Mode...This paper describes a dynamical downscaling simulation over China using the nested model system,which consists of the modified Weather Research and Forecasting Model(WRF)nested with the NCAR Community Atmosphere Model(CAM).Results show that dynamical downscaling is of great value in improving the model simulation of regional climatic characteristics.WRF simulates regional detailed temperature features better than CAM.With the spatial correlation coefficient between the observation and the simulation increasing from 0.54 for CAM to 0.79 for WRF,the improvement in precipitation simulation is more perceptible with WRF.Furthermore,the WRF simulation corrects the spatial bias of the precipitation in the CAM simulation.展开更多
The 21-yr ensemble predictions of model precipitation and circulation in the East Asian and western North Pacific （Asia-Pacific） summer monsoon region （0°-50°N, 100° 150°E） were evaluated in ni...The 21-yr ensemble predictions of model precipitation and circulation in the East Asian and western North Pacific （Asia-Pacific） summer monsoon region （0°-50°N, 100° 150°E） were evaluated in nine different AGCM, used in the Asia-Pacific Economic Cooperation Climate Center （APCC） multi-model ensemble seasonal prediction system. The analysis indicates that the precipitation anomaly patterns of model ensemble predictions are substantially different from the observed counterparts in this region, but the summer monsoon circulations are reasonably predicted. For example, all models can well produce the interannual variability of the western North Pacific monsoon index （WNPMI） defined by 850 hPa winds, but they failed to predict the relationship between WNPMI and precipitation anomalies. The interannual variability of the 500 hPa geopotential height （GPH） can be well predicted by the models in contrast to precipitation anomalies. On the basis of such model performances and the relationship between the interannual variations of 500 hPa GPH and precipitation anomalies, we developed a statistical scheme used to downscale the summer monsoon precipitation anomaly on the basis of EOF and singular value decomposition （SVD）. In this scheme, the three leading EOF modes of 500 hPa GPH anomaly fields predicted by the models are firstly corrected by the linear regression between the principal components in each model and observation, respectively. Then, the corrected model GPH is chosen as the predictor to downscale the precipitation anomaly field, which is assembled by the forecasted expansion coefficients of model 500 hPa GPH and the three leading SVD modes of observed precipitation anomaly corresponding to the prediction of model 500 hPa GPH during a 19-year training period. The cross-validated forecasts suggest that this downscaling scheme may have a potential to improve the forecast skill of the precipitation anomaly in the South China Sea, western North Pacific and the East Asia Pacific regions, wh展开更多
借助大气环流模式(GCMs)进行区域气候影响评价往往受气候模式的分辨率限制,缺少对应尺度的气候情景,目前一般的做法是通过降尺度方法弥补GCMs气候情景的不足。本文集成GCMs输出数据、降尺度模型和分布式水文模型SWAT(Soil and Water Ana...借助大气环流模式(GCMs)进行区域气候影响评价往往受气候模式的分辨率限制,缺少对应尺度的气候情景,目前一般的做法是通过降尺度方法弥补GCMs气候情景的不足。本文集成GCMs输出数据、降尺度模型和分布式水文模型SWAT(Soil and Water Analysis Tool)建立了气候-陆面单向连接系统。将未来气候情景(日降水量、最高和最低气温情景),输入到SWAT模型模拟径流,重点预测评估黄河源区未来不同时期的径流变化情况,并分析讨论气候变化情景下径流深的空间分布及响应。其结果表明,SWAT模型可以较好地模拟黄河源区的流量过程,未来气候变化对黄河源区径流量变化影响很大,而且不同的降尺度情景对模拟结果会产生不同的影响。统计降尺度(SDS)情景模拟表明,黄河源区未来径流量的减少趋势不可避免,未来3个时期(2020s、2050s和2080s)将分别减少88.61m3/(s24.15%)、116.64m3/(s31.79%)和151.62m3/(s41.33%),而Delta情景下研究区年平均流量变化相对较小,与基准期相比未来2020s和2050s分别减少63.69m3/s(17.36%)和1.73m3/s(0.47%),而2080s将增加46.93m3/(s12.79%)。展开更多
In this paper we demonstrate the need for risk-adjusted approaches to planning expansion of livestock production. In particular, we illustrate that under exposure to risk, a portfolio of producers is needed where more...In this paper we demonstrate the need for risk-adjusted approaches to planning expansion of livestock production. In particular, we illustrate that under exposure to risk, a portfolio of producers is needed where more efficient producers co-exist and cooperate with less efficient ones given that the latter are associated with lower, uncorre, lated or even negatively correlated contingencies. This raises important issues of cooperation and risk sharing among diverse producers. For large-scale practical allocation problems when information on the contingencies may be disperse, not analytically tractable, or be available on aggregate levels, we propose a downscaling procedure based on behavioral principles utilizing spatial risk preference structure, It allows for estimation of production allocation at required resolutions accounting for location specific risks and suitability constraints. The approach provides a tool for harmonization of data from various spatial levels. We applied the method in a case study of livestock production allocation in China to 2030.展开更多
Multi-decadal high resolution simulations over the CORDEX East Asia domain were performed with the regional climate model RegCM3 nested within the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version...Multi-decadal high resolution simulations over the CORDEX East Asia domain were performed with the regional climate model RegCM3 nested within the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 （FGOALS-g2）. Two sets of simulations were conducted at the resolution of 50 km, one for present day （1980-2005） and another for near-future climate （2015-40） under the Representative Concentration Pathways 8.5 （RCP8.5） scenario. Results show that RegCM3 adds value with respect to FGOALS-g2 in simulating the spatial patterns of summer total and extreme precipitation over China for present day climate. The major deficiency is that RegCM3 underestimates both total and extreme precipi- tation over the Yangtze River valley. The potential changes in total and extreme precipitation over China in summer under the RCP8.5 scenario were analyzed. Both RegCM3 and FGOALS-g2 results show that total and extreme precipitation tend to increase over northeastern China and the Tibetan Plateau, but tend to decrease over southeastern China. In both RegCM3 and FGOALS-g2, the change in extreme precipitation is weaker than that for total precipitation. RegCM3 projects much stronger amplitude of total and extreme precipitation changes and provides more regional-scale features than FGOALS-g2. A large uncertainty is found over the Yangtze River valley, where RegCM3 and FGOALS-g2 project opposite signs in terms of precipitation changes. The projected change of vertically integrated water vapor flux convergence generally follows the changes in total and extreme precipitation in both RegCM3 and FGOALS-g2, while the amplitude of change is stronger in RegCM3. Results suggest that the spatial pattern of projected precipitation changes may be more affected by the changes in water vapor flux convergence, rather than moisture content itself.展开更多
While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial ac...While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial accuracy. This is particularly true for research focused on the evaluation of adaptive forest management strategies. In this study, we developed an application, Climate AP, to generate scale-free(i.e., specific to point locations) climate data for historical(1901–2015) and future(2011–2100)years and periods. Climate AP uses the best available interpolated climate data for the reference period 1961–1990 as baseline data. It downscales the baseline data from a moderate spatial resolution to scale-free point data through dynamic local elevation adjustments. It also integrates and downscales the historical and future climate data using a delta approach. In the case of future climate data, two greenhouse gas representative concentration pathways(RCP 4.5 and 8.5) and 15 general circulation models are included to allow for the assessment of alternative climate scenarios. In addition, Climate AP generates a large number of biologically relevant climate variables derived from primary monthly variables. The effectiveness of the local downscaling was determined based on the strength of the local linear regression for the estimate of lapse rate. The accuracy of the Climate AP output was evaluated through comparisons of Climate AP output against observations from 1805 weather stations in the Asia Pacific region. The local linear regression explained 70%–80% and 0%–50% of the total variation in monthly temperatures and precipitation, respectively, in most cases. Climate AP reduced prediction error by up to27% and 60% for monthly temperature and precipitation,respectively, relative to the original baselines data. The improvements for baseline portions of historical and futurewere more substantial. Applications and limitations of the software are discussed.展开更多
Forest ecosystems play an important role in the global carbon cycle.The implementation of the United Nations Framework Convention on Climate Change(UNFCCC) and the Kyoto Protocol has made the study of forest ecosystem...Forest ecosystems play an important role in the global carbon cycle.The implementation of the United Nations Framework Convention on Climate Change(UNFCCC) and the Kyoto Protocol has made the study of forest ecosystem carbon cycling a hot topic of scientific research globally.This paper utilized Chinese national forest inventory data sets(for the periods 1984-1988 and 1999-2003),the vegetation map of China(1:1000000),and the spatially explicit net primary productivity(NPP) data sets derived with the remote sensing-based light use efficiency model(CASA model).We quantitatively estimated the spatial distribution of carbon sinks and sources of forest vegetation(with a resolution of 1 km) using the spatial downscaling technique.During the period 1984 to 2003 the forest vegetation in China represented a carbon sink.The total storage of carbon increased by 0.77 PgC,with a mean of 51.0TgCa 1.The total carbon sink was 0.88PgC and carbon source was 0.11 PgC during the study period.The carbon sink and carbon source of forest vegetation in China showed a clear spatial distribution pattern.Carbon sinks were mainly located in subtropical and temperate regions,with the highest values in Hainan Province,Hengduan mountain ranges,Changbai mountain ranges in Jilin,and south and northwest of the Da Hinggan Mountains;carbon sources were mainly distributed from the northeast to southwestern areas in China,with the highest values mainly concentrated in southern Yunnan Province,central Sichuan Basin,and northern Da Hinggan Mountains.Increase in NPP was strongly correlated with carbon sink strength.The regression model showed that more than 80% of the variation in the modeled carbon sinks in Northeast,Northern,Northwest and Southern China were explained by the variation in NPP increase.There was a strong relationship between carbon sink strength and forest stand age.展开更多
The spatial resolution of general circulation models （GCMs） is too coarse to represent regional climate variations at the regional, basin, and local scales required for many environmental modeling and impact assessm...The spatial resolution of general circulation models （GCMs） is too coarse to represent regional climate variations at the regional, basin, and local scales required for many environmental modeling and impact assessments. Weather research and forecasting model （WRF） is a nextgeneration, fully compressible, Euler non-hydrostatic mesoscale forecast model with a runtime hydrostatic option. This model is useful for downscaling weather and climate at the scales from one kilometer to thousands of kilometers, and is useful for deriving meteorological parameters required for hydrological simulation too. The objective of this paper is to validate WRF simulating 5 km/ 1 h air temperatures by daily observed data of China Meteorological Administration （CMA） stations, and by hourly in-situ data of the Watershed Allied Telemetry Experimental Research Project. The daily validation shows that the WRF simulation has good agreement with the observed data; the R2 between the WRF simulation and each station is more than 0.93; the absolute of meanbias error （MBE） for each station is less than 2℃; and the MBEs of Ejina, Mazongshan and Alxa stations are near zero, with R2 is more than 0.98, which can be taken as an unbiased estimation. The hourly validation shows that the WRF simulation can capture the basic trend of observed data, the MBE of each site is approximately 2℃, the R2 of each site is more than 0.80, with the highest at 0.95, and the computed and observed surface air temperature series show a significantly similar trend.展开更多
The climate impact studies in hydrology often rely on climate change information at fine spatial resolution. However, the general circulation model (GCM), which is widely used to simulate future climate scenario, oper...The climate impact studies in hydrology often rely on climate change information at fine spatial resolution. However, the general circulation model (GCM), which is widely used to simulate future climate scenario, operates on a coarse scale and does not provide reliable data on local or regional scale for hydrological modeling. Therefore the outputs from GCM have to be downscaled to obtain the information fit for hydrologic studies. The variable infiltration capacity (VIC) distributed hydrological model with 9×9 km2 grid resolution was applied and calibrated in the Hanjiang Basin. Validation results show that SSVM can approximate observed precipitation and temperature data reasonably well, and that the VIC model can simulate runoff hydrograph with high model efficiency and low relative error. By applying the SSVM model, the trends of precipitation and temperature (including daily mean temperature, daily maximum temperature and daily minimum temperature) projected from CGCM2 under A2 and B2 scenarios will decrease in the 2020s (2011―2040), and increase in the 2080s (2071―2100). However, in the 2050s (2041―2070), the precipitation will be decreased under A2 scenario and no significant changes under B2 scenario, but the temperature will be not obviously changed under both climate change scenarios. Under both climate change scenarios, the impact analysis of runoff, made with the downscaled precipitation and temperature time series as input of the VIC distributed model, has resulted in a decreasing trend for the 2020s and 2050s, and an overall increasing trend for the 2080s.展开更多
基金supported by the Special Fund for Public Welfare Industry (meteorology) (Grant No. GYHY200906018)the National Basic Research Program of China (973 Program) (Grant No. 2009CB421406)the National Natural Science Foundation of China (Grant Nos. 40875048 and 40821092)
文摘This paper describes a dynamical downscaling simulation over China using the nested model system,which consists of the modified Weather Research and Forecasting Model(WRF)nested with the NCAR Community Atmosphere Model(CAM).Results show that dynamical downscaling is of great value in improving the model simulation of regional climatic characteristics.WRF simulates regional detailed temperature features better than CAM.With the spatial correlation coefficient between the observation and the simulation increasing from 0.54 for CAM to 0.79 for WRF,the improvement in precipitation simulation is more perceptible with WRF.Furthermore,the WRF simulation corrects the spatial bias of the precipitation in the CAM simulation.
基金The National Nat-ural Science Foundation of China (NSFC), Grant Nos.90711003, 40375014the program of GYHY200706005, and the APCC Visiting Scientist Program jointly supportedthis work.
文摘The 21-yr ensemble predictions of model precipitation and circulation in the East Asian and western North Pacific （Asia-Pacific） summer monsoon region （0°-50°N, 100° 150°E） were evaluated in nine different AGCM, used in the Asia-Pacific Economic Cooperation Climate Center （APCC） multi-model ensemble seasonal prediction system. The analysis indicates that the precipitation anomaly patterns of model ensemble predictions are substantially different from the observed counterparts in this region, but the summer monsoon circulations are reasonably predicted. For example, all models can well produce the interannual variability of the western North Pacific monsoon index （WNPMI） defined by 850 hPa winds, but they failed to predict the relationship between WNPMI and precipitation anomalies. The interannual variability of the 500 hPa geopotential height （GPH） can be well predicted by the models in contrast to precipitation anomalies. On the basis of such model performances and the relationship between the interannual variations of 500 hPa GPH and precipitation anomalies, we developed a statistical scheme used to downscale the summer monsoon precipitation anomaly on the basis of EOF and singular value decomposition （SVD）. In this scheme, the three leading EOF modes of 500 hPa GPH anomaly fields predicted by the models are firstly corrected by the linear regression between the principal components in each model and observation, respectively. Then, the corrected model GPH is chosen as the predictor to downscale the precipitation anomaly field, which is assembled by the forecasted expansion coefficients of model 500 hPa GPH and the three leading SVD modes of observed precipitation anomaly corresponding to the prediction of model 500 hPa GPH during a 19-year training period. The cross-validated forecasts suggest that this downscaling scheme may have a potential to improve the forecast skill of the precipitation anomaly in the South China Sea, western North Pacific and the East Asia Pacific regions, wh
文摘借助大气环流模式(GCMs)进行区域气候影响评价往往受气候模式的分辨率限制,缺少对应尺度的气候情景,目前一般的做法是通过降尺度方法弥补GCMs气候情景的不足。本文集成GCMs输出数据、降尺度模型和分布式水文模型SWAT(Soil and Water Analysis Tool)建立了气候-陆面单向连接系统。将未来气候情景(日降水量、最高和最低气温情景),输入到SWAT模型模拟径流,重点预测评估黄河源区未来不同时期的径流变化情况,并分析讨论气候变化情景下径流深的空间分布及响应。其结果表明,SWAT模型可以较好地模拟黄河源区的流量过程,未来气候变化对黄河源区径流量变化影响很大,而且不同的降尺度情景对模拟结果会产生不同的影响。统计降尺度(SDS)情景模拟表明,黄河源区未来径流量的减少趋势不可避免,未来3个时期(2020s、2050s和2080s)将分别减少88.61m3/(s24.15%)、116.64m3/(s31.79%)和151.62m3/(s41.33%),而Delta情景下研究区年平均流量变化相对较小,与基准期相比未来2020s和2050s分别减少63.69m3/s(17.36%)和1.73m3/s(0.47%),而2080s将增加46.93m3/(s12.79%)。
文摘In this paper we demonstrate the need for risk-adjusted approaches to planning expansion of livestock production. In particular, we illustrate that under exposure to risk, a portfolio of producers is needed where more efficient producers co-exist and cooperate with less efficient ones given that the latter are associated with lower, uncorre, lated or even negatively correlated contingencies. This raises important issues of cooperation and risk sharing among diverse producers. For large-scale practical allocation problems when information on the contingencies may be disperse, not analytically tractable, or be available on aggregate levels, we propose a downscaling procedure based on behavioral principles utilizing spatial risk preference structure, It allows for estimation of production allocation at required resolutions accounting for location specific risks and suitability constraints. The approach provides a tool for harmonization of data from various spatial levels. We applied the method in a case study of livestock production allocation in China to 2030.
基金supported by the National Natural Science Foundation of China(Grant Nos.41205080 and 41023002)National Program on Key Basic Research Project of China(2013CB956204)+2 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA05110301)China R&D Special Fund for Public Welfare Industry(meteorology)(GYHY201306019)Public Science and Technology Research Funds(Projects of Ocean Grant No.201105019-3)
文摘Multi-decadal high resolution simulations over the CORDEX East Asia domain were performed with the regional climate model RegCM3 nested within the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 （FGOALS-g2）. Two sets of simulations were conducted at the resolution of 50 km, one for present day （1980-2005） and another for near-future climate （2015-40） under the Representative Concentration Pathways 8.5 （RCP8.5） scenario. Results show that RegCM3 adds value with respect to FGOALS-g2 in simulating the spatial patterns of summer total and extreme precipitation over China for present day climate. The major deficiency is that RegCM3 underestimates both total and extreme precipi- tation over the Yangtze River valley. The potential changes in total and extreme precipitation over China in summer under the RCP8.5 scenario were analyzed. Both RegCM3 and FGOALS-g2 results show that total and extreme precipitation tend to increase over northeastern China and the Tibetan Plateau, but tend to decrease over southeastern China. In both RegCM3 and FGOALS-g2, the change in extreme precipitation is weaker than that for total precipitation. RegCM3 projects much stronger amplitude of total and extreme precipitation changes and provides more regional-scale features than FGOALS-g2. A large uncertainty is found over the Yangtze River valley, where RegCM3 and FGOALS-g2 project opposite signs in terms of precipitation changes. The projected change of vertically integrated water vapor flux convergence generally follows the changes in total and extreme precipitation in both RegCM3 and FGOALS-g2, while the amplitude of change is stronger in RegCM3. Results suggest that the spatial pattern of projected precipitation changes may be more affected by the changes in water vapor flux convergence, rather than moisture content itself.
基金funded by a research grant"Adaptation of Asia-Pacific Forests to Climate Change"(APFNet/2010/PPF/001)funded by the Asia-Pacific Network for Sustainable Forest Management and Rehabilitation
文摘While low-to-moderate resolution gridded climate data are suitable for climate-impact modeling at global and ecosystems levels, spatial analyses conducted at local scales require climate data with increased spatial accuracy. This is particularly true for research focused on the evaluation of adaptive forest management strategies. In this study, we developed an application, Climate AP, to generate scale-free(i.e., specific to point locations) climate data for historical(1901–2015) and future(2011–2100)years and periods. Climate AP uses the best available interpolated climate data for the reference period 1961–1990 as baseline data. It downscales the baseline data from a moderate spatial resolution to scale-free point data through dynamic local elevation adjustments. It also integrates and downscales the historical and future climate data using a delta approach. In the case of future climate data, two greenhouse gas representative concentration pathways(RCP 4.5 and 8.5) and 15 general circulation models are included to allow for the assessment of alternative climate scenarios. In addition, Climate AP generates a large number of biologically relevant climate variables derived from primary monthly variables. The effectiveness of the local downscaling was determined based on the strength of the local linear regression for the estimate of lapse rate. The accuracy of the Climate AP output was evaluated through comparisons of Climate AP output against observations from 1805 weather stations in the Asia Pacific region. The local linear regression explained 70%–80% and 0%–50% of the total variation in monthly temperatures and precipitation, respectively, in most cases. Climate AP reduced prediction error by up to27% and 60% for monthly temperature and precipitation,respectively, relative to the original baselines data. The improvements for baseline portions of historical and futurewere more substantial. Applications and limitations of the software are discussed.
基金supported by the National Basic Research Program of China (2012CB955401)the National Natural Science Foundation of China (30970514 and 30590384)the New Century Excellent Talents in University (NCET-10-0251)
文摘Forest ecosystems play an important role in the global carbon cycle.The implementation of the United Nations Framework Convention on Climate Change(UNFCCC) and the Kyoto Protocol has made the study of forest ecosystem carbon cycling a hot topic of scientific research globally.This paper utilized Chinese national forest inventory data sets(for the periods 1984-1988 and 1999-2003),the vegetation map of China(1:1000000),and the spatially explicit net primary productivity(NPP) data sets derived with the remote sensing-based light use efficiency model(CASA model).We quantitatively estimated the spatial distribution of carbon sinks and sources of forest vegetation(with a resolution of 1 km) using the spatial downscaling technique.During the period 1984 to 2003 the forest vegetation in China represented a carbon sink.The total storage of carbon increased by 0.77 PgC,with a mean of 51.0TgCa 1.The total carbon sink was 0.88PgC and carbon source was 0.11 PgC during the study period.The carbon sink and carbon source of forest vegetation in China showed a clear spatial distribution pattern.Carbon sinks were mainly located in subtropical and temperate regions,with the highest values in Hainan Province,Hengduan mountain ranges,Changbai mountain ranges in Jilin,and south and northwest of the Da Hinggan Mountains;carbon sources were mainly distributed from the northeast to southwestern areas in China,with the highest values mainly concentrated in southern Yunnan Province,central Sichuan Basin,and northern Da Hinggan Mountains.Increase in NPP was strongly correlated with carbon sink strength.The regression model showed that more than 80% of the variation in the modeled carbon sinks in Northeast,Northern,Northwest and Southern China were explained by the variation in NPP increase.There was a strong relationship between carbon sink strength and forest stand age.
基金Acknowledgements This work was supported by the National Natural Science Foundation of China （Grant Nos. 40901202, 40925004）, and the National High Technology Research and Development Program of China （Grant No. 2009AA122104）. The input data for WRF model are from the Research Data Archive （RDA） which is maintained by the Computational and Information Systems Laboratory （CISL） at the National Center for Atmo- spheric Research （NCAR）. The original data are available from the RDA （http：//dss.ucar.edu） in Dataset No. ds083.2.
文摘The spatial resolution of general circulation models （GCMs） is too coarse to represent regional climate variations at the regional, basin, and local scales required for many environmental modeling and impact assessments. Weather research and forecasting model （WRF） is a nextgeneration, fully compressible, Euler non-hydrostatic mesoscale forecast model with a runtime hydrostatic option. This model is useful for downscaling weather and climate at the scales from one kilometer to thousands of kilometers, and is useful for deriving meteorological parameters required for hydrological simulation too. The objective of this paper is to validate WRF simulating 5 km/ 1 h air temperatures by daily observed data of China Meteorological Administration （CMA） stations, and by hourly in-situ data of the Watershed Allied Telemetry Experimental Research Project. The daily validation shows that the WRF simulation has good agreement with the observed data; the R2 between the WRF simulation and each station is more than 0.93; the absolute of meanbias error （MBE） for each station is less than 2℃; and the MBEs of Ejina, Mazongshan and Alxa stations are near zero, with R2 is more than 0.98, which can be taken as an unbiased estimation. The hourly validation shows that the WRF simulation can capture the basic trend of observed data, the MBE of each site is approximately 2℃, the R2 of each site is more than 0.80, with the highest at 0.95, and the computed and observed surface air temperature series show a significantly similar trend.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 50679063, 50809049)the International Cooperation Research Fund of China (Grant No. 2005DFA20520)the Research Fund for the Doctoral Program of Higher Education (Grant No. 200804861062)
文摘The climate impact studies in hydrology often rely on climate change information at fine spatial resolution. However, the general circulation model (GCM), which is widely used to simulate future climate scenario, operates on a coarse scale and does not provide reliable data on local or regional scale for hydrological modeling. Therefore the outputs from GCM have to be downscaled to obtain the information fit for hydrologic studies. The variable infiltration capacity (VIC) distributed hydrological model with 9×9 km2 grid resolution was applied and calibrated in the Hanjiang Basin. Validation results show that SSVM can approximate observed precipitation and temperature data reasonably well, and that the VIC model can simulate runoff hydrograph with high model efficiency and low relative error. By applying the SSVM model, the trends of precipitation and temperature (including daily mean temperature, daily maximum temperature and daily minimum temperature) projected from CGCM2 under A2 and B2 scenarios will decrease in the 2020s (2011―2040), and increase in the 2080s (2071―2100). However, in the 2050s (2041―2070), the precipitation will be decreased under A2 scenario and no significant changes under B2 scenario, but the temperature will be not obviously changed under both climate change scenarios. Under both climate change scenarios, the impact analysis of runoff, made with the downscaled precipitation and temperature time series as input of the VIC distributed model, has resulted in a decreasing trend for the 2020s and 2050s, and an overall increasing trend for the 2080s.
