In this study, the authors demonstrate that the Coupled Model Intercomparison Project Phase 5 （CMIP5） models project a robust response in changes of mean and climate extremes to warming in China. Under a scenario of...In this study, the authors demonstrate that the Coupled Model Intercomparison Project Phase 5 （CMIP5） models project a robust response in changes of mean and climate extremes to warming in China. Under a scenario of a 1% CO2 increase per year, surface temperature in China is projected to increase more rapidly than the global average, and the model ensemble projects more precipitation （2.2%/℃）. Responses in changes of climate extremes are generally much stronger than that of climate means. The majority of models project a consistent re- sponse, with more warm events but fewer cold events in China due to CO2 warming. For example, the ensemble mean indicates a high positive sensitivity for increasing summer days （12.4%/℃） and tropical nights （26.0%/℃）, but a negative sensitivity for decreasing frost days （-4.7%/℃） and ice days （-7.0%/℃）. Further analyses indicate that precipitation in China is likely to become more extreme, featuring a high positive sensitivity. The sensitivity is high （2.4%/℃） for heavy precipitation days （〉 10 mm d l） and increases dramatically （5.3%/℃） for very heavy precipitation days （〉 20 mm d-1）, as well as for precipitation amounts on very wet days （10.8%/℃） and extremely wet days （22.0%/℃）. Thus, it is concluded that the more extreme precipitation events generally show higher sensitivity to CO2 warming. Additionally, southern China is projected to experience an increased risk of drought and flood occurrence, while an increased risk of flood but a decreased risk of drought is likely in other regions of China.展开更多
Mountain catchments are prone to flash flooding due to heavy rainfall. Enhanced understanding of the generation and evolution processes of flash floods is essential for effective flood risk management. However, tradit...Mountain catchments are prone to flash flooding due to heavy rainfall. Enhanced understanding of the generation and evolution processes of flash floods is essential for effective flood risk management. However, traditional distributed hydrological models based on kinematic and diffusion wave approximations ignore certain physical mechanisms of flash floods and thus bear excessive uncertainty. Here a hydrodynamic model is presented for flash floods based on the full two-dimensional shallow water equations incorporating rainfall and infiltration. Laboratory experiments of overland flows were modelled to illustrate the capability of the model. Then the model was applied to resolve two observed flash floods of distinct magnitudes in the Lengkou catchment in Shanxi Province, China. The present model is shown to be able to reproduce the flood flows fairly well compared to the observed data. The spatial distribution of rainfall is shown to be crucial for the modelling of flash floods. Sensitivity analyses of the model parameters reveal that the stage and discharge hydrographs are more sensitive to the Manning roughness and initial water content in the catchment than to the Green-Ampt head. Most notably, as the flash flood augments due to heavier rainfall, the modelling results agree with observed data better, which clearly characterizes the paramount role of rainfall in dictating the floods. From practical perspectives, the proposed model is more appropriate for modelling large flash floods.展开更多
Fifty cases of regional yearly extreme precipitation events （RYEPEs） were identified over the Yangtze-Huaihe River Valley （YHRV） during 1979-2016 applying the statistical percentile method. There were five types o...Fifty cases of regional yearly extreme precipitation events （RYEPEs） were identified over the Yangtze-Huaihe River Valley （YHRV） during 1979-2016 applying the statistical percentile method. There were five types of RYEPEs, namely Yangtze Meiyu （YM-RYEPE）, Huaihe Meiyu （HM-RYEPE）, southwest-northeast-oriented Meiyu （SWNE-RYEPE） and typhoon I and II （TC-RYEPE） types of RYEPEs. Potential vorticity diagnosis showed that propagation trajectories of the RYEPEs along the Western Pacific Subtropical High and its steering flow were concentrated over the southern YHRV. As a result, the strongest and most frequently RYEPEs events, about 16-21 cases with average rainfall above 100 mm, occurred in the southern YHRV, particularly in the Nanjing metropolitan area. There have been 14 cases of flood-inducing RYEPEs since 1979, with the submerged area exceeding 120 km2 as simulated by the FloodArea hydraulic model, comprising six HM-RYEPEs, five YM- RYEPEs, two TC-RYEPEs, and one SWNE-RYEPE. The combination of evolving RYEPEs and rapid expansion of urban agglomeration is most likely to change the flood risk distribution over the Nanjing metropolitan area in the future. In the RCP6.0 （RCPS.5） scenario, the built-up area increases at a rate of about 10.41 km2 （10 yr）-t（24.67 km2 （10 yr）-1） from 2010 to 2100, and the area of high flood risk correspondingly increases from 3.86 km2（3.86 km2） to 9.00 kin2（13.51 km2）. Areas of high flood risk are mainly located at Chishan Lake in Jurong, Lukou International Airport in Nanjing, Dongshan in Jiangning District, Lishui District and other low-lying areas. The accurate simulation of flood scenarios can help reduce losses due to torrential flooding and improve early warnings, evacuation planning and risk analysis. More attention should be paid to the projected high flood risk because of the concentrated population, industrial zones and social wealth throughout the Nanjing metropolitan area.展开更多
To avoid dangerous climate change impact, the Paris Agreement sets out two ambitious goals: to limit the global warming to be well below 2 ℃ and to pursue effort for the global warming to be below 1.5 ℃ above the ...To avoid dangerous climate change impact, the Paris Agreement sets out two ambitious goals: to limit the global warming to be well below 2 ℃ and to pursue effort for the global warming to be below 1.5 ℃ above the pre-industrial level. As climate change risks may be region-dependent, changes in magnitude and probability of extreme precipitation over China are investigated under those two global warming levels based on simulations from the Coupled Model Inter-Comparison Projects Phase 5. The focus is on the added changes due to the additional half a degree warming from 1.5 ℃ to 2 ℃ . Results show that regional average changes in the magnitude do not depend on the return periods with a relative increase around 7% and 11% at the 1.5 ℃ and 2 ℃ global warming levels, respectively. The additional half a degree global warming adds an additional increase in the magnitude by nearly 4%. The regional average changes in term of occurrence probabilities show dependence on the return periods, with rarer events(longer return periods) having larger increase of risk. For the 100-year historical event, the probability is projected to increase by a factor of 1.6 and 2.4 at the 1.5 ℃ and 2 ℃ global warming levels, respectively.The projected changes in extreme precipitation are independent of the RCP scenarios.展开更多
基金supported by the National Basic Research Program of China (Grant No. 2012CB955401)the National Natural Science Foundation of China (Grant No. 41305061)the "Strategic Priority Research Program-Climate Change: Carbon Budget and Relevant Issues" of the Chinese Academy of Sciences (Grant No. XDA05090306)
文摘In this study, the authors demonstrate that the Coupled Model Intercomparison Project Phase 5 （CMIP5） models project a robust response in changes of mean and climate extremes to warming in China. Under a scenario of a 1% CO2 increase per year, surface temperature in China is projected to increase more rapidly than the global average, and the model ensemble projects more precipitation （2.2%/℃）. Responses in changes of climate extremes are generally much stronger than that of climate means. The majority of models project a consistent re- sponse, with more warm events but fewer cold events in China due to CO2 warming. For example, the ensemble mean indicates a high positive sensitivity for increasing summer days （12.4%/℃） and tropical nights （26.0%/℃）, but a negative sensitivity for decreasing frost days （-4.7%/℃） and ice days （-7.0%/℃）. Further analyses indicate that precipitation in China is likely to become more extreme, featuring a high positive sensitivity. The sensitivity is high （2.4%/℃） for heavy precipitation days （〉 10 mm d l） and increases dramatically （5.3%/℃） for very heavy precipitation days （〉 20 mm d-1）, as well as for precipitation amounts on very wet days （10.8%/℃） and extremely wet days （22.0%/℃）. Thus, it is concluded that the more extreme precipitation events generally show higher sensitivity to CO2 warming. Additionally, southern China is projected to experience an increased risk of drought and flood occurrence, while an increased risk of flood but a decreased risk of drought is likely in other regions of China.
基金funded by Natural Science Foundation of China (Grants Nos. 51279144 and 11432015)Chinese Academy of Sciences (Grant No. KZZD-EW-05-01-03)
文摘Mountain catchments are prone to flash flooding due to heavy rainfall. Enhanced understanding of the generation and evolution processes of flash floods is essential for effective flood risk management. However, traditional distributed hydrological models based on kinematic and diffusion wave approximations ignore certain physical mechanisms of flash floods and thus bear excessive uncertainty. Here a hydrodynamic model is presented for flash floods based on the full two-dimensional shallow water equations incorporating rainfall and infiltration. Laboratory experiments of overland flows were modelled to illustrate the capability of the model. Then the model was applied to resolve two observed flash floods of distinct magnitudes in the Lengkou catchment in Shanxi Province, China. The present model is shown to be able to reproduce the flood flows fairly well compared to the observed data. The spatial distribution of rainfall is shown to be crucial for the modelling of flash floods. Sensitivity analyses of the model parameters reveal that the stage and discharge hydrographs are more sensitive to the Manning roughness and initial water content in the catchment than to the Green-Ampt head. Most notably, as the flash flood augments due to heavier rainfall, the modelling results agree with observed data better, which clearly characterizes the paramount role of rainfall in dictating the floods. From practical perspectives, the proposed model is more appropriate for modelling large flash floods.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41205063 & 41330529)the China Meteorological Administration Special Public Welfare Research Fund (Grant No. GYHY201506006)+1 种基金the Project of Development of Key Techniques in Meteorological Forecasting Operation (Grant No. CMAHX20160404)the Huaihe Basin Meteorological Research Foundation (Grant No. HRM201605)
文摘Fifty cases of regional yearly extreme precipitation events （RYEPEs） were identified over the Yangtze-Huaihe River Valley （YHRV） during 1979-2016 applying the statistical percentile method. There were five types of RYEPEs, namely Yangtze Meiyu （YM-RYEPE）, Huaihe Meiyu （HM-RYEPE）, southwest-northeast-oriented Meiyu （SWNE-RYEPE） and typhoon I and II （TC-RYEPE） types of RYEPEs. Potential vorticity diagnosis showed that propagation trajectories of the RYEPEs along the Western Pacific Subtropical High and its steering flow were concentrated over the southern YHRV. As a result, the strongest and most frequently RYEPEs events, about 16-21 cases with average rainfall above 100 mm, occurred in the southern YHRV, particularly in the Nanjing metropolitan area. There have been 14 cases of flood-inducing RYEPEs since 1979, with the submerged area exceeding 120 km2 as simulated by the FloodArea hydraulic model, comprising six HM-RYEPEs, five YM- RYEPEs, two TC-RYEPEs, and one SWNE-RYEPE. The combination of evolving RYEPEs and rapid expansion of urban agglomeration is most likely to change the flood risk distribution over the Nanjing metropolitan area in the future. In the RCP6.0 （RCPS.5） scenario, the built-up area increases at a rate of about 10.41 km2 （10 yr）-t（24.67 km2 （10 yr）-1） from 2010 to 2100, and the area of high flood risk correspondingly increases from 3.86 km2（3.86 km2） to 9.00 kin2（13.51 km2）. Areas of high flood risk are mainly located at Chishan Lake in Jurong, Lukou International Airport in Nanjing, Dongshan in Jiangning District, Lishui District and other low-lying areas. The accurate simulation of flood scenarios can help reduce losses due to torrential flooding and improve early warnings, evacuation planning and risk analysis. More attention should be paid to the projected high flood risk because of the concentrated population, industrial zones and social wealth throughout the Nanjing metropolitan area.
基金supported by the National Key R&D Program of China(Grant 2017YFA0603804)the State Key Program of National Natural Science Foundation of China(41230528)+1 种基金the China Scholarship Council(CSC)under the State Scholarship Fundsupported by the French ANR Project China-Trend-Stream
文摘To avoid dangerous climate change impact, the Paris Agreement sets out two ambitious goals: to limit the global warming to be well below 2 ℃ and to pursue effort for the global warming to be below 1.5 ℃ above the pre-industrial level. As climate change risks may be region-dependent, changes in magnitude and probability of extreme precipitation over China are investigated under those two global warming levels based on simulations from the Coupled Model Inter-Comparison Projects Phase 5. The focus is on the added changes due to the additional half a degree warming from 1.5 ℃ to 2 ℃ . Results show that regional average changes in the magnitude do not depend on the return periods with a relative increase around 7% and 11% at the 1.5 ℃ and 2 ℃ global warming levels, respectively. The additional half a degree global warming adds an additional increase in the magnitude by nearly 4%. The regional average changes in term of occurrence probabilities show dependence on the return periods, with rarer events(longer return periods) having larger increase of risk. For the 100-year historical event, the probability is projected to increase by a factor of 1.6 and 2.4 at the 1.5 ℃ and 2 ℃ global warming levels, respectively.The projected changes in extreme precipitation are independent of the RCP scenarios.
