青藏高原气温和降水近期、中期与长期变化的预估及其不确定性来源

采用第五次耦合模式比较计划（Coupled Model Intercomparison Project Phase 5,CMIP5）高分辨率全球统计降尺度预估数据集,针对近期（2020—2039年）、中期（2040—2059年）和长期（2080—2099年）,以及全球1.5℃和2℃温升阈值,预估了青藏高原地区平均气温和降水、极端气温和极端降水的变化,定量估算了预估结果的不确定性来源。结果表明：（1）在RCP4.5和RCP8.5情景下,21世纪青藏高原地区平均气温和降水、极端气温和极端降水强度均显著增加,最长连续干旱天气减少。高原气候变化幅度超全球平均,至21世纪末,模式集合预估的气候变化幅度介于全球平均的1.5~3倍。（2）青藏高原地区受0.5℃额外增温的显著影响,年均气温、极端高温和极端低温均显著升高,平均及极端强降水均显著增加。（3）排放情景的选择对近期气候预估影响小,但对长期影响大。在相同排放情景下,内部变率主导了近期高原平均气温预估的不确定性,但至长期其贡献降至10%以下。模式和内部变率的不确定性对降水预估均有贡献,且都随时间减小,最大不确定性中心位于西部和北部边缘,噪声与信号比大于6。     

CMIP5多模式预估的1.5℃升温背景下中国气温和降水变化

本文使用国际耦合模式比较计划第五阶段（CMIP5）中39个全球气候模式的试验数据,预估了相对于工业革命前期全球1.5℃升温背景下中国气温和降水变化。根据多模式中位数预估结果,在不同典型浓度路径（RCPs）情景下,相对于工业革命前期全球1.5℃升温分别发生在2034年（RCP2.6）、2033年（RCP4.5）和2029年（RCP8.5）。全球升温1.5℃时,中国年和季节气温平均上升1.8℃和1.6～2.1℃,其中冬季最强。增温总体上由南向北加强,青藏高原为高值中心。年和各季节增温均超过其自然内部变率,区域平均的信噪比分别为3.4和1.6～2.7。年和季节降水整体上在中国北方增加、华南减少;区域平均的年降水增加1.4%,季节降水增加0.1%～5.1%,冬季增幅最大。年和季节降水变化要远小于其自然内部变率,区域平均的信噪比仅为0.1和0.01～0.2。总体上,模式对气温预估的不确定性较小,对降水的偏大,其中对季节尺度预估的不确定性要高于年平均结果。     

Impacts of internal climate variability on meteorological drought changes in China

干旱受气候内部变率和外部强迫共同影响。本文利用地球系统模式CESM对历史时期和RCP8.5下的40个集合模拟的降水资料,并结合实际观测,研究了上述两因子对气象学干旱–标准化降水指数变化的贡献。通过对干旱频率、强度、持续时间、及最长持续时间的变化分析发现:在历史时期,气候内部变率对干旱变化起主要影响,而在未来(RCP8.5)情景下,外部强迫变得更为重要。本文建议,在利用模式模拟结果研究干旱变化时应考虑气候内部变率的影响。     

CMIP5多模式对阿留申低压气候特征的模拟检验与预估

利用观测的海温资料和海平面气压资料,检验了CMIP5(Coupled Model Intercomparison Project 5,CMIP5)多模式对阿留申低压(Aleutian Low,AL)特征指数的时空分布和变化的模拟能力;从AL周期及变化趋势等方面,分析了CMIP5模式预估的未来AL的变化特征。结果表明,CMIP5模式及其集合平均能够很好地模拟AL的环流结构,对AL的气候态有着较强的模拟能力,尤其是模式对于东太平洋海表温度的模拟能力直接影响其对于AL的模拟效果。模式的集合平均对变率强度的模拟偏强,且对于变率的模拟效果逊于对气候态的模拟。22个模式中的16个模式能模拟出AL强度指数的年代际变化周期,对年代际周期有着较好的刻画能力。Historical试验下对于AL的变化趋势存在着较大的不确定性,而相对于两种不同排放情景,随着排放的增加,AL更加偏北,强度增强,年际、年代际周期变得更加显著。在两种排放情景下模式的集合平均以及多数模式模拟出AL有着向北和增强的趋势。     

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 analysis of the interannual variability of the Pacific SST and its association with the Asian-Pacific oscillation

基于27个CMIP5模式的模拟数据,评估了模式对太平洋海表温度年际变率及其与亚洲-太平洋涛动关系的模拟能力,并预估了其在RCP4.5和RCP8.5情景下的未来变化。评估结果表明,大多数模式和多模式集合能很好的再现观测中北太平洋和热带东太平洋海表温度的强年际变率,其与亚洲-太平洋涛动的同位相和反位相变化关系也能成功模拟出。多模式集合预估显示,与1950-99年相比,2050-99年期间北太平洋和热带东太平洋海表温度的年际变率在RCP4.5和RCP8.5情景下将减弱。大多数模式的预估结果与此相一致。此外,多模式集合预估还表明,当今亚洲-太平洋涛动与北太平洋和热带东太平洋海表温度的年际关系在RCP4.5和RCP8.5情景下仍存在,不过单模式的预估结果具有明显差异。     

基于CMIP6模式的黄河流域宁夏段未来气温变化预估研究

为预估黄河流域宁夏段不同地区未来气候特征及其变化趋势，利用宁夏区内19个国家气象站观测资料和CMIP6(Coupled Model Intercomparison Project 6)模式数据，在检验CMIP6模式对宁夏气温模拟能力的基础上，对不同情景下宁夏引黄灌区、中部干旱带和南部山区未来气温变化进行预估。结果表明：(1)CMIP6大部分模式对黄河流域宁夏段年平均气温模拟能力较好，空间相关系数为0.603～0.930，时间相关系数为0.381～0.782，多模式集合优于单个模式模拟效果。(2)在SSP1-2.6、SSP2-4.5、SSP3-7.0、SSP5-8.5 4种情景下，预计2021—2099年黄河流域宁夏段年平均气温均呈明显增温趋势，增温速率为0.09～0.68℃·(10 a)^-1。不同情景下增温速率差异明显，SSP1-2.6情景下呈减小趋势，SSP2-4.5情景下先增后减，SSP3-7.0情景下呈“增大、减小、增大”特征，SSP5-8.5情景下呈增大趋势。(3)预计4种情景下21世纪30年代引黄灌区、中部干旱带和南部山区年平均气温分别达10.91～11...     

基于IPCC A1B情景的中国未来气候变化预估:多模式集合结果及其不确定性

利用耦合模式比较计划(CMIP3)提供的20世纪气候模拟试验(20C3M)及A1B情景预估试验,讨论了全球增暖情景下21世纪中期中国气候的可能变化。结果表明,A1B情景下,中国夏季降水变化在-0.1～1.1mm/d,冬季降水变化在-0.2～0.2mm/d。模式对降水变化的预估存在较大不确定性。无论冬夏,预估的全国表面气温都将升高,升温幅度在1.2～2.8℃;随纬度升高,增暖幅度相应增大。模式对表面气温变化的预估能力强于对降水变化的预估能力。在A1B情景下,东亚夏季风增强,而冬季风则略为减弱,东亚夏季风雨带到达最北后南撤的时间较之20C3M滞后约一个月。     

CMIP5气候模式对云南气候变化模拟评估及未来情景预估

基于8个气候模式和多模式集合数据(21个气候模式简单集合)和观测数据,评估了其在气候基准期内对云南气温、降水的模拟能力,在评估基础上应用多模式集合数据,预估了未来不同排放情景下云南气温、降水的空间变化情况。结果表明:①多模式集合和部分模式能较好的模拟出基准期内气温、降水的年际变化趋势;在空间分布特征上,气候模式(包括多模式集合)对降水的模拟偏差较差,对气温的模拟相对较好;但在月平均气温和月降水的年内分布模拟上,多模式集合数据的模拟效果明显优于8个气候模式数据;②预估结果表明,在未来3种排放情景下云南地区降水呈西增东减的空间部分特征,纵向岭谷地区降水增加幅度为1%～3%,而气温在3种排放情景下则表现为一致的增加,降水和气温均在RCP8.5情景下增幅最大。     

CMIP5全球气候模式对青藏高原地区气候模拟能力评估

青藏高原是气候变化的敏感和脆弱区,全球气候模式对于这一地区气候态的模拟能力如何尚不清楚。为此,本文使用国际耦合模式比较计划第五阶段（CMIP5）的历史模拟试验数据,评估了44 个全球气候模式对1986~2005 年青藏高原地区地表气温和降水两个基本气象要素的模拟能力。结果表明,CMIP5 模式低估了青藏高原地区年和季节平均地表气温,年均平均偏低2.3℃,秋季和冬季冷偏差相对更大;模式可较好地模拟年和季节平均地表气温分布型,但模拟的空间变率总体偏大;地形效应校正能够有效订正地表气温结果。CMIP5 模式对青藏高原地区降水模拟能力较差。尽管它们能够模拟出年均降水自西北向东南渐增的分布型,但模拟的年和季节降水量普遍偏大,年均降水平均偏多1.3 mm d-1,这主要是源于春季和夏季降水被高估。同时,模式模拟的年和季节降水空间变率也普遍大于观测值,尤其表现在春季和冬季。相比较而言,44 个模式集合平均性能总体上要优于大多数单个模式;等权重集合平均方案要优于中位数平均;对择优挑选的模式进行集合平均能够提高总体的模拟能力,其中对降水模拟的改进更为显著。     

CMIP5模式对AMO与PDO模拟评估及未来预估

利用1880—2009年海表温度(Sea Surface Temperature, SST)观测资料以及耦合模式比较计划第五阶段(Coupled Model Intercomparison Project phase 5,CMIP5)中4种情景(piControl、historical、RCP2.6、RCP4.5)下的模拟资料,通过资料对比,评估了CMIP5模式对两个最为重要年代际尺度模态——北大西洋年代际振荡(Atlantic Multidecadal Oscillation, AMO)和太平洋年代际振荡(Pacific Decadal Oscillation, PDO)的模拟性能,并分析了在不同增暖情景下,这两个海洋年代际模态的变化特征。结果表明:在historical和piControl情景下,多模式集合可以再现北太平洋、东太平洋和北大西洋海表温度的年代际变化中心,但模拟的AMO和PDO模态的振幅都偏弱,特别是PDO模态在东太平洋强度的再现能力较弱。与观测资料相比,在historical情景下对AMO和PDO时空特征模拟较好的模式有:CESM1-CAM5、FGOALS-g2、GISS-E2-H-CC、MIROC5和NorESM1-ME,多模式集合则有更好的模拟效果。在不同增暖情景下,AMO与PDO的空间特征基本一致且振幅差随增暖变化不明显,但是伴随全球增暖加强,两模态都呈现方差贡献减小的特征,尤其AMO模态。     

Future evolution of the Sahel precipitation zonal contrast in CESM1

The main focus of this study is the zonal contrast of the Sahel precipitation shown in the CMIP5 climate projections: precipitation decreases over the western Sahel (i.e., Senegal and western Mali) and increases over the central Sahel (i.e., eastern Mali, Burkina Faso and Niger). This zonal contrast in future precipitation change is a robust model response to climate change but suffers from a lack of an explanation. To this aim, we study the impact of current and future climate change on Sahel precipitation by using the Large Ensemble of the Community Earth System Model version 1 (CESM1). In CESM1, global warming leads to a strengthening of the zonal contrast, as shown by the difference between the 2060–2099 period (under a high emission scenario) and the 1960–1999 period (under the historical forcing). The zonal contrast is associated with dynamic shifts in the atmospheric circulation. We show that, in absence of a forced response, that is, when only accounting for internal climate variability, the zonal contrast is associated with the Pacific and the tropical Atlantic oceans variability. However, future patterns in sea surface temperature (SST) anomalies are not necessary to explaining the projected strengthening of the zonal contrast. The mechanisms underlying the simulated changes are elucidated by analysing a set of CMIP5 idealised simulations. We show the increase in precipitation over the central Sahel to be mostly associated with the surface warming over northern Africa, which favour the displacement of the monsoon cell northwards. Over the western Sahel, the decrease in Sahel precipitation is associated with a southward shift of the monsoon circulation, and is mostly due to the warming of the SST. These two mechanisms allow explaining the zonal contrast in precipitation change.

     

On the generation of climate model ensembles

Climate model ensembles are used to estimate uncertainty in future projections, typically by interpreting the ensemble distribution for a particular variable probabilistically. There are, however, different ways to produce climate model ensembles that yield different results, and therefore different probabilities for a future change in a variable. Perhaps equally importantly, there are different approaches to interpreting the ensemble distribution that lead to different conclusions. Here we use a reduced-resolution climate system model to compare three common ways to generate ensembles: initial conditions perturbation, physical parameter perturbation, and structural changes. Despite these three approaches conceptually representing very different categories of uncertainty within a modelling system, when comparing simulations to observations of surface air temperature they can be very difficult to separate. Using the twentieth century CMIP5 ensemble for comparison, we show that initial conditions ensembles, in theory representing internal variability, significantly underestimate observed variance. Structural ensembles, perhaps less surprisingly, exhibit over-dispersion in simulated variance. We argue that future climate model ensembles may need to include parameter or structural perturbation members in addition to perturbed initial conditions members to ensure that they sample uncertainty due to internal variability more completely. We note that where ensembles are over- or under-dispersive, such as for the CMIP5 ensemble, estimates of uncertainty need to be treated with care.     

Analysis of uncertainties in future climate projections for South America: comparison of WCRP-CMIP3 and WCRP-CMIP5 models

This paper identifies two sources of uncertainties in model projections of temperature and precipitation: internal and inter-model variability. Eight models of WCRP-CMIP3 and WCRP-CMIP5 were compared to identify improvements in the reliability of projections from new generation models. While no significant differences are observed between both datasets, some improvements were found in the new generation models. For example, in summer CMIP5 inter-model variability of temperature was lower over northeastern Argentina, Paraguay and northern Brazil, in the last decades of the 21st century. Reliability of temperature projections from both sets of models is high, with signal to noise ratio greater than 1 over most of the study region. Although no major differences were observed in both precipitation datasets, CMIP5 inter-model variability was lower over northern and eastern Brazil in summer (especially at the end of the 21st century). Reliability of precipitation projections was low in both datasets. However, the signal to noise ratio in new generation models was close to 1, and even greater than 1 over eastern Argentina, Uruguay and southern Brazil in some seasons.     

Uncertainties in historical changes and future projections of drought. Part II: model-simulated historical and future drought changes

While most models project large increases in agricultural drought frequency and severity in the 21st century, significant uncertainties exist in these projections. Here, we compare the model-simulated changes with observation-based estimates since 1900 and examine model projections from both the Coupled Model Inter-comparison Project Phase 3 (CMIP3) and Phase 5 (CMIP5). We use the self-calibrated Palmer Drought Severity Index with the Penman-Monteith potential evapotranspiration (PET) (sc_PDSI_pm) as a measure of agricultural drought. Results show that estimated long-term changes in global and hemispheric drought areas from 1900 to 2014 are consistent with the CMIP3 and CMIP5 model-simulated response to historical greenhouse gases and other external forcing, with the short-term variations within the model spread of internal variability, despite that regional changes are still dominated by internal variability. Both the CMIP3 and CMIP5 models project continued increases (by 50–200 % in a relative sense) in the 21st century in global agricultural drought frequency and area even under low-moderate emissions scenarios, resulting from a decrease in the mean and flattening of the probability distribution functions (PDFs) of the sc_PDSI_pm. This flattening is especially pronounced over the Northern Hemisphere land, leading to increased drought frequency even over areas with increasing sc_PDSI_pm. Large differences exist in the CMIP3 and CMIP5 model-projected precipitation and drought changes over the Sahel and northern Australia due to uncertainties in simulating the African Inter-tropical convergence zone (ITCZ) and the subsidence zone over northern Australia, while the wetting trend over East Africa reflects a robust response of the Indian Ocean ITCZ seen in both the CMIP3 and CMIP5 models. While warming-induced PET increases over all latitudes and precipitation decreases over subtropical land are responsible for mean sc_PDSI_pm decreases, the exact cause of its PDF flattening needs further investigation.     

Consistency of simulated and observed regional changes in temperature, sea level pressure and precipitation

There is increasing pressure from stakeholders for highly localised climate change projections. A comprehensive assessment of climate model performance at the grid box scale in simulating recent change, however, is not available at present. Therefore, we compare observed changes in near-surface temperature, sea level pressure (SLP) and precipitation with simulations available from the Coupled Model Intercomparison Projects 3 and 5 (CMIP3 and CMIP5). In both multi-model datasets we find coherent areas of inconsistency between observed and simulated local trends per degree global warming in both temperature and SLP in the majority of models. Localised projections should thus take into account the possibility of regional biases shared across models. In contrast, simulated changes in precipitation are not significantly different from observations due to low signal-to-noise ratio of local precipitation changes. Therefore, recent regional rainfall change is likely not providing useful constraints for future projections as of yet. Comparing the two most recent sets of internationally coordinated climate model experiments, we find no indication of improvement in the models’ ability to reproduce local trends in temperature, SLP and precipitation.     

Present-day and future Amazonian precipitation in global climate models: CMIP5 versus CMIP3

The present study aims at evaluating and comparing precipitation over the Amazon in two sets of historical and future climate simulations based on phase 3 (CMIP3) and 5 (CMIP5) of the Coupled Model Intercomparison Project. Thirteen models have been selected in order to discuss (1) potential improvements in the simulation of present-day climate and (2) the potential reduction in the uncertainties of the model response to increasing concentrations of greenhouse gases. While several features of present-day precipitation—including annual cycle, spatial distribution and co variability with tropical sea surface temperature (SST)—have been improved, strong uncertainties remain in the climate projections. A closer comparison between CMIP5 and CMIP3 highlights a weaker consensus on increased precipitation during the wet season, but a stronger consensus on a drying and lengthening of the dry season. The latter response is related to a northward shift of the boreal summer intertropical convergence zone in CMIP5, in line with a more asymmetric warming between the northern and southern hemispheres. The large uncertainties that persist in the rainfall response arise from contrasted anomalies in both moisture convergence and evapotranspiration. They might be related to the diverse response of tropical SST and ENSO (El Niño Southern Oscillation) variability, as well as to spurious behaviours among the models that show the most extreme response. Model improvements of present-day climate do not necessarily translate into more reliable projections and further efforts are needed for constraining the pattern of the SST response and the soil moisture feedback in global climate scenarios.     

Consistency of observed near surface temperature trends with climate change projections over the Mediterranean region

We examine the possibility that anthropogenic forcing (Greenhouse gases and Sulfate aerosols, GS) is a plausible explanation for the observed near-surface temperature trends over the Mediterranean area. For this purpose, we compare annual and seasonal observed trends in near-surface temperature over the period from 1980 to 2009 with the response to GS forcing estimated from 23 models derived from CMIP3 database. We find that there is less than a 5% chance that natural (internal) variability is responsible for the observed annual and seasonal area-mean warming except in winter. Using additionally two pattern similarity statistics, pattern correlation and regression, we find that the large-scale component (spatial-mean) of the GS signal is detectable (at 2.5% level) in all seasons except in winter. In contrast, we fail to detect the small-scale component (spatial anomalies about the mean) of GS signal in observed trend patterns. Further, we find that the recent trends are significantly (at 2.5% level) consistent with all the 23 GS patterns, except in summer and spring, when 9 and 5 models respectively underestimate the observed warming. Thus, we conclude that GS forcing is a plausible explanation for the observed warming in the Mediterranean region. Consistency of observed trends with climate change projections indicates that present trends may be understood of what will come more so in the future, allowing for a better communication of the societal challenges to meet in the future.     

通用地球系统模式对亚洲夏季风降水的模拟能力评估

通过与观测/再分析资料和参加第五次耦合模式比较计划(CMIP5)的模式模拟结果进行对比,评估了通用地球系统模式(CESM,1.0.3版本)对亚洲夏季风降水的模拟能力。结果表明:CESM能够合理地模拟出亚洲夏季风降水的气候平均态,但与其他CMIP5模式模拟结果类似,对中国东南地区降水模拟偏少,而对中国西部高原地区降水模拟偏多;CESM可以再现亚洲季风区降水冬弱夏强、雨带北进南退的季节变化特征,其模拟偏差具有区域性和季节性差异;从EOF分析结果来看,CESM能够模拟出亚洲夏季风降水的时空变化特征,且能较好地抓住亚洲夏季风降水与厄尔尼诺-南方涛动(El Ni?o-Southern Oscillation,简称ENSO)的相关关系。总的说来,CESM对亚洲夏季风降水的模拟是合理的,模拟水平与4个最好的CMIP5模式相当。