Future changes of heating degree days （HDD） and cooling degree days （CDD） in the 21st century with and without considering populationfactor are investigated based on four sets of climate change simulations over Ea...Future changes of heating degree days （HDD） and cooling degree days （CDD） in the 21st century with and without considering populationfactor are investigated based on four sets of climate change simulations over East Asia using the regional climate model version 4.4 （RegCM4.4）driven by the global models of CSIRO-Mk3-6-0, EC-EARTH, HadGEM2-ES, and MPI-ESM-MR. Under global warming of 1.5℃, 2℃, 3℃,and 4℃, significant decrease of HDD can be found over China without considering population factor, with greater decrease over high elevationand high latitude regions, including the Tibetan Plateau, the northern part of Northeast China, and Northwest China; while population-weightedHDD increased in areas where population will increase in the future, such as Beijing, Tianjin, parts of southern Hebei, northern Shandong andHenan provinces. Similarly, the CDD projections with and without considering population factor are largely different. Specifically, withoutconsidering population, increase of CDD were observed over most parts of China except the Tibetan Plateau where the CDD remained zerobecause of the cold climate even under global warming; while considering population factor, the future CDD decreases in South China andincreases in North China, the Sichuan Basin, and the southeastern coastal areas, which is directly related to the population changes. The differentfuture changes of HDD and CDD when considering and disregarding the effects of population show that population distribution plays animportant role in energy consumption, which should be considered in future research.展开更多
A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model,version 2.0.1.The approach averages the deterministic predictions...A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model,version 2.0.1.The approach averages the deterministic predictions of precipitation from the most recent model run and from earlier runs,all at the same forecast valid time.This lagged average forecast （LAF） method assigns equal weight to each ensemble member and produces a forecast by taking the ensemble mean.Our analyses of the Equitable Threat Score,the Hanssen and Kuipers Score,and the frequency bias indicate that the LAF using five members at time-lagged intervals of 6 h improves 6-15 day forecasts of precipitation frequency above 1 mm d-1 and 5 mm d-1 in many regions of China,and is more effective than the LAF method with selection of the time-lagged interval of 12 or 24 h between ensemble members.In particular,significant improvements are seen over regions where the frequencies of rainfall days are higher than about 40％-50％ in the summer season; these regions include northeastern and central to southern China,and the southeastem Tibetan Plateau.展开更多
基于ISI-MIP(The Inter-Sectoral Impact Model Inter-comparison Project)推荐使用的5个全球气候模式数据(HadGEM2-ES,GFDL-ESM2M,MIROC-ESM-CHEM,Nor-ESM1-M,IPSL-CM5ALR),驱动SWIM(Soil and Water IntegratedModel)水文模型,研究全...基于ISI-MIP(The Inter-Sectoral Impact Model Inter-comparison Project)推荐使用的5个全球气候模式数据(HadGEM2-ES,GFDL-ESM2M,MIROC-ESM-CHEM,Nor-ESM1-M,IPSL-CM5ALR),驱动SWIM(Soil and Water IntegratedModel)水文模型,研究全球升温1.5℃和2.0℃情景下淮河上游干流径流量变化,得出结论:(1)淮河上游干流径流量年际变化在2种升温情景下均呈先减小后增加趋势。全球升温1.5℃时年径流量较基准期(1986—2005年)增长9.5%,而升温2.0℃情景下涨幅更明显,高达17%。(2) 4个季节径流量在2种升温情景下较基准期均有增长,其中春季涨幅最明显,达24.4%,夏、秋、冬季涨幅分别为7.1%、16.1%、13.5%。全球升温2.0℃时淮河上游干流径流量在4个季节较基准期增长率均大于全球升温1.5℃时。(3)不同气候模式输出日径流量最大值相差较大而平均值相差较小。未来2种升温情景日径流量超过王家坝闸设计流量的日次较基准期均有增加,尤其升温2.0℃情景较基准期增多22次,较升温1.5℃情景多5.8次,表明未来升温2.0℃情景下淮河上游出现极端径流事件的可能性进一步增大。展开更多
文摘Future changes of heating degree days （HDD） and cooling degree days （CDD） in the 21st century with and without considering populationfactor are investigated based on four sets of climate change simulations over East Asia using the regional climate model version 4.4 （RegCM4.4）driven by the global models of CSIRO-Mk3-6-0, EC-EARTH, HadGEM2-ES, and MPI-ESM-MR. Under global warming of 1.5℃, 2℃, 3℃,and 4℃, significant decrease of HDD can be found over China without considering population factor, with greater decrease over high elevationand high latitude regions, including the Tibetan Plateau, the northern part of Northeast China, and Northwest China; while population-weightedHDD increased in areas where population will increase in the future, such as Beijing, Tianjin, parts of southern Hebei, northern Shandong andHenan provinces. Similarly, the CDD projections with and without considering population factor are largely different. Specifically, withoutconsidering population, increase of CDD were observed over most parts of China except the Tibetan Plateau where the CDD remained zerobecause of the cold climate even under global warming; while considering population factor, the future CDD decreases in South China andincreases in North China, the Sichuan Basin, and the southeastern coastal areas, which is directly related to the population changes. The differentfuture changes of HDD and CDD when considering and disregarding the effects of population show that population distribution plays animportant role in energy consumption, which should be considered in future research.
基金supported by the National Basic Research Program of China (973 Program: Grant No. 2010CB951902)the Special Program for China Meteorology Trade (Grant No. GYHY201306020)the Technology Support Program of China (Grant No. 2009BAC51B03)
文摘A time-lagged ensemble method is used to improve 6-15 day precipitation forecasts from the Beijing Climate Center Atmospheric General Circulation Model,version 2.0.1.The approach averages the deterministic predictions of precipitation from the most recent model run and from earlier runs,all at the same forecast valid time.This lagged average forecast （LAF） method assigns equal weight to each ensemble member and produces a forecast by taking the ensemble mean.Our analyses of the Equitable Threat Score,the Hanssen and Kuipers Score,and the frequency bias indicate that the LAF using five members at time-lagged intervals of 6 h improves 6-15 day forecasts of precipitation frequency above 1 mm d-1 and 5 mm d-1 in many regions of China,and is more effective than the LAF method with selection of the time-lagged interval of 12 or 24 h between ensemble members.In particular,significant improvements are seen over regions where the frequencies of rainfall days are higher than about 40％-50％ in the summer season; these regions include northeastern and central to southern China,and the southeastem Tibetan Plateau.
文摘基于ISI-MIP(The Inter-Sectoral Impact Model Inter-comparison Project)推荐使用的5个全球气候模式数据(HadGEM2-ES,GFDL-ESM2M,MIROC-ESM-CHEM,Nor-ESM1-M,IPSL-CM5ALR),驱动SWIM(Soil and Water IntegratedModel)水文模型,研究全球升温1.5℃和2.0℃情景下淮河上游干流径流量变化,得出结论:(1)淮河上游干流径流量年际变化在2种升温情景下均呈先减小后增加趋势。全球升温1.5℃时年径流量较基准期(1986—2005年)增长9.5%,而升温2.0℃情景下涨幅更明显,高达17%。(2) 4个季节径流量在2种升温情景下较基准期均有增长,其中春季涨幅最明显,达24.4%,夏、秋、冬季涨幅分别为7.1%、16.1%、13.5%。全球升温2.0℃时淮河上游干流径流量在4个季节较基准期增长率均大于全球升温1.5℃时。(3)不同气候模式输出日径流量最大值相差较大而平均值相差较小。未来2种升温情景日径流量超过王家坝闸设计流量的日次较基准期均有增加,尤其升温2.0℃情景较基准期增多22次,较升温1.5℃情景多5.8次,表明未来升温2.0℃情景下淮河上游出现极端径流事件的可能性进一步增大。
