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1.
Projected increased risk of water deficit over major West African river basins under future climates
Mouhamadou Bamba Sylla Aissatou Faye Nana Ama Browne Klutse Kangbeni Dimobe 《Climatic change》2018,149(2):247-260
Despite decades of research, large multi-model uncertainty remains about the Earth’s equilibrium climate sensitivity to carbon dioxide forcing as inferred from state-of-the-art Earth system models (ESMs). Statistical treatments of multi-model uncertainties are often limited to simple ESM averaging approaches. Sometimes models are weighted by how well they reproduce historical climate observations. Here, we propose a novel approach to multi-model combination and uncertainty quantification. Rather than averaging a discrete set of models, our approach samples from a continuous distribution over a reduced space of simple model parameters. We fit the free parameters of a reduced-order climate model to the output of each member of the multi-model ensemble. The reduced-order parameter estimates are then combined using a hierarchical Bayesian statistical model. The result is a multi-model distribution of reduced-model parameters, including climate sensitivity. In effect, the multi-model uncertainty problem within an ensemble of ESMs is converted to a parametric uncertainty problem within a reduced model. The multi-model distribution can then be updated with observational data, combining two independent lines of evidence. We apply this approach to 24 model simulations of global surface temperature and net top-of-atmosphere radiation response to abrupt quadrupling of carbon dioxide, and four historical temperature data sets. Our reduced order model is a 2-layer energy balance model. We present probability distributions of climate sensitivity based on (1) the multi-model ensemble alone and (2) the multi-model ensemble and observations. 相似文献
2.
Jorge Perez Melisa Menendez Fernando J. Mendez Inigo J. Losada 《Climate Dynamics》2014,43(9-10):2663-2680
One of the main sources of uncertainty in estimating climate projections affected by global warming is the choice of the global climate model (GCM). The aim of this study is to evaluate the skill of GCMs from CMIP3 and CMIP5 databases in the north-east Atlantic Ocean region. It is well known that the seasonal and interannual variability of surface inland variables (e.g. precipitation and snow) and ocean variables (e.g. wave height and storm surge) are linked to the atmospheric circulation patterns. Thus, an automatic synoptic classification, based on weather types, has been used to assess whether GCMs are able to reproduce spatial patterns and climate variability. Three important factors have been analyzed: the skill of GCMs to reproduce the synoptic situations, the skill of GCMs to reproduce the historical inter-annual variability and the consistency of GCMs experiments during twenty-first century projections. The results of this analysis indicate that the most skilled GCMs in the study region are UKMO-HadGEM2, ECHAM5/MPI-OM and MIROC3.2(hires) for CMIP3 scenarios and ACCESS1.0, EC-EARTH, HadGEM2-CC, HadGEM2-ES and CMCC-CM for CMIP5 scenarios. These models are therefore recommended for the estimation of future regional multi-model projections of surface variables driven by the atmospheric circulation in the north-east Atlantic Ocean region. 相似文献
3.
Significance of model credibility in estimating climate projection distributions for regional hydroclimatological risk assessments 总被引：1，自引：1，他引：0
Levi D. Brekke Michael D. Dettinger Edwin P. Maurer Michael Anderson 《Climatic change》2008,89(3-4):371-394
Ensembles of historical climate simulations and climate projections from the World Climate Research Programme’s (WCRP’s) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset were investigated to determine how model credibility affects apparent relative scenario likelihoods in regional risk assessments. Methods were developed and applied in a Northern California case study. An ensemble of 59 twentieth century climate simulations from 17 WCRP CMIP3 models was analyzed to evaluate relative model credibility associated with a 75-member projection ensemble from the same 17 models. Credibility was assessed based on how models realistically reproduced selected statistics of historical climate relevant to California climatology. Metrics of this credibility were used to derive relative model weights leading to weight-threshold culling of models contributing to the projection ensemble. Density functions were then estimated for two projected quantities (temperature and precipitation), with and without considering credibility-based ensemble reductions. An analysis for Northern California showed that, while some models seem more capable at recreating limited aspects twentieth century climate, the overall tendency is for comparable model performance when several credibility measures are combined. Use of these metrics to decide which models to include in density function development led to local adjustments to function shapes, but led to limited affect on breadth and central tendency, which were found to be more influenced by “completeness” of the original ensemble in terms of models and emissions pathways. 相似文献
4.
Evaluation of CMIP5 Earth System Models in Reproducing Leaf Area Index and Vegetation Cover over the Tibetan Plateau 
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下载免费PDF全文 BAO Yan GAO Yanhong L&#; Shihu WANG Qingxi ZHANG Shaobo XU Jianwei LI Ruiqing LI Suosuo MA Di MENG Xianhong CHEN Hao CHANG Yan 《Acta Meteorologica Sinica》2014,28(6):1041-1060
The abilities of 12 earth system models (ESMs) from the Coupled Model Intercomparison Project Phase5 (CMIP5) to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau (TP) were examined. The results show that most of the models tend to overestimate the observed leaf area index (LAI) and vegetation carbon above the ground, with the possible reasons being overestimation of photosynthesis and precipitation. The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005, while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions. Three of the models: CCSM4, CESM1-BGC, and NorESM1-ME, which share the same vegetation model, show some common strengths and weaknesses in their simulations according to our analysis. The model ensemble indicates a reasonable spatial distribution but overestimated land coverage, with a significant decreasing trend (-1.48% per decade) for tree coverage and a slight increasing trend (0.58% per decade) for bare ground during the period 1950-2005. No significant sign of variation is found for grass. To quantify the relative performance of the models in representing the observed mean state, seasonal cycle, and interannual variability, a model ranking method was performed with respect to simulated LAI. INMCM4, bcc-csm-1.1m, MPI-ESM-LR, IPSL CM5A-LR, HadGEM2-ES, and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models. 相似文献
5.
The use of radiative kernels to diagnose climate feedbacks is a recent development that may be applied to existing climate change simulations. We apply the radiative kernel technique to transient simulations from a multi-thousand member perturbed physics ensemble of coupled atmosphere-ocean general circulation models, comparing distributions of model feedbacks with those taken from the CMIP-3 multi GCM ensemble. Although the range of clear sky longwave feedbacks in the perturbed physics ensemble is similar to that seen in the multi-GCM ensemble, the kernel technique underestimates the net clear-sky feedbacks (or the radiative forcing) in some perturbed models with significantly altered humidity distributions. In addition, the compensating relationship between global mean atmospheric lapse rate feedback and water vapor feedback is found to hold in the perturbed physics ensemble, but large differences in relative humidity distributions in the ensemble prevent the compensation from holding at a regional scale. Both ensembles show a similar range of response of global mean net cloud feedback, but the mean of the perturbed physics ensemble is shifted towards more positive values such that none of the perturbed models exhibit a net negative cloud feedback. The perturbed physics ensemble contains fewer models with strong negative shortwave cloud feedbacks and has stronger compensating positive longwave feedbacks. A principal component analysis used to identify dominant modes of feedback variation reveals that the perturbed physics ensemble produces very different modes of climate response to the multi-model ensemble, suggesting that one may not be used as an analog for the other in estimates of uncertainty in future response. Whereas in the multi-model ensemble, the first order variation in cloud feedbacks shows compensation between longwave and shortwave components, in the perturbed physics ensemble the shortwave feedbacks are uncompensated, possibly explaining the larger range of climate sensitivities observed in the perturbed simulations. Regression analysis suggests that the parameters governing cloud formation, convection strength and ice fall speed are the most significant in altering climate feedbacks. Perturbations of oceanic and sulfur cycle parameters have relatively little effect on the atmospheric feedbacks diagnosed by the kernel technique. 相似文献
6.
Decadal variability in the climate system from the Atlantic Multidecadal Oscillation (AMO) is one of the major sources of variability at this temporal scale that climate models must properly incorporate because of its climate impact. The current analysis of historical simulations of the twentieth century climate from models participating in the CMIP3 and CMIP5 projects assesses how these models portray the observed spatiotemporal features of the sea surface temperature (SST) and precipitation anomalies associated with the AMO. A short sample of the models is analyzed in detail by using all ensembles available of the models CCSM3, GFDL-CM2.1, UKMO-HadCM3, and ECHAM5/MPI-OM from the CMIP3 project, and the models CCSM4, GFDL-CM3, UKMO-HadGEM2-ES, and MPI-ESM-LR from the CMIP5 project. The structure and evolution of the SST anomalies of the AMO have not progressed consistently from the CMIP3 to the CMIP5 models. While the characteristic period of the AMO (smoothed with a binomial filter applied fifty times) is underestimated by the three of the models, the e-folding time of the autocorrelations shows that all models underestimate the 44-year value from observations by almost 50 %. Variability of the AMO in the 10–20/70–80 year ranges is overestimated/underestimated in the models and the variability in the 10–20 year range increases in three of the models from the CMIP3 to the CMIP5 versions. Spatial variability and correlation of the AMO regressed precipitation and SST anomalies in summer and fall indicate that models are not up to the task of simulating the AMO impact on the hydroclimate over the neighboring continents. This is in spite of the fact that the spatial variability and correlations in the SST anomalies improve from CMIP3 to CMIP5 versions in two of the models. However, a multi-model mean from a sample of 14 models whose first ensemble was analyzed indicated there were no improvements in the structure of the SST anomalies of the AMO or associated regional precipitation anomalies in summer and fall from CMIP3 to CMIP5 projects. 相似文献
7.
利用参与第三次古气候模式评估比较计划（Paleoclimate Modelling Intercomparison Project Phase III,PMIP3）过去千年气候模拟试验以及参与第五次耦合模式评估比较计划（Paleoclimate Model Intercomparison Project Phase 5,CMIP5）全强迫历史情景试验的9个地球系统模式模拟试验结果,对过去千年3个特征时段（中世纪气候异常期、小冰期和现代暖期）北极涛动（Arctic Oscillation, AO）的变率及成因进行了分析。通过与NCEP再分析资料的对比发现,模式能够较好地模拟出AO的空间模态及年际变化周期,且大部分模式能够模拟出过去50年AO的增强趋势。过去千年3个特征时段中,不同模式对中世纪气候异常期AO位相的模拟并不一致,但大部分模式显示小冰期AO基本呈现负位相,而现代暖期则表现为显著的正位相,与重建结果一致。基于多模式集合平均的机制分析表明,中世纪气候异常期北极地区海平面气压变化不显著,小冰期北极地区海平面气压显著偏正,现代暖期海平面气压显著偏负,这与现代暖期北极温度偏高而小冰期北极温度偏低有关。过去千年中,小冰期和现代暖期的AO变率分别受自然外强迫和人为外强迫的影响。 相似文献
8.
Jinming Feng Dong-Kyou Lee Congbin Fu Jianping Tang Yasuo Sato Hisashi Kato John L. Mcgregor Kazuo Mabuchi 《Meteorology and Atmospheric Physics》2011,111(1-2):41-53
A number of uncertainties exist in climate simulation because the results of climate models are influenced by factors such as their dynamic framework, physical processes, initial and driving fields, and horizontal and vertical resolution. The uncertainties of the model results may be reduced, and the credibility can be improved by employing multi-model ensembles. In this paper, multi-model ensemble results using 10-year simulations of five regional climate models (RCMs) from December 1988 to November 1998 over Asia are presented and compared. The simulation results are derived from phase II of the Regional Climate Model Inter-comparison Project (RMIP) for Asia. Using the methods of the arithmetic mean, the weighted mean, multivariate linear regression, and singular value decomposition, the ensembles for temperature, precipitation, and sea level pressure are carried out. The results show that the multi-RCM ensembles outperform the single RCMs in many aspects. Among the four ensemble methods used, the multivariate linear regression, based on the minimization of the root mean square errors, significantly improved the ensemble results. With regard to the spatial distribution of the mean climate, the ensemble result for temperature was better than that for precipitation. With an increasing number of models used in the ensembles, the ensemble results were more accurate. Therefore, a multi-model ensemble is an efficient approach to improve the results of regional climate simulations. 相似文献
9.
Using 32 CMIP5(Coupled Model Intercomparison Project Phase 5) models, this study examines the veracity in the simulation of cloud amount and their radiative effects(CREs) in the historical run driven by observed external radiative forcing for 1850–2005, and their future changes in the RCP(Representative Concentration Pathway) 4.5 scenario runs for2006–2100. Validation metrics for the historical run are designed to examine the accuracy in the representation of spatial patterns for climatological mean, and annual and interannual variations of clouds and CREs. The models show large spread in the simulation of cloud amounts, specifically in the low cloud amount. The observed relationship between cloud amount and the controlling large-scale environment are also reproduced diversely by various models. Based on the validation metrics,four models—ACCESS1.0, ACCESS1.3, Had GEM2-CC, and Had GEM2-ES—are selected as best models, and the average of the four models performs more skillfully than the multimodel ensemble average.All models project global-mean SST warming at the increase of the greenhouse gases, but the magnitude varies across the simulations between 1 and 2 K, which is largely attributable to the difference in the change of cloud amount and distribution. The models that simulate more SST warming show a greater increase in the net CRE due to reduced low cloud and increased incoming shortwave radiation, particularly over the regions of marine boundary layer in the subtropics. Selected best-performing models project a significant reduction in global-mean cloud amount of about-0.99% K~(-1)and net radiative warming of 0.46 W m~(-2)K~(-1), suggesting a role of positive feedback to global warming. 相似文献
10.
We explore the potential to improve understanding of the climate system by directly targeting climate model analyses at specific indicators of climate change impact. Using the temperature suitability of premium winegrape cultivation as a climate impacts indicator, we quantify the inter- and intra-ensemble spread in three climate model ensembles: a physically uniform multi-member ensemble consisting of the RegCM3 high-resolution climate model nested within the NCAR CCSM3 global climate model; the multi-model NARCCAP ensemble consisting of single realizations of multiple high-resolution climate models nested within multiple global climate models; and the multi-model CMIP3 ensemble consisting of realizations of multiple global climate models. We find that the temperature suitability for premium winegrape cultivation is substantially reduced throughout the high-value growing areas of California and the Columbia Valley region (eastern Oregon and Washington) in all three ensembles in response to changes in temperature projected for the mid-twenty first century period. The reductions in temperature suitability are driven primarily by projected increases in mean growing season temperature and occurrence of growing season severe hot days. The intra-ensemble spread in the simulated climate change impact is smaller in the single-model ensemble than in the multi-model ensembles, suggesting that the uncertainty arising from internal climate system variability is smaller than the uncertainty arising from climate model formulation. In addition, the intra-ensemble spread is similar in the NARCCAP nested climate model ensemble and the CMIP3 global climate model ensemble, suggesting that the uncertainty arising from the model formulation of fine-scale climate processes is not smaller than the uncertainty arising from the formulation of large-scale climate processes. Correction of climate model biases substantially reduces both the inter- and intra-ensemble spread in projected climate change impact, particularly for the multi-model ensembles, suggesting that—at least for some systems—the projected impacts of climate change could be more robust than the projected climate change. Extension of this impacts-based analysis to a larger suite of impacts indicators will deepen our understanding of future climate change uncertainty by focusing on the climate phenomena that most directly influence natural and human systems. 相似文献
11.
Climate model errors, feedbacks and forcings: a comparison of perturbed physics and multi-model ensembles 总被引：4，自引：4，他引：0
Matthew Collins Ben B. B. Booth B. Bhaskaran Glen R. Harris James M. Murphy David M. H. Sexton Mark J. Webb 《Climate Dynamics》2011,36(9-10):1737-1766
Ensembles of climate model simulations are required for input into probabilistic assessments of the risk of future climate change in which uncertainties are quantified. Here we document and compare aspects of climate model ensembles from the multi-model archive and from perturbed physics ensembles generated using the third version of the Hadley Centre climate model (HadCM3). Model-error characteristics derived from time-averaged two-dimensional fields of observed climate variables indicate that the perturbed physics approach is capable of sampling a relatively wide range of different mean climate states, consistent with simple estimates of observational uncertainty and comparable to the range of mean states sampled by the multi-model ensemble. The perturbed physics approach is also capable of sampling a relatively wide range of climate forcings and climate feedbacks under enhanced levels of greenhouse gases, again comparable with the multi-model ensemble. By examining correlations between global time-averaged measures of model error and global measures of climate change feedback strengths, we conclude that there are no simple emergent relationships between climate model errors and the magnitude of future global temperature change. Algorithms for quantifying uncertainty require the use of complex multivariate metrics for constraining projections. 相似文献
12.
利用国际耦合模式比较计划第六阶段（CMIP6）的全球气候模式历史模拟试验资料，通过旋转经验正交函数分析得到了CMIP6模式中的我国冬季气温变化主要的区域空间模态。结果表明：CMIP6多模式集合平均中我国冬季气温有4个主要的区域空间模态，分别为中原—西北型，华南型，东北型以及滇藏型。其中，东北型与滇藏型是较为稳定的空间模态，在所选CMIP6模式及观测资料中都稳定存在，这也是前人研究中一致性较高的模态。而我国新疆、西北、华中及华南地区的冬季气温在空间分型上存在分歧，这些地区的分型在以往研究中的一致性也较差。华南型在所选CMIP6模式内是一致存在的模态，中原—西北型在模式内部的差异性较大。在近40 a观测资料中，新疆及西北到我国南方为统一的空间分型，在CMIP6多模式集合平均的结果中新疆及西北地区气温空间分布与我国中原地区的联系更为紧密。CMIP6模式能较好地模拟出与低温空间分布有直接联系的对流层中层的槽的位置，当CMIP6模式和观测中的冬季气温都表现为同一个空间模态时，该模态所对应的对流层中层的主要环流系统在观测和CMIP6模式中也是一致的。 相似文献
13.
Detlef P. van Vuuren Jason Lowe Elke Stehfest Laila Gohar Andries F. Hof Chris Hope Rachel Warren Malte Meinshausen Gian-Kasper Plattner 《Climatic change》2011,104(2):255-285
Integrated assessment models (IAMs) are regularly used to evaluate different policies of future emissions reductions. Since
the global costs associated with these policies are immense, it is vital that the uncertainties in IAMs are quantified and
understood. We first demonstrate the significant spread in the climate system and carbon cycle components of several contemporary
IAMs. We then examine these components in more detail to understand the causes of differences, comparing the results with
more complex climate models and earth system models (ESMs), where available. Our results show that in most cases the outcomes
of IAMs are within the range of the outcomes of complex models, but differences are large enough to matter for policy advice.
There are areas where IAMs would benefit from improvements (e.g. climate sensitivity, inertia in climate response, carbon
cycle feedbacks). In some cases, additional climate model experiments are needed to be able to tune some of these improvements.
This will require better communication between the IAM and ESM development communities. 相似文献
14.
利用第5次耦合模式比较计划(CMIP5)提供的39个全球气候模式模拟的1961—2005年逐月500 hPa位势高度场资料,以及同期美国国家环境预测中心再分析资料,通过经验正交函数分解提取主要模态,基于泰勒图方法、概率密度函数的Brier评分和显著性评分指标,探讨CMIP5模式对东亚500 hPa高度场主要模态时空结构的模拟能力,寻求具有较好东亚环流型态模拟能力的气候模式以及模拟较好的主模态。结果表明:(1) CMIP5模式能够模拟出东亚500 hPa高度场主要模态,且各模式对冬季主要模态时空结构的模拟能力都高于夏季。(2) 各模式对冬季模态(西太平洋遥相关型)模拟能力最强,第3模态最差,对冬季主要模态空间结构模拟较好的模式为IPSL-CM5B-LR、MPI-ESM-P、CMCC-CMS、FGOALS-g2、HadGEM2-ES;夏季第1模态空间结构模拟能力最强,其次分别为第2模态和东亚-太平洋型(简记第3模态),西太平洋遥相关型较差,对夏季主要模态空间结构模拟较好的模式为ECEARTH、CanESM2、CMCC-CM、GFDL-ESM2G、IPSL-CM5A-MR。(3)对主要模态时间系数概率密度函数特征的模拟评估表明,模式对冬季第2模态概率密度函数的模拟较好,其次为西太平洋遥相关型,其主要模态时间系数的概率密度函数模拟较好的模式为CESM1-FASTCHEM、HadGEM2-ES、INM-CM4、GISS-E2-H、BCC-CSM1-1;模式对夏季第2模态时间系数的概率密度函数模拟较好,其次分别为第3模态、西太平洋遥相关型,其主要模态时间系数概率密度函数模拟较好的模式为CCSM4、HadGEM2-CC、GFDL-CM3、MRI-CGCM3、NorESM1-M。(4)综合时空结构模式模拟能力,对冬季主要模态模拟较好的前5个模式为HadGEM2-ES、IPSL-CM5B-LR、CESM1-FASTCHEM、INM-CM4、BCC-CSM1-1;夏季前5个模式为ECEARTH、CMCC-CM、CCSM4、CANESM2、MIROC5。 相似文献
15.
Regional and seasonal intercomparison of CMIP3 and CMIP5 climate model ensembles for temperature and precipitation 总被引：2，自引：1，他引：1
Regional and seasonal temperature and precipitation over land are compared across two generations of global climate model ensembles, specifically, CMIP5 and CMIP3, through historical twentieth century skills and multi-model agreement, and twenty first century projections. A suite of diagnostic and performance metrics, ranging from spatial bias or model-consensus maps and aggregate time series plots, to measures of equivalence between probability density functions and Taylor diagrams, are used for the intercomparisons. Pairwise and multi-model ensemble comparisons were performed for 11 models, which were selected based on data availability and resolutions. Results suggest little change in the central tendency or variability or uncertainty of historical skills or consensus across the two generations of models. However, there are regions and seasons, at different levels of aggregation, where significant changes, performance improvements, and even degradation in skills, are suggested. The insights may provide directions for further improvements in next generations of climate models, and in the meantime, help inform adaptation and policy. 相似文献
16.
CMIP5模式对中国年平均气温模拟及其与CMIP3模式的比较 总被引：5，自引：0，他引：5
利用CRUT3v和CN05两套观测资料,评估25个CMIP5模式对1906-2005年中国年平均气温变化的模拟能力,并与CMIP3模式对比。结果表明：1906-2005年中国平均温升速率为0.84℃/100a,CMIP5多模式集合平均模拟的增温率为0.77℃/100a。模式对20世纪后期温升模拟好于前期,仅有两个模式能模拟中国20世纪40年代异常增暖。模式对气温气候态空间分布模拟较好,但在中国西部地区存在最大模拟冷偏差和不确定性。1961-1999年,中国北方增暖大于南方。多模式集合平均可以较好地模拟气温变化线性趋势的空间分布,但对南北气温变化趋势的差异模拟过小。总体说来,在中国平均气温变化趋势、气温气候态空间分布和气温变化趋势空间分布三方面,CMIP5模式都较CMIP3模式有所提高。 相似文献
17.
How well can CMIP5 simulate precipitation and its controlling processes over tropical South America?
Underestimated rainfall over Amazonia was a common problem for the Coupled Model Intercomparison Project phase 3 (CMIP3) models. We investigate whether it still exists in the CMIP phase 5 (CMIP5) models and, if so, what causes these biases? Our evaluation of historical simulations shows that some models still underestimate rainfall over Amazonia. During the dry season, both convective and large-scale precipitation is underestimated in most models. GFDL-ESM2M and IPSL notably show more pentads with no rainfall. During the wet season, large-scale precipitation is still underestimated in most models. In the dry and transition seasons, models with more realistic moisture convergence and surface evapotranspiration generally have more realistic rainfall totals. In some models, overestimates of rainfall are associated with the adjacent tropical and eastern Pacific ITCZs. However, in other models, too much surface net radiation and a resultant high Bowen ratio appears to cause underestimates of rainfall. During the transition season, low pre-seasonal latent heat, high sensible flux, and a weaker influence of cold air incursions contribute to the dry bias. About half the models can capture, but overestimate, the influences of teleconnection. Based on a simple metric, HadGEM2-ES outperforms other models especially for surface conditions and atmospheric circulation. GFDL-ESM2M has the strongest dry bias presumably due to its overestimate of moisture divergence, induced by overestimated ITCZs in adjacent oceans, and reinforced by positive feedbacks between reduced cloudiness, high Bowen ratio and suppression of rainfall during the dry season, and too weak incursions of extratropical disturbances during the transition season. 相似文献
18.
Pichelli Emanuela Coppola Erika Sobolowski Stefan Ban Nikolina Giorgi Filippo Stocchi Paolo Alias Antoinette Belu&#;i&#; Danijel Berthou Segolene Caillaud Cecile Cardoso Rita M. Chan Steven Christensen Ole B&#;ssing Dobler Andreas de Vries Hylke Goergen Klaus Kendon Elizabeth J. Keuler Klaus Lenderink Geert Lorenz Torge Mishra Aditya N. Panitz Hans-Juergen Sch&#;r Christoph Soares Pedro M. M. Truhetz Heimo Vergara-Temprado Jesus 《Climate Dynamics》2021,56(11):3581-3602
This paper presents the first multi-model ensemble of 10-year, “convection-permitting” kilometer-scale regional climate model (RCM) scenario simulations downscaled from selected CMIP5 GCM projections for historical and end of century time slices. The technique is to first downscale the CMIP5 GCM projections to an intermediate 12–15 km resolution grid using RCMs, and then use these fields to downscale further to the kilometer scale. The aim of the paper is to provide an overview of the representation of the precipitation characteristics and their projected changes over the greater Alpine domain within a Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study and the European Climate Prediction system project, tasked with investigating convective processes at the kilometer scale. An ensemble of 12 simulations performed by different research groups around Europe is analyzed. The simulations are evaluated through comparison with high resolution observations while the complementary ensemble of 12 km resolution driving models is used as a benchmark to evaluate the added value of the convection-permitting ensemble. The results show that the kilometer-scale ensemble is able to improve the representation of fine scale details of mean daily, wet-day/hour frequency, wet-day/hour intensity and heavy precipitation on a seasonal scale, reducing uncertainty over some regions. It also improves the representation of the summer diurnal cycle, showing more realistic onset and peak of convection. The kilometer-scale ensemble refines and enhances the projected patterns of change from the coarser resolution simulations and even modifies the sign of the precipitation intensity change and heavy precipitation over some regions. The convection permitting simulations also show larger changes for all indices over the diurnal cycle, also suggesting a change in the duration of convection over some regions. A larger positive change of frequency of heavy to severe precipitation is found. The results are encouraging towards the use of convection-permitting model ensembles to produce robust assessments of the local impacts of future climate change.
相似文献19.
本文对中国参加CMIP5的6个气候模式对未来北极海冰的模拟情况进行了评估。通过与1979-2005年海冰的观测值以及2050年代的多模式集合平均值对比发现,中国的气候模式对海冰范围的模拟结果与CMIP5模式的平均水平存在一定差距,具体表现为：BNU-ESM和FGOALS-s2对当前海冰范围估计很好,但对温度敏感性略偏高;FIO-ESM对当前海冰范围估计很好,但由于海冰对温度的敏感性偏低,导致其模拟的未来海冰在各种RCP情景中都融化缓慢;FGOALS-g2（BCC-CSM1-1和BCC-CSM1-1-m）对当前海冰范围的模拟存在显著偏多（显著偏少）的问题,这导致其对未来海冰融化的估计也持续偏多（偏少）。中国模式对北极海冰的模拟偏差导致它们对极区地表大气温度和湿度的模拟出现偏差,并且这些极区气象要素的偏差会进一步通过动力过程传导到对秋、冬季西风带、极涡的模拟中去。研究表明：从对海冰本身的模拟以及海冰偏差带来的气候影响这两个角度看,BNU-ESM在中国模式中水平较高,但总体上中国6个气候模式在海冰分量的模拟上仍与世界平均水平存在差距,这需要中国各模式中心的持续改进。 相似文献
20.
Uncertainties in the climate response to a doubling of atmospheric CO2 concentrations are quantified in a perturbed land surface parameter experiment. The ensemble of 108 members is constructed by systematically perturbing five poorly constrained land surface parameters of global climate model individually and in all possible combinations. The land surface parameters induce small uncertainties at global scale, substantial uncertainties at regional and seasonal scale and very large uncertainties in the tails of the distribution, the climate extremes. Climate sensitivity varies across the ensemble mainly due to the perturbation of the snow albedo parameterization, which controls the snow albedo feedback strength. The uncertainty range in the global response is small relative to perturbed physics experiments focusing on atmospheric parameters. However, land surface parameters are revealed to control the response not only of the mean but also of the variability of temperature. Major uncertainties are identified in the response of climate extremes to a doubling of CO2. During winter the response both of temperature mean and daily variability relates to fractional snow cover. Cold extremes over high latitudes warm disproportionately in ensemble members with strong snow albedo feedback and large snow cover reduction. Reduced snow cover leads to more winter warming and stronger variability decrease. As a result uncertainties in mean and variability response line up, with some members showing weak and others very strong warming of the cold tail of the distribution, depending on the snow albedo parametrization. The uncertainty across the ensemble regionally exceeds the CMIP3 multi-model range. Regarding summer hot extremes, the uncertainties are larger than for mean summer warming but smaller than in multi-model experiments. The summer precipitation response to a doubling of CO2 is not robust over many regions. Land surface parameter perturbations and natural variability alter the sign of the response even over subtropical regions. 相似文献