IPCC AR4多模式对海河流域气候模拟能力的评估及预估

根据海河流域1961-2010年气象观测资料,检验IPCC AR4中全球气候模式和多模式集合的模拟能力,并预估未来2011-2050年气候变化的可能趋势,结果表明:全球气候模式以及多模式集合对海河流域都具有一定的模拟能力,其中MIUB_ECHO_G模式和多模式集合具有相对较好的模拟能力.海河流域气温和降水未来情景预估表明:气温整体呈现增加趋势,尤其是A1B情景下各模式的年升温率均高于全国水平;未来降水也呈现增加趋势,在A1B和B1情景下,各模式都为夏季降水增加显著.A2情景下,春季时各模式降水均增加显著,A1B情景下,MIUB_ECHO_G模式模拟在2013年出现突变,降水量出现显著增长,A2情景下,MIUB_ECHO_G模式和多模式集合模拟的降水量则是在2031年和2001年出现突变,出现显著增长.     

基于ECHAM5模式预估2050年前中国旱涝格局趋势

 利用ECHAM5/MPI-OM气候模式输出的2001-2050年逐月降水量资料,考虑IPCC采用的3种排放情景（A2：温室气体高排放情景;A1B:温室气体中排放情景;B1：温室气体低排放情景）,计算其标准化降水指数,分析了中国2050年前3种排放情景下的旱涝格局。结果表明：3种情景下旱涝趋势空间分布不同,其中A2情景下旱涝格局同1961-2000年观测到的旱涝格局相似,均存在一条由东北向西南的干旱带;而A1B和B1情景下旱涝格局则发生了很大的变化,尤其B1情景下出现了"北涝南旱"的格局。未来50 a干旱面积在A2情景下呈略增加趋势;A1B和B1情景下为减少趋势。3种情景下干旱频率的空间分布也各不相同。     

2050年前长江流域地表水资源变化趋势

利用ECHAM5/MPI-OM气候模式预估2001-2050年长江流域不同排放情景（SRES-A2,A1B,B1）下径流深的变化,分析了长江流域地表水资源量的时空变化特征。结果表明：3种排放情景下长江流域多年平均地表水资源量相差不大,但不同排放情景下年际变化特征较为复杂,且变化趋势有所不同。其中,A2高排放情景下地表水资源量呈缓慢减小的趋势,A1B中等排放情景下变化趋势不明显,B1低排放情景下呈相对最为显著的增加趋势。地表水资源量年代际变化波动幅度也较大,2001-2030年3种情景下地表水资源量总体呈现下降特征,但从2030年起,则均表现出不同程度的增加,最高增幅达7.47%,其中尤以夏季和冬季增加显著。模式预估长江流域未来水资源量仍保持目前水平,水资源空间分布不均匀特征仍较为突出。     

2050年前长江流域地表水资源变化趋势

 利用ECHAM5/MPI-OM气候模式预估2001-2050年长江流域不同排放情景（SRES-A2,A1B,B1）下径流深的变化,分析了长江流域地表水资源量的时空变化特征。结果表明：3种排放情景下长江流域多年平均地表水资源量相差不大,但不同排放情景下年际变化特征较为复杂,且变化趋势有所不同。其中,A2高排放情景下地表水资源量呈缓慢减小的趋势,A1B中等排放情景下变化趋势不明显,B1低排放情景下呈相对最为显著的增加趋势。地表水资源量年代际变化波动幅度也较大,2001-2030年3种情景下地表水资源量总体呈现下降特征,但从2030年起,则均表现出不同程度的增加,最高增幅达7.47%,其中尤以夏季和冬季增加显著。模式预估长江流域未来水资源量仍保持目前水平,水资源空间分布不均匀特征仍较为突出。     

基于19个站的不同排放情景下贵州21世纪气候变化预估

运用IPCC AR4提供的模式预估结果,分析了基于19个站的不同排放情景下21世纪贵州气候变化特征,结果表明:21世纪贵州省将继续变暖、变湿,且人类排放越大,增温增湿的幅度越大。从未来情景气候预估的区域性特征来看,相对于基准期(1981—1999年),2011—2040年,A2(高排放)、A1B(中排放)和B1(低排放)3种排放情景下全省年平均气温偏暖在1℃以下,且省北部地区偏暖程度略大。2041—2070年,3种排放情景下全省年平均气温分别比基准期偏暖1.6~2℃、1.8~2.4℃和1.2~1.8℃,且均表现为省东北部偏暖幅度大、西南部偏暖幅度小的态势。2071—2099年,偏暖态势亦是东北部多、西南部少,3种排放情景下分别比基准期偏暖3℃以上、2.6~3.2℃和1.8~2.2℃。降水方面,前期(2011—2040年)在A2和A1B情景下相对于基准期全省年平均降水以偏少为主,偏少幅度在2%以内,在B1情景下相对于基准期省西北部降水偏少东南部降水偏多,变化幅度基本在1%以内。21世纪中期(2041—2070年)和后期(2071—2099年)在3种排放情景下全省各区域降水相对于基准期均是偏多。其中2041—2070年,3种排放情景下全省年平均降水分别偏多0%~3%,2%~5%和1%~3%,且偏多态势分布在3种情景下均不一致。2071—2099年,降水偏多的态势为南多北少,具体表现为3种排放情景下分别偏多4%以上,3%以上和2%~5%。     

珠江流域1961-2007年气候变化及2011-2060年预估分析

 根据珠江流域1961-2007年气温、降水量观测资料和ECHAM5/MPI-OM模式2011-2060年预估结果,分析了流域过去47 a的气温和降水量变化,并预估未来50 a变化趋势。结果表明,在全球变暖的背景下,过去47 a温度呈上升趋势,约升高1.8℃。冬季增温最明显,夏季最弱。未来50 a流域温度仍呈上升趋势,A1B情景下升幅约1.9℃,并且年际变化增强。A2和B1两种排放情景下秋季升温最显著,冬季最弱,A1B排放情景与此相反。过去47 a秋季降水量呈减少趋势;春、夏、冬季和年降水量均呈增加趋势。未来50 a降水总体呈增加趋势,A1B排放情景降水增加最多,约为230 mm。A2、A1B和B1情景下降水季节分配未发生显著变化。年降水和冬季降水的年际变率增强,秋季减弱。     

青藏高原及铁路沿线未来50年气候变化的模拟分析

利用由IPCC数据分发中心（DDC）提供的5个全球海气耦合模式（包括海冰与陆地生态系统）（CCCma,CCSR,CSIRO,GFDL,Hadley）气温及降水的模拟结果,对温室气体排放情景SRES-A2和B2影响下,青藏高原及铁路沿线未来50年气温和降水的变化进行了分析,包括整个青藏高原地区2011-2040年,2041-2070年的温度和降水空间分布特征以及21世纪前50年温度和降水变化的线性倾向等,结果表明：在人类活动引起的温室气体不断增加的情况下,21世纪青藏高原地区的温度将继续增加,在B2排放情景下,2011～2040年年平均温度增暖在高原主体达到1．6℃;20412070年,整个青藏高原的温度将上升2．8～3．0℃,A2排放情景下的升温幅度比B2排放情景下略高。对青藏铁路沿线地区各站A2和B2两种排放情景下,每10年平均的温度分析表明,在A2排放情景下,到2050年前后青藏铁路沿线各站的温度增加将是2010年时的2～3倍左右,A2时在2．56～2．96℃之间,B2时在2．37～2．65℃之间。对21世纪前50年整个青藏高原地区温度变化的线性倾向的空间分布的分析可知,在A2排放情景下,大部分都在1.5～2．5℃／50a,冬季大部分地区的变暖倾向都在2．0℃／50a以上,有些地区达到2．5℃／50a以上,夏季在2℃／50a左右;B2时青藏高原地区温度变化倾向的分布趋势与A2时基本一致,只是变化的数值偏低约0．5℃。对21世纪青藏高原地区降水变化的预估结果表明,与温度不同,在两种不同的排放情景下,降水的变化较为复杂。总体来说,21世纪前50年青藏高原大部分地区的降水为增加趋势。     

5个IPCC AR4全球气候模式对东北三省降水模拟与预估

利用IPCC AR4中5个全球气候模式数据集和中国东北三省162个站降水实测资料,评估5个全球气候模式和多模式集合平均对中国东北三省降水的模拟能力,并对SRES B1、A1B和A2三种排放情景东北三省未来降水变化进行预估。结果表明：全球气候模式能较好再现东北三省降水的月变化,但存在系统性湿偏差;多模式集合平均能较好模拟东北三省年降水量的空间分布,但模拟中心偏北,强度略强,模式对东北三省夏季降水的模拟效果优于冬季降水;预估结果表明,三种排放情景下21世纪中前期和末期东北三省降水均将增多,21世纪末期增幅高于21世纪中前期,冬季增幅高于其他季节;就排放情景而言,SRES A1B和A2排放情景增幅相当,高于B1排放情景增幅;不同排放情景东北三省降水量增率分布呈较一致变化,A2排放情景下,增幅最显著的辽宁环渤海地区年降水量在21世纪中前期将增加7%以上,21世纪末期将增加16%。     

CMIP5模式对长江流域气温模拟与预估

利用长江流域147个气象观测站1961—2000年观测数据,对两个多模式集合CMIP3和CMIP5在长江流域气温模拟效果进行了评估,并进一步利用CMIP5输出结果预估2011—2050年长江流域气温时空变化。结果表明:两个多模式集合对长江流域气温具有一定的模拟能力,相对于CMIP3,CMIP5对实验期后20 a的年均气温变化的模拟效果更好,对年均气温变化倾向率的空间分布更加接近实测。预估表明:长江流域年均气温在3种RCPs情景下呈显著增加趋势,长江中下游变暖幅度要高于长江上游,到2050年,全流域气温都增加1.0℃以上。     

CMIP5和RegCM4.0模式对西南区域未来降水的预估

利用CMIP5全球模式数据集和RegCM4.0区域气候模式进行连续积分获得的模拟数据,对西南区域未来在RCP2.6,RCP4.5和RCP8.5几种温室气体排放情景下年平均降雨、四季降水,极端降雨事件的特征及其相对历史基准期的变化进行预估。结果表明,不同RCP情景下西南区域降水都将呈持续上升趋势,3种情景下西南区域降水在2020—2050年变化特征差别较小,2050年后差别较大,RCP2.6情景下降水变化幅度最小,CMIP5和RegCM4.0模式模拟的西南区域降水变化的地理分布特征基本一致,降水的高值区都位于青藏高原东南部,横断山脉和四川中部,差异在于RegCM4.0模拟的西藏西部的降雨量级更小,而青藏高原东南部、四川中部和贵州的降雨高值区量级更大。未来近期2020—2060年和远期2061—2099年RCP4.5情景下暴雨天数显著减少的区域主要在西藏东南部(0.5~1 d),未来远期2061—2099年RCP4.5情景云南南部和贵州东部区域暴雨天数显著性增加,而RCP8.5情景下上述区域暴雨天数显著性减少。     

Impacts of cumulus momentum transport on MJO simulation

Vertical cumulus momentum transport is an important physical process in the tropical atmosphere and plays a key role in the evolution of the tropical atmospheric system. This paper focuses on the impact of the vertical cumulus momentum transport on Madden-Julian Oscillation (MJO) simulation in two global climate models (GCMs). The Tiedtke cumulus parameterization scheme is applied to both GCMs [CAM2 and Spectral Atmospheric general circulation Model of LASG/IAP (SAMIL)]. It is found that the MJO simulation ability might be influenced by the vertical cumulus momentum transport through the cumulus parameterization scheme. However, the use of vertical momentum transport in different models provides different results. In order to improve model's MJO simulation ability, we must introduce vertical cumulus momentum transport in a more reasonable way into models. Furthermore, the coherence of the parameterization and the underlying model also need to be considered.     

Downscaling reveals diverse effects of anthropogenic climate warming on the potential for local environments to support malaria transmission

The potential impact of climate warming on patterns of malaria transmission has been the subject of keen scientific and policy debate. Standard climate models (GCMs) characterize climate change at relatively coarse spatial and temporal scales. However, malaria parasites and the mosquito vectors respond to diurnal variations in conditions at very local scales. Here we bridge this gap by downscaling a series of GCMs to provide high-resolution temperature data for four different sites and show that although outputs from both the GCM and the downscaled models predict diverse but qualitatively similar effects of warming on the potential for adult mosquitoes to transmit malaria, the predicted magnitude of change differs markedly between the different model approaches. Raw GCM model outputs underestimate the effects of climate warming at both hot (3-fold) and cold (8–12 fold) extremes, and overestimate (3-fold) the change under intermediate conditions. Thus, downscaling could add important insights to the standard application of coarse-scale GCMs for biophysical processes driven strongly by local microclimatic conditions.     

Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes

Future climate projections from general circulation models (GCMs) predict an acceleration of the global hydrological cycle throughout the 21st century in response to human-induced rise in temperatures. However, projections of GCMs are too coarse in resolution to be used in local studies of climate change impacts. To cope with this problem, downscaling methods have been developed that transform climate projections into high resolution datasets to drive impact models such as rainfall-runoff models. Generally, the range of changes simulated by different GCMs is considered to be the major source of variability in the results of such studies. However, the cascade of uncertainty in runoff projections is further elongated by differences between impact models, especially where robust calibration is hampered by the scarcity of data. Here, we address the relative importance of these different sources of uncertainty in a poorly monitored headwater catchment of the Ecuadorian Andes. Therefore, we force 7 hydrological models with downscaled outputs of 8 GCMs driven by the A1B and A2 emission scenarios over the 21st century. Results indicate a likely increase in annual runoff by 2100 with a large variability between the different combinations of a climate model with a hydrological model. Differences between GCM projections introduce a gradually increasing relative uncertainty throughout the 21st century. Meanwhile, structural differences between applied hydrological models still contribute to a third of the total uncertainty in late 21st century runoff projections and differences between the two emission scenarios are marginal.     

热带季节内振荡模拟研究的若干进展

大气季节内振荡（ISO）在长期天气和气候变化中有重要作用，它是20世纪70～80年代以来大气科学领域的重要研究课题。本文简要介绍近年来季节内振荡的数值模拟研究的成果和进展，包括数值模式模拟季节内振荡能力的进展； 模式模拟ISO能力对模式中对流参数化方案的敏感性；ISO模拟结果与基本态的关系；外强迫对模拟结果的影响； ENSO与ISO关系的模拟研究，以及全球变暖对ISO影响的模拟研究等。最后，对今后的研究工作提出了一些建议。     

Climate change projections of the North American Regional Climate Change Assessment Program (NARCCAP)

We investigate major results of the NARCCAP multiple regional climate model (RCM) experiments driven by multiple global climate models (GCMs) regarding climate change for seasonal temperature and precipitation over North America. We focus on two major questions: How do the RCM simulated climate changes differ from those of the parent GCMs and thus affect our perception of climate change over North America, and how important are the relative contributions of RCMs and GCMs to the uncertainty (variance explained) for different seasons and variables? The RCMs tend to produce stronger climate changes for precipitation: larger increases in the northern part of the domain in winter and greater decreases across a swath of the central part in summer, compared to the four GCMs driving the regional models as well as to the full set of CMIP3 GCM results. We pose some possible process-level mechanisms for the difference in intensity of change, particularly for summer. Detailed process-level studies will be necessary to establish mechanisms and credibility of these results. The GCMs explain more variance for winter temperature and the RCMs for summer temperature. The same is true for precipitation patterns. Thus, we recommend that future RCM-GCM experiments over this region include a balanced number of GCMs and RCMs.     

A quantitative performance assessment of cloud regimes in climate models

Differences in the radiative feedback from clouds account for much of the variation in climate sensitivity amongst General Circulation Models (GCMs). Therefore metrics of model performance which are demonstrated to be relevant to the cloud response to climate change form an important contribution to the overall evaluation of GCMs. In this paper we demonstrate an alternative method for assigning model data to observed cloud regimes obtained from clustering histograms of cloud amount in joint cloud optical depth—cloud top pressure classes. The method removes some of the subjectivity that exists in previous GCM cloud clustering studies. We apply the method to ten GCMs submitted to the Cloud Feedback Model Intercomparison Project (CFMIP), evaluate the simulated cloud regimes and analyse the climate change response in the context of these regimes. We also propose two cloud regime metrics, one of which is specifically targeted at assessing GCMs for the purpose of obtaining the global cloud radiative response to climate change. Most of the global variance in the cloud radiative response between GCMs is due to low clouds, with 47% arising from the stratocumulus regime and 18% due to the regime characterised by clouds undergoing transition from stratocumulus to cumulus. This result is found to be dominated by two structurally similar GCMs. The shallow cumulus regime, though widespread, has a smaller contribution and reduces the variance. For the stratocumulus and transition regimes, part of the variance results from a large model spread in the radiative properties of the regime in the control simulation. Comparison with observations reveals a systematic bias for both the stratocumulus and transition regimes to be overly reflective. If this bias was corrected with all other aspects of the response unchanged, the variance in the low cloud response would reduce. The response of some regimes with high cloud tops differ between the GCMs. These regimes are simulated too infrequently in a few of the models. If the frequency in the control simulation were more realistic and changes within the regimes were unaltered, the variance in the cloud radiative response from high-top clouds would increase. As a result, use of observations of the mean present-day cloud regimes suggests that whilst improvements in the simulation of the cloud regimes would impact the climate sensitivity, the inter-model variance may not reduce. When the cloud regime metric is calculated for the GCMs analysed here, only one model is on average consistent with observations within their uncertainty (and even this model is not consistent with the observations for all regimes), indicating scope for improvement in the simulation of cloud regimes. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Climate projections over CORDEX Africa domain using the fifth-generation Canadian Regional Climate Model (CRCM5)

Following the CORDEX experimental protocol, climate simulations and climate-change projections for Africa were made with the new fifth-generation Canadian Regional Climate Model (CRCM5). The model was driven by two Global Climate Models (GCMs), one developed by the Max-Planck-Institut für Meteorologie and the other by the Canadian Centre for Climate Modelling and Analysis, for the period 1950–2100 under the RCP4.5 emission scenario. The performance of the CRCM5 simulations for current climate is discussed first and compared also with a reanalysis-driven CRCM5 simulation. It is shown that errors in lateral boundary conditions and sea-surface temperature from the GCMs have deleterious consequences on the skill of the CRCM5 at reproducing specific regional climate features such as the West African Monsoon and the annual cycle of precipitation. For other aspects of the African climate however the regional model is able to add value compared to the simulations of the driving GCMs. Climate-change projections for periods until the end of this century are also analysed. All models project a warming throughout the twenty-first century, although the details of the climate changes differ notably between model projections, especially for precipitation changes. It is shown that the climate changes projected by CRCM5 often differ noticeably from those of the driving GCMs.     

随机天气模型参数化方案的研究及其模拟能力评估

文中介绍了随机天气模型 WGEN的基本结构及其模拟原理 ,并针对其中随机过程的统计结构特征和 GCMs输出要素的不同时空尺度特点 ,利用动态数据的参数化分析方法等统计学技术 ,确定了该模型参数的估计方法。同时基于蒙特卡罗数值计算原理 ,给出了 WGEN的随机试验方法 ,并通过模拟基准气候 ,从时间分布和空间场两方面对模型在中国东北地区的模拟效果及其能力进行了评估。结果表明 ,模型对于最高气温、最低气温、降水和辐射等要素均具有较好的模拟效果 ,模拟序列与观测序列的取值分布有较一致的概率特性。由此可以结合 GCMs大尺度网格上输出的月和年要素值 ,通过调控随机过程的参数 ,生成具有不同气候变率的 2× CO2 逐日气候变化情景 ,实现气候预测模式与气候影响模式的嵌套 ,进一步研究气候变率变化的可能影响。     

GCM intercomparison of global cloud regimes: present-day evaluation and climate change response

The radiative feedback from clouds remains the largest source of variation in climate sensitivity amongst general circulation models (GCMs). A cloud clustering methodology is applied to six contemporary GCMs in order to provide a detailed intercomparison and evaluation of the simulated cloud regimes. By analysing GCMs in the context of cloud regimes, processes related to particular cloud types are more likely to be evaluated. In this paper, the mean properties of the global cloud regimes are evaluated, and the cloud response to climate change is analysed in the cloud-regime framework. Most of the GCMs are able to simulate the principal cloud regimes, however none of the models analysed have a good representation of trade cumulus in the tropics. The models also share a difficulty in simulating those regimes with cloud tops at mid-levels, with only ECHAM5 producing a regime of tropical cumulus congestus. Optically thick, high top cloud in the extra-tropics, typically associated with the passage of frontal systems, is simulated considerably too frequently in the ECHAM5 model. This appears to be a result of the cloud type persisting in the model after the meteorological conditions associated with frontal systems have ceased. The simulation of stratocumulus in the MIROC GCMs is too extensive, resulting in the tropics being too reflective. Most of the global-mean cloud response to doubled CO₂ in the GCMs is found to be a result of changes in the cloud radiative properties of the regimes, rather than changes in the relative frequency of occurrence (RFO) of the regimes. Most of the variance in the global cloud response between the GCMs arises from differences in the radiative response of frontal cloud in the extra-tropics and from stratocumulus cloud in the tropics. This variance is largely the result of excessively high RFOs of specific regimes in particular GCMs. It is shown here that evaluation and subsequent improvement in the simulation of the present-day regime properties has the potential to reduce the variance of the global cloud response, and hence climate sensitivity, amongst GCMs. For the ensemble of models considered in this study, the use of observations of the mean present-day cloud regimes suggests a potential reduction in the range of climate sensitivity of almost a third. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Evaluation of a component of the cloud response to climate change in an intercomparison of climate models

Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time–mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption is made that the quantity evaluated is relevant for the mean climate change response. Nine GCMs (atmosphere models coupled to mixed-layer ocean models) from the CFMIP and CMIP model comparison projects are used in this study to demonstrate a common relationship between the mean cloud response to climate change and present-day variability. Although atmosphere–mixed-layer ocean models are used here, the results are found to be equally applicable to transient coupled model simulations. When changes in cloud radiative forcing (CRF) are composited by changes in vertical velocity and saturated lower tropospheric stability, a component of the local mean climate change response can be related to present-day variability in all of the GCMs. This suggests that the relationship is not model specific and might be relevant in the real world. In this case, evaluation within the proposed compositing framework is a direct evaluation of a component of the cloud response to climate change. None of the models studied are found to be clearly superior or deficient when evaluated, but a couple appear to perform well on several relevant metrics. Whilst some broad similarities can be identified between the 60°N–60°S mean change in CRF to increased CO₂ and that predicted from present-day variability, the two cannot be quantitatively constrained based on changes in vertical velocity and stability alone. Hence other processes also contribute to the global mean cloud response to climate change.