In this study, we employ two regional climate models(RCMs or RegCMs), which are RegCM4 and PRECIS(Providing Regional Climates for Impact Studies), with a horizontal grid spacing of 25 km, to simulate the precipitation...In this study, we employ two regional climate models(RCMs or RegCMs), which are RegCM4 and PRECIS(Providing Regional Climates for Impact Studies), with a horizontal grid spacing of 25 km, to simulate the precipitation dynamics across China for the baseline climate of 1981–2010 and two future climates of 2031–2060 and 2061–2090. The global climate model(GCM)—Hadley Centre Global Environment Model version 2-Earth Systems(HadGEM2-ES) is used to drive the two RCMs. The results of baseline simulations show that the two RCMs can correct the obvious underestimation of light rain below 5 mm day^-1 and the overestimation of precipitation above 5 mm day^-1 in Northwest China and the Qinghai–Tibetan Plateau, as being produced by the driving GCM. While PRECIS outperforms RegCM4 in simulating annual precipitation and wet days in several sub-regions of Northwest China, its underperformance shows up in eastern China. For extreme precipitation, the two RCMs provide a more accurate simulation of continuous wet days(CWD) with reduced biases and more realistic spatial patterns compared to their driving GCM. For other extreme precipitation indices, the RCM simulations show limited benefit except for an improved performance in some localized regions. The future projections of the two RCMs show an increase in the annual precipitation amount and the intensity of extreme precipitation events in most regions. Most areas of Southeast China will experience fewer number of wet days, especially in summer, but more precipitation per wet day(≥ 30 mm day^-1). By contrast, number of wet days will increase in the Qinghai–Tibetan Plateau and some areas of northern China. The increase in both the maximum precipitation for five consecutive days and the regional extreme precipitation will lead to a higher risk of increased flooding. The findings of this study can facilitate the efforts of climate service institutions and government agencies to improve climate services and to make climate-smart decisions.展开更多
One of the key issues in climate risk management is to develop climate resilient infrastructure so as to ensure safety and sustainability of urban functioning systems as well as mitigate the adverse impacts associated...One of the key issues in climate risk management is to develop climate resilient infrastructure so as to ensure safety and sustainability of urban functioning systems as well as mitigate the adverse impacts associated with increasing climate hazards.However,conventional methods of assessing risks do not fully address the interaction of various subsystems within the city system and are unable to consolidate diverse opinions of various stakeholders on their assessments of sector-specific risks posed by climate change.To address this gap,this study advances an integrated-systems-analysis tool-Climate Risk Assessment of Infrastructure Tool(CRAIT),and applies it to analyze and compare the extent of risk factor exposure and vulnerability over time across five critical urban infrastructure sectors in Shanghai and Shenzhen,two cities that have distinctive geo-climate profiles and histories of infrastructure development.The results show significantly higher level of variation between the two cities in terms of vulnerability levels than that of exposure.More specifically,the sectors of critical buildings,water,energy,and information&communication in Shenzhen have significantly higher vulnerability levels than Shanghai in both the 2000s and the 2050s.We further discussed the vulnerability levels of subsystems in each sector and proposed twelve potential adaptation options for the roads system based on four sets of criteria:technical feasibility,flexibility,co-benefits,and policy compatibility.The application of CRAIT is bound to be a knowledge co-production process with the local experts and stakeholders.This knowledge co-production process highlights the importance of management advancements and nature-based green solutions in managing climate change risk in the future though differences are observed across the efficacy categories due to the geographical and meteorological conditions in the two cities.This study demonstrates that this knowledge co-creation process is valuable in facilitating policymakers'decision-making and their feedback to scientific understanding in climate risk assessment,and that this approach has general applicability for cities in other regions and countries.展开更多
基金Project(2018YFF0214706)supported by the National Key Research and Development Program of ChinaProject(cstc2020jcyj-msxmX0690)supported by the Natural Science Foundation of Chongqing,China+1 种基金Project(2020CDJ-LHZZ-039)supported by the Fundamental Research Funds for the Central Universities of Chongqing,ChinaProject(cstc2019jscx-fxydX0012)supported by the Key Research Program of Chongqing Technology Innovation and Application Development,China。
基金Supported by the National Key Research and Development Program of China(2018YFA0606204)National Natural Science Foundation of China(51761135024 and 41671113)+1 种基金UK–China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP)China as part of the Newton Fund(P106409)Social Development Project of Science and Technology Commission of Shanghai Municipality(19DZ1201500)。
文摘In this study, we employ two regional climate models(RCMs or RegCMs), which are RegCM4 and PRECIS(Providing Regional Climates for Impact Studies), with a horizontal grid spacing of 25 km, to simulate the precipitation dynamics across China for the baseline climate of 1981–2010 and two future climates of 2031–2060 and 2061–2090. The global climate model(GCM)—Hadley Centre Global Environment Model version 2-Earth Systems(HadGEM2-ES) is used to drive the two RCMs. The results of baseline simulations show that the two RCMs can correct the obvious underestimation of light rain below 5 mm day^-1 and the overestimation of precipitation above 5 mm day^-1 in Northwest China and the Qinghai–Tibetan Plateau, as being produced by the driving GCM. While PRECIS outperforms RegCM4 in simulating annual precipitation and wet days in several sub-regions of Northwest China, its underperformance shows up in eastern China. For extreme precipitation, the two RCMs provide a more accurate simulation of continuous wet days(CWD) with reduced biases and more realistic spatial patterns compared to their driving GCM. For other extreme precipitation indices, the RCM simulations show limited benefit except for an improved performance in some localized regions. The future projections of the two RCMs show an increase in the annual precipitation amount and the intensity of extreme precipitation events in most regions. Most areas of Southeast China will experience fewer number of wet days, especially in summer, but more precipitation per wet day(≥ 30 mm day^-1). By contrast, number of wet days will increase in the Qinghai–Tibetan Plateau and some areas of northern China. The increase in both the maximum precipitation for five consecutive days and the regional extreme precipitation will lead to a higher risk of increased flooding. The findings of this study can facilitate the efforts of climate service institutions and government agencies to improve climate services and to make climate-smart decisions.
基金supported by the Shenzhen Science and Technology Program(KCXFZ20201221173412035)the National Natural Science Foundation of China(51761135024)+1 种基金the UK-China Research&Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP)China as part of the Newton Fund(Project:Climate Risk Assessment Tool for Chinese Cities)the UK-China Cooperation on Climate Change Risk Assessment(Phase 3)for financial support.
文摘One of the key issues in climate risk management is to develop climate resilient infrastructure so as to ensure safety and sustainability of urban functioning systems as well as mitigate the adverse impacts associated with increasing climate hazards.However,conventional methods of assessing risks do not fully address the interaction of various subsystems within the city system and are unable to consolidate diverse opinions of various stakeholders on their assessments of sector-specific risks posed by climate change.To address this gap,this study advances an integrated-systems-analysis tool-Climate Risk Assessment of Infrastructure Tool(CRAIT),and applies it to analyze and compare the extent of risk factor exposure and vulnerability over time across five critical urban infrastructure sectors in Shanghai and Shenzhen,two cities that have distinctive geo-climate profiles and histories of infrastructure development.The results show significantly higher level of variation between the two cities in terms of vulnerability levels than that of exposure.More specifically,the sectors of critical buildings,water,energy,and information&communication in Shenzhen have significantly higher vulnerability levels than Shanghai in both the 2000s and the 2050s.We further discussed the vulnerability levels of subsystems in each sector and proposed twelve potential adaptation options for the roads system based on four sets of criteria:technical feasibility,flexibility,co-benefits,and policy compatibility.The application of CRAIT is bound to be a knowledge co-production process with the local experts and stakeholders.This knowledge co-production process highlights the importance of management advancements and nature-based green solutions in managing climate change risk in the future though differences are observed across the efficacy categories due to the geographical and meteorological conditions in the two cities.This study demonstrates that this knowledge co-creation process is valuable in facilitating policymakers'decision-making and their feedback to scientific understanding in climate risk assessment,and that this approach has general applicability for cities in other regions and countries.
