Global warming has altered the thermodynamic and dynamic environments of climate systems,affecting the biogeochemical processes between the geosphere and atmosphere,which has significant impacts on precipitation extre...Global warming has altered the thermodynamic and dynamic environments of climate systems,affecting the biogeochemical processes between the geosphere and atmosphere,which has significant impacts on precipitation extremes and the terrestrial carbon budget of ecosystems.Existing studies have reported a hook structure for precipitation extreme-temperature relationships but have rarely examined the underlying physical mechanisms.Previous studies have also failed to quantify the impact of precipitation on ecosystem productivity,hindering the assessment of future extreme climatic hazards and potential ecosystem risks.To reveal the thermodynamic driving mechanisms for the formation of global precipitation extremes and ecohydrological effects,this study utilizes over ten multisource datasets(i.e.,satellite,reanalysis,climate model,land surface model,machine learning reconstruction,and flux tower measurements).We first assess the response of water-heat-carbon flux to precipitation extremes and explain the underlying physical mechanisms behind the hook structures in terms of atmospheric thermodynamics and dynamics.Based on outputs from five global climate models(GCMs)under ISIMIP3b,we project future changes in the hook structures as well as their impacts on precipitation extremes.Finally,we discuss the impact of precipitation on the terrestrial carbon budget by using outputs from the CLM4.5 model.The results show that precipitation extremes are usually accompanied by strong exchanges of water and heat and demonstrate a nonlinear relationship between precipitation and ecosystem productivity.The intensity(duration)of extreme precipitation is intensifying(decreasing)over most areas of the globe,whereas three-dimensional precipitation events are becoming more concentrated.Atmospheric dynamics play a key role in shaping the hook structure.The structure is not stable;it shifts under climate change and is projected to result in a 10–40%intensification in precipitation by the end of this century.Moderate levels of precipitation contribute to carbon assimilation in ecosystems,and the response of the carbon budget to precipitation is relatively stable under climate change.展开更多
Probabilistic inflow forecasts can quantify the uncertainty involved in the forecasting process and provide useful risk information for reservoir management.This study proposed a probabilistic inflow forecasting schem...Probabilistic inflow forecasts can quantify the uncertainty involved in the forecasting process and provide useful risk information for reservoir management.This study proposed a probabilistic inflow forecasting scheme for the Three Gorges Reservoir(TGR)at 1-3 d lead times.The post-processing method Ensemble Model Output Statistics(EMOS)is used to derive probabilistic inflow forecasts from ensemble inflow forecasts.Considering the inherent skew feature of the inflow series,lognormal and gamma distributions are used as EMOS predictive distributions in addition to conventional normal distribution.Results show that TGR's ensemble inflow forecasts at 1-3 d lead times perform well with high model efficiency and small mean absolute error.Underestimation of forecasting uncertainty is observed for the raw ensemble inflow forecasts with biased probability integral transform(PIT)histograms.The three EMOS probabilistic forecasts outperform the raw ensemble forecasts in terms of both deterministic and probabilistic performance at 1-3 d lead times.The EMOS results are more reliable with much flatter PIT histograms,coverage rates approximate to the nominal coverage 89.47%and satisfactory sharpness.Results also show that EMOS with gamma distribution is superior to normal and lognormal distributions.This research can provide reliable probabilistic inflow forecasts without much variation of TGR5s operational inflow forecasting procedure.展开更多
Global warming has altered the thermodynamic and dynamic environments of the climate system, thus affecting the energy budget and water cycle process of the land-atmosphere system. Under changes in key hydrological el...Global warming has altered the thermodynamic and dynamic environments of the climate system, thus affecting the energy budget and water cycle process of the land-atmosphere system. Under changes in key hydrological elements such as precipitation, runoff, and terrestrial water storage, future drought variation remains a complex question. Existing studies have utilized terrestrial water storage anomaly(TWSA) in drought monitoring and assessment, but they usually focused on either drought duration or intensity, overlooking the multi-faced attributes of droughts as well as their socioeconomic impacts under a non-stationary condition. In this study, we first identify dry/wet conditions over China using GRACE/GRACE-FO satellite observations, and then evaluate the feedback effects of humidity and energy factors(e.g., sensible heat flux, latent heat flux,atmospheric relative humidity, and convective available potential energy) to drought events. Future changes in TWSA and dry/wet conditions are projected by eight Coupled Model Inter-comparison Project Phase 6(CMIP6) global climate models(GCMs)under three shared socioeconomic pathways(SSPs), with their biases corrected by a trend-preserving quantile mapping method.The time-varying Copula function of drought duration and intensity is constructed by a moving windows method, and future bivariate drought risks are quantified with the most likely realization method. The population and GDP affected by increasing drought risks are finally quantified based on the SSPs data. It is found that the land-atmosphere coupling effects closely interact with drought evolution, and the uneven distribution of water resources is projected to be further aggravated, with most areas of China will be threatened by continuous drying tendency. By the end of the century, the duration of moderate, severe and exceptional droughts in some regions of China will double, and the drought intensity will increase by over 80%. For the 50-year bivariate droughts during the historical period, their occurrence may increase by 5–10 times in several regions, and might affect about 35–55% of China’s population and GDP at the end of 21st century.展开更多
Poyang Lake, the largest freshwater lake in China, and its surrounding sub-basins have suffered frequent floods and droughts in recent decades. To better understand and quantitatively assess hydrological impacts of cl...Poyang Lake, the largest freshwater lake in China, and its surrounding sub-basins have suffered frequent floods and droughts in recent decades. To better understand and quantitatively assess hydrological impacts of climate change in the region, this study adopted the Statistical Downscaling Model （SDSM） to downseale the outputs of a Global Climate Model （GCM） under three scenarios （RCP2.6, RCP4.5 and RCP8.5） as recommended by the fifth phase of the Coupled Model Inter-comparison Project （CMIP5） during future periods （2010-2099） in the Poyang Lake Basin. A semi-distributed two-parameter monthly water balance model was also used to simulate and predict projected changes of runoff in the Ganjiang sub-basin. Results indicate that： 1） SDSM can simulate monthly mean precipitation reasonably well, while a bias correction procedure should be applied to downscaled extreme precipitation indices （EPI） before being employed to simulate future precipitation; 2） for annual mean precipitation, a mixed pattern of positive or negative changes are detected in the entire basin, with a slightly higher or lower trend in the 2020s and 2050s, with a consistent increase in the 2080s; 3） all six EPI show a general increase under RCP4.5 and RCP8.5 scenarios, while a mixed pattern of positive and negative changes is detected for most indices under the RCP2.6 scenario; and 4） the future runoff in the Ganjiang sub-basin shows an overall decreasing trend for all periods but the 2080s under the RCP8.5 scenario when runoff is more sensitive to changes in precipitation than evaporation.展开更多
Climate change and land use/cover change(LUCC)can both exert great impacts on the generation processes of precipitation and runoff.However,previous studies usually neglected considering the contribution component of f...Climate change and land use/cover change(LUCC)can both exert great impacts on the generation processes of precipitation and runoff.However,previous studies usually neglected considering the contribution component of future LUCC in evaluating changes in hydrological cycles.In this study,an integrated framework is developed to quantify and partition the impact of climate change and LUCC on future runoff evolution.First,a daily bias correction(DBC)method and the Cellular Automaton-Markov(CA-Markov)model are used to project future climate and LUCC scenarios,and then future runoff is simulated by the calibrated Soil and Water Assessment Tool(SWAT)model with different climate and LUCC scenarios.Finally,the uncertainty of future runoff and the contribution rate of the two driving factors are systematically quantified.The Han River basin in China was selected as a case study.Results indicate that:1)both climate change and LUCC will contribute to future runoff intensification,the variation of future runoff under combined climate and LUCC is larger than these under climate change or LUCC alone;2)the projected uncertainty of median value of multi-models under RCP4.5(RCP8.5)will reach 18.14%(20.34%),12.18%(14.71%),11.01%(13.95%),and 11.41%(14.34%)at Baihe,Ankang,Danjiangkou,and Huangzhuang stations,respectively;3)the contribution rate of climate change to runoff at Baihe,Ankang,Danjiangkou,and Huangzhuang stations under RCP4.5(RCP8.5)are 91%-98%(84%-94%),while LUCC to runoff under RCP4.5(RCP8.5)only accounts for 2%-9%(6%-16%)in the annual scale.This study may provide useful adaptive strategies for policymakers on future water resources planning and management.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52009091)the Fundamental Research Funds for the Central Universities(Grant No.2042022kf1221)。
文摘Global warming has altered the thermodynamic and dynamic environments of climate systems,affecting the biogeochemical processes between the geosphere and atmosphere,which has significant impacts on precipitation extremes and the terrestrial carbon budget of ecosystems.Existing studies have reported a hook structure for precipitation extreme-temperature relationships but have rarely examined the underlying physical mechanisms.Previous studies have also failed to quantify the impact of precipitation on ecosystem productivity,hindering the assessment of future extreme climatic hazards and potential ecosystem risks.To reveal the thermodynamic driving mechanisms for the formation of global precipitation extremes and ecohydrological effects,this study utilizes over ten multisource datasets(i.e.,satellite,reanalysis,climate model,land surface model,machine learning reconstruction,and flux tower measurements).We first assess the response of water-heat-carbon flux to precipitation extremes and explain the underlying physical mechanisms behind the hook structures in terms of atmospheric thermodynamics and dynamics.Based on outputs from five global climate models(GCMs)under ISIMIP3b,we project future changes in the hook structures as well as their impacts on precipitation extremes.Finally,we discuss the impact of precipitation on the terrestrial carbon budget by using outputs from the CLM4.5 model.The results show that precipitation extremes are usually accompanied by strong exchanges of water and heat and demonstrate a nonlinear relationship between precipitation and ecosystem productivity.The intensity(duration)of extreme precipitation is intensifying(decreasing)over most areas of the globe,whereas three-dimensional precipitation events are becoming more concentrated.Atmospheric dynamics play a key role in shaping the hook structure.The structure is not stable;it shifts under climate change and is projected to result in a 10–40%intensification in precipitation by the end of this century.Moderate levels of precipitation contribute to carbon assimilation in ecosystems,and the response of the carbon budget to precipitation is relatively stable under climate change.
基金This study is supported by the National Key Research and Development Plan of China(No.2016YFC0402206)the National Natural Science Foundation of China(Grant Nos.51879192,91647106).Thanks are also given to CWRC for providing necessary data and the three anonymous reviewers’valuable suggestions to improve our manuscript.
文摘Probabilistic inflow forecasts can quantify the uncertainty involved in the forecasting process and provide useful risk information for reservoir management.This study proposed a probabilistic inflow forecasting scheme for the Three Gorges Reservoir(TGR)at 1-3 d lead times.The post-processing method Ensemble Model Output Statistics(EMOS)is used to derive probabilistic inflow forecasts from ensemble inflow forecasts.Considering the inherent skew feature of the inflow series,lognormal and gamma distributions are used as EMOS predictive distributions in addition to conventional normal distribution.Results show that TGR's ensemble inflow forecasts at 1-3 d lead times perform well with high model efficiency and small mean absolute error.Underestimation of forecasting uncertainty is observed for the raw ensemble inflow forecasts with biased probability integral transform(PIT)histograms.The three EMOS probabilistic forecasts outperform the raw ensemble forecasts in terms of both deterministic and probabilistic performance at 1-3 d lead times.The EMOS results are more reliable with much flatter PIT histograms,coverage rates approximate to the nominal coverage 89.47%and satisfactory sharpness.Results also show that EMOS with gamma distribution is superior to normal and lognormal distributions.This research can provide reliable probabilistic inflow forecasts without much variation of TGR5s operational inflow forecasting procedure.
基金supported by the National Natural Science Foundation of China (Grant No. 52009091)the Fundamental Research Funds for the Central Universities (Grant No. 2042022kf1221)。
文摘Global warming has altered the thermodynamic and dynamic environments of the climate system, thus affecting the energy budget and water cycle process of the land-atmosphere system. Under changes in key hydrological elements such as precipitation, runoff, and terrestrial water storage, future drought variation remains a complex question. Existing studies have utilized terrestrial water storage anomaly(TWSA) in drought monitoring and assessment, but they usually focused on either drought duration or intensity, overlooking the multi-faced attributes of droughts as well as their socioeconomic impacts under a non-stationary condition. In this study, we first identify dry/wet conditions over China using GRACE/GRACE-FO satellite observations, and then evaluate the feedback effects of humidity and energy factors(e.g., sensible heat flux, latent heat flux,atmospheric relative humidity, and convective available potential energy) to drought events. Future changes in TWSA and dry/wet conditions are projected by eight Coupled Model Inter-comparison Project Phase 6(CMIP6) global climate models(GCMs)under three shared socioeconomic pathways(SSPs), with their biases corrected by a trend-preserving quantile mapping method.The time-varying Copula function of drought duration and intensity is constructed by a moving windows method, and future bivariate drought risks are quantified with the most likely realization method. The population and GDP affected by increasing drought risks are finally quantified based on the SSPs data. It is found that the land-atmosphere coupling effects closely interact with drought evolution, and the uneven distribution of water resources is projected to be further aggravated, with most areas of China will be threatened by continuous drying tendency. By the end of the century, the duration of moderate, severe and exceptional droughts in some regions of China will double, and the drought intensity will increase by over 80%. For the 50-year bivariate droughts during the historical period, their occurrence may increase by 5–10 times in several regions, and might affect about 35–55% of China’s population and GDP at the end of 21st century.
基金Acknowledgements This study was supported by the National Nature Science Foundation of China （Grant Nos. 51539009 and 51190094）, and the National Key Research and Development Plan of China （2016YFC0402206）. The authors thank the editor and anonymous reviewers for their comments and suggestions, and Prof. Chong-Yu Xu and Dr. David E. Rheinheimer whose cornments and English language editing helped to clarify and improve the quality of this paper.
文摘Poyang Lake, the largest freshwater lake in China, and its surrounding sub-basins have suffered frequent floods and droughts in recent decades. To better understand and quantitatively assess hydrological impacts of climate change in the region, this study adopted the Statistical Downscaling Model （SDSM） to downseale the outputs of a Global Climate Model （GCM） under three scenarios （RCP2.6, RCP4.5 and RCP8.5） as recommended by the fifth phase of the Coupled Model Inter-comparison Project （CMIP5） during future periods （2010-2099） in the Poyang Lake Basin. A semi-distributed two-parameter monthly water balance model was also used to simulate and predict projected changes of runoff in the Ganjiang sub-basin. Results indicate that： 1） SDSM can simulate monthly mean precipitation reasonably well, while a bias correction procedure should be applied to downscaled extreme precipitation indices （EPI） before being employed to simulate future precipitation; 2） for annual mean precipitation, a mixed pattern of positive or negative changes are detected in the entire basin, with a slightly higher or lower trend in the 2020s and 2050s, with a consistent increase in the 2080s; 3） all six EPI show a general increase under RCP4.5 and RCP8.5 scenarios, while a mixed pattern of positive and negative changes is detected for most indices under the RCP2.6 scenario; and 4） the future runoff in the Ganjiang sub-basin shows an overall decreasing trend for all periods but the 2080s under the RCP8.5 scenario when runoff is more sensitive to changes in precipitation than evaporation.
基金supported by the National Natural Science Foundation of China(Grant Nos.U20A20317 and 51539009).
文摘Climate change and land use/cover change(LUCC)can both exert great impacts on the generation processes of precipitation and runoff.However,previous studies usually neglected considering the contribution component of future LUCC in evaluating changes in hydrological cycles.In this study,an integrated framework is developed to quantify and partition the impact of climate change and LUCC on future runoff evolution.First,a daily bias correction(DBC)method and the Cellular Automaton-Markov(CA-Markov)model are used to project future climate and LUCC scenarios,and then future runoff is simulated by the calibrated Soil and Water Assessment Tool(SWAT)model with different climate and LUCC scenarios.Finally,the uncertainty of future runoff and the contribution rate of the two driving factors are systematically quantified.The Han River basin in China was selected as a case study.Results indicate that:1)both climate change and LUCC will contribute to future runoff intensification,the variation of future runoff under combined climate and LUCC is larger than these under climate change or LUCC alone;2)the projected uncertainty of median value of multi-models under RCP4.5(RCP8.5)will reach 18.14%(20.34%),12.18%(14.71%),11.01%(13.95%),and 11.41%(14.34%)at Baihe,Ankang,Danjiangkou,and Huangzhuang stations,respectively;3)the contribution rate of climate change to runoff at Baihe,Ankang,Danjiangkou,and Huangzhuang stations under RCP4.5(RCP8.5)are 91%-98%(84%-94%),while LUCC to runoff under RCP4.5(RCP8.5)only accounts for 2%-9%(6%-16%)in the annual scale.This study may provide useful adaptive strategies for policymakers on future water resources planning and management.
