在第2代加拿大地球系统模型(the second generation Canadian earth system model,CanESM2)中的3种典型浓度路径(representative concentration pathways,RCPs)情景(RCP2.6、RCP4.5和RCP8.5)下,基于统计降尺度模型(statistical down sca...在第2代加拿大地球系统模型(the second generation Canadian earth system model,CanESM2)中的3种典型浓度路径(representative concentration pathways,RCPs)情景(RCP2.6、RCP4.5和RCP8.5)下,基于统计降尺度模型(statistical down scaling model,SDSM)研究兰江流域未来年份温度和降水量的变化趋势。结果表明:1)SDSM在兰江流域具有较好的适用性,各站点最高温度、最低温度、降水量的解释方差分别为70.62%~79.74%、69.61%~78.76%、28.56%~41.45%;2)3种RCPs情景下温度均呈上升趋势,且上升幅度随辐射强迫度上升而同步增大,至21世纪末,RCP2.6、RCP4.5、RCP8.5情景下的最高温度分别较基准期上升0.06℃、1.22℃、2.76℃,最低温度分别较基准期上升0.35℃、1.15℃、3.01℃;3)RCP2.6情景下的降水量总体呈下降趋势,至2080—2100年下降0.98%,RCP4.5情景下的降水量呈先上升后下降趋势,至2050—2079年达到峰值,较基准期上升12.03%,RCP8.5情景下的降水量呈先下降后快速上升趋势,至2080—2100年上升38.08%。研究结果可为兰江流域内水资源管理、生态文明建设及社会经济可持续发展提供依据和理论支持。展开更多
Climate change caused by past,current,and future greenhouse gas emissions has become a major concern for scientists in the field in many countries and regions of the world.This study modelled future precipitation chan...Climate change caused by past,current,and future greenhouse gas emissions has become a major concern for scientists in the field in many countries and regions of the world.This study modelled future precipitation change by downscaling a set of large-scale climate predictor variables(predictors)from the second generation Canadian Earth System Model(CanESM2)under two Representative Concentration Pathway(RCP)emission scenarios(RCP4.5 and RCP8.5)in the semi-arid Borana lowland,southern Ethiopia.The Statistical DownScaling Model(SDSM)4.2.9 was employed to downscale and project future precipitation change in the middle(2036-2065;2050s)and far(2066-2095;2080s)future at the local scale.Historical precipitation observations from eight meteorological stations stretching from 1981 to 1995 and 1996 to 2005 were used for the model calibration and validation,respectively,and the time period of 1981-2018 was considered and used as the baseline period to analyze future precipitation change.The results revealed that the surface-specific humidity and the geopotential height at 500 hPa were the preferred large-scale predictors.Compared to the middle future(2050s),precipitation showed a much greater increase in the far future(2080s)under both RCP4.5 and RCP8.5 scenarios at all meteorological stations(except Teletele and Dillo stations).At Teltele station,the projected annual precipitation will decrease by 26.53%(2050s)and 39.45%(2080s)under RCP4.5 scenario,and 34.99%(2050s)and 60.62%(2080s)under RCP8.5 scenario.Seasonally,the main rainy period would shift from spring(March to May)to autumn(September to November)at Dehas,Dire,Moyale,and Teltele stations,but for Arero and Yabelo stations,spring would consistently receive more precipitation than autumn.It can be concluded that future precipitation in the semi-arid Borana lowland is predicted to differ under the two climate scenarios(RCP4.5 and RCP8.5),showing an increasing trend at most meteorological stations.This information could be helpful for policymakers to design adaptation plans in water resources management,and we suggest that the government should give more attention to improve early warning systems in drought-prone areas by providing dependable climate forecast information as early as possible.展开更多
This study was aimed to assess the impact of climate change on the water resource of Megech river catchment. In this study, large scale regional climate model (REMO) output was downscaled statistically to metrological...This study was aimed to assess the impact of climate change on the water resource of Megech river catchment. In this study, large scale regional climate model (REMO) output was downscaled statistically to metrological variables at a daily resolution using SDSM model version 5.11. We noticed that statistical downscaling smooth out the bias between REMO output and observed data. According to the projected climate data, the maximum temperature is likely to have an increasing trend +0.57°C while the minimum temperature shows a decreasing trends ﹣0.61°C. There is no clear trend for precipitation, both increasing and decreasing trend observed in the catchment. The HBV-Light hydrological model was successfully calibrated (1991-1995) and validated (1998-2000) using current climatic inputs and observed river flows. The overall performances of the model was good at monthly time scale both on calibration (NSE = 0.91) and validation (NSE = 0.86). Future discharge (2015-2050) was simulated using statistically downscaled 20 ensembles climate scenario data for both A1B and B1 scenarios. HBV-Light model simulation results showed a reduction of the peak discharge in August and September.展开更多
Temporal change in rainfall erosivity varies due to the rainfall characteristic(amount,intensity,frequency,duration),which affects the conservation of soil and water.This study illustrates the variation of rainfall er...Temporal change in rainfall erosivity varies due to the rainfall characteristic(amount,intensity,frequency,duration),which affects the conservation of soil and water.This study illustrates the variation of rainfall erosivity due to changing rainfall in the past and the future.The projected rainfall is generated by SDSM(Statistical DownScaling Model)after calibration and validation using two GCMs(general circulation model)data of HadCM3(A2 and B2 scenario)and CGCM3(A1B and A2 scenario).The selected study area is mainly a cultivable area with an agricultural based economy.This economy depends on rainfall and is located in a part of the Narmada river basin in central India.Nine rainfall locations are selected that are distributed throughout the study area and surrounding.The results indicate gradually increasing projected rainfall while the past rainfall has shown a declined pattern by Mann–Kendall test with statistical 95%confidence level.Rainfall erosivity has increased due to the projected increase in the future rainfall(2080 s)in comparison to the past.Rainfall erosivity varies from32.91%to 24.12%in the 2020s,18.82 to 75.48%in 2050 s and 20.95–202.40%in 2080s.The outputs of this paper can be helpful for the decision makers to manage the soil water conservation in this study area.展开更多
文摘在第2代加拿大地球系统模型(the second generation Canadian earth system model,CanESM2)中的3种典型浓度路径(representative concentration pathways,RCPs)情景(RCP2.6、RCP4.5和RCP8.5)下,基于统计降尺度模型(statistical down scaling model,SDSM)研究兰江流域未来年份温度和降水量的变化趋势。结果表明:1)SDSM在兰江流域具有较好的适用性,各站点最高温度、最低温度、降水量的解释方差分别为70.62%~79.74%、69.61%~78.76%、28.56%~41.45%;2)3种RCPs情景下温度均呈上升趋势,且上升幅度随辐射强迫度上升而同步增大,至21世纪末,RCP2.6、RCP4.5、RCP8.5情景下的最高温度分别较基准期上升0.06℃、1.22℃、2.76℃,最低温度分别较基准期上升0.35℃、1.15℃、3.01℃;3)RCP2.6情景下的降水量总体呈下降趋势,至2080—2100年下降0.98%,RCP4.5情景下的降水量呈先上升后下降趋势,至2050—2079年达到峰值,较基准期上升12.03%,RCP8.5情景下的降水量呈先下降后快速上升趋势,至2080—2100年上升38.08%。研究结果可为兰江流域内水资源管理、生态文明建设及社会经济可持续发展提供依据和理论支持。
文摘Climate change caused by past,current,and future greenhouse gas emissions has become a major concern for scientists in the field in many countries and regions of the world.This study modelled future precipitation change by downscaling a set of large-scale climate predictor variables(predictors)from the second generation Canadian Earth System Model(CanESM2)under two Representative Concentration Pathway(RCP)emission scenarios(RCP4.5 and RCP8.5)in the semi-arid Borana lowland,southern Ethiopia.The Statistical DownScaling Model(SDSM)4.2.9 was employed to downscale and project future precipitation change in the middle(2036-2065;2050s)and far(2066-2095;2080s)future at the local scale.Historical precipitation observations from eight meteorological stations stretching from 1981 to 1995 and 1996 to 2005 were used for the model calibration and validation,respectively,and the time period of 1981-2018 was considered and used as the baseline period to analyze future precipitation change.The results revealed that the surface-specific humidity and the geopotential height at 500 hPa were the preferred large-scale predictors.Compared to the middle future(2050s),precipitation showed a much greater increase in the far future(2080s)under both RCP4.5 and RCP8.5 scenarios at all meteorological stations(except Teletele and Dillo stations).At Teltele station,the projected annual precipitation will decrease by 26.53%(2050s)and 39.45%(2080s)under RCP4.5 scenario,and 34.99%(2050s)and 60.62%(2080s)under RCP8.5 scenario.Seasonally,the main rainy period would shift from spring(March to May)to autumn(September to November)at Dehas,Dire,Moyale,and Teltele stations,but for Arero and Yabelo stations,spring would consistently receive more precipitation than autumn.It can be concluded that future precipitation in the semi-arid Borana lowland is predicted to differ under the two climate scenarios(RCP4.5 and RCP8.5),showing an increasing trend at most meteorological stations.This information could be helpful for policymakers to design adaptation plans in water resources management,and we suggest that the government should give more attention to improve early warning systems in drought-prone areas by providing dependable climate forecast information as early as possible.
文摘This study was aimed to assess the impact of climate change on the water resource of Megech river catchment. In this study, large scale regional climate model (REMO) output was downscaled statistically to metrological variables at a daily resolution using SDSM model version 5.11. We noticed that statistical downscaling smooth out the bias between REMO output and observed data. According to the projected climate data, the maximum temperature is likely to have an increasing trend +0.57°C while the minimum temperature shows a decreasing trends ﹣0.61°C. There is no clear trend for precipitation, both increasing and decreasing trend observed in the catchment. The HBV-Light hydrological model was successfully calibrated (1991-1995) and validated (1998-2000) using current climatic inputs and observed river flows. The overall performances of the model was good at monthly time scale both on calibration (NSE = 0.91) and validation (NSE = 0.86). Future discharge (2015-2050) was simulated using statistically downscaled 20 ensembles climate scenario data for both A1B and B1 scenarios. HBV-Light model simulation results showed a reduction of the peak discharge in August and September.
基金The authors express their thanks to the Indian Meteorological Department(IMD)for the rainfall data and the Pacific Climate Impacts Consortium(PCIC)for the GCM and NCEP Data.The authors are also thankful to the Council of Scientific&Industrial Research(CSIR)(Roll no.200773,Ref.No.20-12/2009(ii)EU-IV)for financial assistance.
文摘Temporal change in rainfall erosivity varies due to the rainfall characteristic(amount,intensity,frequency,duration),which affects the conservation of soil and water.This study illustrates the variation of rainfall erosivity due to changing rainfall in the past and the future.The projected rainfall is generated by SDSM(Statistical DownScaling Model)after calibration and validation using two GCMs(general circulation model)data of HadCM3(A2 and B2 scenario)and CGCM3(A1B and A2 scenario).The selected study area is mainly a cultivable area with an agricultural based economy.This economy depends on rainfall and is located in a part of the Narmada river basin in central India.Nine rainfall locations are selected that are distributed throughout the study area and surrounding.The results indicate gradually increasing projected rainfall while the past rainfall has shown a declined pattern by Mann–Kendall test with statistical 95%confidence level.Rainfall erosivity has increased due to the projected increase in the future rainfall(2080 s)in comparison to the past.Rainfall erosivity varies from32.91%to 24.12%in the 2020s,18.82 to 75.48%in 2050 s and 20.95–202.40%in 2080s.The outputs of this paper can be helpful for the decision makers to manage the soil water conservation in this study area.
