CMIP5全球气候模式对贵州省极端气温的预估

利用泰勒图客观地评估了贵州省在参照时段1986—2005年8个CMIP5模式试验结果对气温的模拟能力,并采用在等权重系数条件下的集合平均结果计算了贵州省21世纪不同阶段不同情景下未来极端气温指数.研究表明：8个模式的集合平均的模拟效果能较好地模拟用于计算极端气温指数的基础数据,包括日平均气温、日最低气温和日最高气温.根据集合平均的结果,不同RCPs排放情景下21世纪贵州省相对于基准期大于25℃的高温日数（SU）、最低气温的最低值（TNN）和生长季长度（GSL）均表现为增加的趋势,而小于0℃的霜冻日数（FD）则呈现减少的趋势,排放越高,增加或减少的趋势越明显.RCP8.5、RCP4.5和RCP2.6情景下2006—2099年贵州省极端气温指数相对于1986—2005年SU、TNN、FD和GSL的变化速率分别为8.06~1.30 d／（10 a）、0.49~0.07℃／（10 a）、-4.99~-0.97 d／（10 a）和3.33~0.04 d／（10 a）.     

CMIP5全球气候模式对上海极端气温和降水的情景预估

基于国际耦合模式比较计划第五阶段(Coupled Model Intercomparison Project Phase 5,以下简称CMIP5)28个模式的数值模拟结果和1981~2010年华东和上海气温和降水观测数据,评估了该28个气候模式对华东和上海气温和降水的模拟能力,并预估了RCP4.5(Representative Concentration Pathway 4.5)情景下上海2021~2030年极端气温和降水气候的变化趋势和不确定性。结果表明:与观测值相比,模式对华东和上海年平均气温的模拟大多均值偏高、方差偏低;对年总降水量的模拟大多均值偏高,但方差以华东偏高、上海偏低为主;26个模式的气温变化趋势和12个模式的降水变化趋势与观测值相同。选出8个模式的预估结果表明:与2001~2010年相比,2021~2030年上海冬天极端低温的出现日数(冷夜日数)呈减少趋势,不确定性最小;夏天暖夜日数呈增加的趋势,不确定性较小;其他极端气温事件的变化趋势则存在较大的不确定性,冷夜指标的不确定性最大。强降水发生日数和强降水的强度都呈现增加的趋势,且不确定性较小。     

CMIP5 模式对中国极端气温及其变化趋势的模拟评估

本文基于中国区域逐日气温资料和CMIP5 中30 个全球气候模式资料,计算了平均日最高气温（TXAV)、平均日最低气温（TNAV)、热浪指数（HWDI)、霜冻日数（FD)、和暖夜指数（TNF90）5 个极端气温指数,评估各模式对中国区域极端气温的气候平均场和趋势的模拟能力。研究结果表明,大部分模式能够较好地模拟出极端指数的气候平均场,其中对TNAV、TXAV 和FD 平均场模拟能力较强,大部分模式平均场与观测场的相关系数超过0.90,但对TNF90 和HWDI 的模拟能力相对较低,相关系数均低于0.70,且各模式的模拟能力存在较大的差异。对极端指数的趋势模拟来说,模式模拟的中国区域平均各极端气温指数的线性变化趋势与观测相同,但大多数模式模拟趋势的强度偏弱。相比于气候平均场,模式对极端气温指数趋势空间场模拟较差,除TNAV 有1/3 的模式平均场与观测场的相关系数超过0.60 外,模式模拟其余指数的相关系数均低于0.60。模拟极端气温气候平均场的能力最优的5 个模式为：IPSL-CM5A-MR、CMCC-CM、IPSL-CM5A-LR、MPI-ESM-MR 和MPI-ESM-P。趋势空间场模拟最好的5 个模式为：MPI-ESM-P、CANESM2、ACCESS1-3、BCC-CSM1-1 和NorESM1-M。模式对极端气温指数的时空模拟能力一致性较差,但基于气候平均场或趋势空间场的优选模式,相比于所有集合模式平均,模拟能力均有一定程度的改善。     

CMIP6模式对青藏高原极端气温指数模拟能力评估及预估

利用第六次国际耦合模式比较计划（CMIP6）28个全球气候模式模拟的历史和多SSP排放情景下的模拟结果以及国家气候中心制作的CN05.1格点化的观测数据,在评估28个全球气候模式对青藏高原极端气温相关指数模拟效果的基础上,预估了多个SSP情景下青藏高原未来极端气温指数的变化趋势。评估结果表明多模式集合平均模拟结果更稳定,且能模拟出极端气温指数的时间分布以及空间分布特征,但与观测相比,不同指数存在不同偏差。预估结果表明,相对于1995-2014年,青藏高原上日最高气温最高值（TXx）、日最低气温最低值（TNn）、暖昼指数（TX90p）未来呈上升趋势,霜冻日数（FD）、冰冻日数（ID）、冷夜指数（TN10p）呈减少趋势,其中高原极端低温比极端高温增温明显,暖昼指数在高原西南部增加明显,霜冻日数、冰冻日数、冷夜指数在高原东南部减少明显。SSP1-1.9情景下,极端气温指数在21世纪的变化幅度较小,随着辐射强迫增大,指数的变化趋势也增大。SSP1-2.6情景下,2030年前中国实现碳达峰时,青藏高原地区TXx、 TNn、 TX90p增长分别不超过1.12℃、0.84℃、 8.4%, FD、 I...     

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。     

中国未来极端气温变化的概率预估及其不确定性

本文基于第五次耦合模式比较计划的23个全球气候模式所提供的最高气温与最低气温在RCP4.5情景下的逐日格点资料,根据模式对5个极端气温指数的模拟能力,使用秩加权方法研究了中国未来极端气温变化的概率预估及其不确定性。结果表明,21世纪中期（2046—2065年）中国区域平均最高气温和平均最低气温的增加幅度相对于历史时期（1986—2005年）可能超过2.0℃（概率>66%),增加的大值区主要位于青藏高原南部。暖夜指数在中国大部分地区增加超过15%,西南和东南部沿海是增加的大值区,增幅超过20%。霜冻日数在全国范围内减少,减少的大值区位于青藏高原周围,减少日数超过了20 d。热浪指数在整个中国区域可能增加10 d以上,大值区位于西藏西南部,可达30 d。不确定性的结果表明,除热浪指数的可信度较低外,其余指数都有较高的可信度。到21世纪末期（2081—2100年),中国区域极端气温增加幅度超过前期,平均最高气温和平均最低气温很可能增加超过2.0℃（概率>90%),大值区除中国西部地区外,还扩展到了东北和青藏高原西南地区。中国大部分地区的暖夜指数增加超过15%,西南和南部沿海可能超过25%。大部分地区的霜冻日数减少20 d,青藏高原周围减少超过40 d。热浪指数在中国范围内增加20 d,青藏高原西南部增加40 d以上。除霜冻指数的信噪比略比21世纪中期大外,其余指数的信噪比与中期基本一致。     

东北地区气候变化CMIP5模式预估

利用CMIP5的多模式集合资料,从时间变化和空间分布两方面分析了不同情景下(RCP2.6、RCP4.5、RCP8.5)中国东北地区未来100年的气候变化。结果显示:3种排放情景下,21世纪东北地区气温和降水呈显著增长趋势,中期和末期增幅较明显,冬季增幅高于其他季节,RCP8.5情景下气温增暖最为显著,RCP4.5次之,RCP2.6最小,随着年代的推移,气温和降水年较差逐渐减小;空间分布显示:3种排放情景下各个时期的增温分布形式基本一致,由南向北逐渐增大,辽宁南部增温幅度最小,最显著地区位于黑龙江大兴安岭;不同情景下气温变化率的分布形势略有不同,但均呈显著增温趋势;3种排放情景下降水距平百分率均为增加趋势,呈由东向西逐渐增大的经向分布特征;不同情景下的降水变化率分布形势相似,呈南大北小特征,辽宁地区增长最为明显,黑龙江西部地区增长相对较小。     

中国干湿区变化与预估

本文采用干湿指数对1962~2011年中国干湿区范围变化进行了集中分析,并利用CMIP5（Coupled Model Intercomparison Project Phase 5）模式对其变化趋势开展了预估研究。结果表明,1962~2011年平均极端干旱区、干旱区、半干旱区、半湿润区和湿润区分别占中国陆地总面积的2.8%、11.7%、22.4%、32.6%和30.5%。期间,中国区域年干湿指数总体上呈现下降趋势,空间上表现为西部湿润化和东部干旱化的特征。显著缩小的是湿润区和极端干旱区,半湿润区、半干旱区和干旱区则显著扩大,这表明中国气候敏感区域在扩张。春季和秋季干湿指数变化趋势的空间分布与年平均的较为一致,冬季西北呈干旱化,夏季东南部地区为湿润化。相对于参考时段1986~2005年,在RCP4.5（Representative Concentration Pathway 4.5）情景下18个气候模式中位数的预估结果中,降水仅在东南南部减少,而潜在蒸散发在全区域增加,由于潜在蒸散发的增量超过了降水的增幅,中国区域将整体趋于干旱化,仅在西北地区呈湿润化特征;未来湿润区、干旱区和极端干旱区缩小,气候敏感性高的半湿润区和半干旱区仍将扩大。     

CMIP5模式对中国地区气温模拟能力评估与预估

利用第五次国际耦合模式比较计划（CMIP5）中29个气候模式的气温模拟结果,评估了各模式对中国地区年平均气温的模拟能力,对未来不同典型浓度路径（RCPs）下中国地区气温的可能变化给出了预估。结果表明：各模式能较好地模拟过去100多年中国地区增温趋势和年平均气温的空间分布,从模式间标准差来看,各模式对中国中部、南部气温模拟具有较高的一致性。利用相对均方根误差分析了各模式的模拟能力,对于多时间尺度（月、年）气温的气候平均态,有7个模式表现良好,高于中等水平,5个模式的模拟能力低于中等水平,模式集合平均值的模拟效果优于大多数单个模式。根据29个模式的评估结果,使用模拟性能相对较好的模式分析了未来不同排放情景下中国地区气温变化,21世纪前期,不同排放情景之间的预估结果差别较小,21世纪中期各情景之间的差别逐渐增大,到21世纪后期,3种排放情景的升温差别明显增大。     

CMIP5模式对西太平洋副热带高压的模拟和预估

利用国际耦合模式比较计划第五阶段（CMIP5）26个模式的模拟结果,从空间分布和振幅变化、年际周期及年代际趋势等方面,初步评估了CMIP5模式对西太平洋副热带高压（副高）的模拟能力。在此基础上,还对未来不同典型浓度路径（RCPs）情景下副高的可能变化给出了定性的预估。CMIP5模式历史试验结果显示,大多数模式对500 hPa位势高度气候平均值的模拟有明显误差,这主要是由于模式对热带印度洋和西太平洋地区海表温度（SST）的模拟普遍较观测值低,从而导致模式对副高的模拟能力有限。但大多数模式对高度场和纬向风场变化的空间形态与振幅都有较强的模拟能力。因此,通过用NCEP/NCAR再分析资料的气候平均值替代CMIP5模式气候平均值的简单方法,对CMIP5模拟结果进行了订正。经订正后的模式结果均有能力刻画副高指数的历史时间序列,且能够反映出20世纪70年代末期之后,副高面积增大、强度增强和显著西伸的变化趋势。此外,通过对副高指数的长期趋势、年际周期及标准差等的定量评估,注意到CNRM-CM5、FGOALS-g2、FIO-ESM、MIROC-ESM和MPI-ESM-P这5个模式对副高的模拟能力较强。未来气候预估试验中,副高面积和强度均增大,且显著西伸;其线性增长趋势在RCP8.5情景下最高,RCP4.5情景下次之,RCP2.6情景下最弱。有趣的是副高脊线指数在3种排放情景下都没有明显的长期变化趋势。这些结果为选取和利用CMIP5模式进行东亚地区气候变化的归因分析和未来预估提供了一定的科学依据。     

Projected Changes in Temperature and Precipitation Extremes over China as Measured by 50-yr Return Values and Periods Based on a CMIP5 Ensemble

Future changes in the 50-yr return level for temperature and precipitation extremes over mainland China are investigated based on a CMIP5 multi-model ensemble for RCP2.6, RCP4.5 and RCP8.5 scenarios. The following indices are analyzed:TXx and TNn(the annual maximum and minimum of daily maximum and minimum surface temperature), RX5 day(the annual maximum consecutive 5-day precipitation) and CDD(maximum annual number of consecutive dry days). After first validating the model performance, future changes in the 50-yr return values and return periods for these indices are investigated along with the inter-model spread. Multi-model median changes show an increase in the 50-yr return values of TXx and a decrease for TNn, more specifically, by the end of the 21 st century under RCP8.5, the present day 50-yr return period of warm events is reduced to 1.2 yr, while extreme cold events over the country are projected to essentially disappear.A general increase in RX5 day 50-yr return values is found in the future. By the end of the 21 st century under RCP8.5, events of the present RX5 day 50-yr return period are projected to reduce to 10 yr over most of China. Changes in CDD-50 show a dipole pattern over China, with a decrease in the values and longer return periods in the north, and vice versa in the south. Our study also highlights the need for further improvements in the representation of extreme events in climate models to assess the future risks and engineering design related to large-scale infrastructure in China.     

CMIP6 Evaluation and Projection of Temperature and Precipitation over China

This article evaluates the performance of 20 Coupled Model Intercomparison Project phase 6(CMIP6)models in simulating temperature and precipitation over China through comparisons with gridded observation data for the period of 1995–2014,with a focus on spatial patterns and interannual variability.The evaluations show that the CMIP6 models perform well in reproducing the climatological spatial distribution of temperature and precipitation,with better performance for temperature than for precipitation.Their interannual variability can also be reasonably captured by most models,however,poor performance is noted regarding the interannual variability of winter precipitation.Based on the comprehensive performance for the above two factors,the“highest-ranked”models are selected as an ensemble(BMME).The BMME outperforms the ensemble of all models(AMME)in simulating annual and winter temperature and precipitation,particularly for those subregions with complex terrain but it shows little improvement for summer temperature and precipitation.The AMME and BMME projections indicate annual increases for both temperature and precipitation across China by the end of the 21st century,with larger increases under the scenario of the Shared Socioeconomic Pathway 5/Representative Concentration Pathway 8.5(SSP585)than under scenario of the Shared Socioeconomic Pathway 2/Representative Concentration Pathway 4.5(SSP245).The greatest increases of annual temperature are projected for higher latitudes and higher elevations and the largest percentage-based increases in annual precipitation are projected to occur in northern and western China,especially under SSP585.However,the BMME,which generally performs better in these regions,projects lower changes in annual temperature and larger variations in annual precipitation when compared to the AMME projections.     

基于CMIP5资料的云南及周边地区未来50年气候预估

利用CRU(Climatic Research Unit)高分辨率观测数据及云南省124站资料,检验了参与IPCC AR5(政府间气候变化专门委员会第5次评估报告)的7个全球海气耦合模式(Coupled Model Intercomparison Program 5,CMIP5)及模式集合平均对云南及周边地区气温和降水的模拟性能,同时进行该区域不同温室气体排放量情景下2006~2055年的气候预估。结果表明:全球海气耦合模式对该区域气温和降水气候场空间分布、气温的线性趋势和春、夏季降水的年代际振荡特征具有一定的模拟能力,且模式集合能力优于单一模式,气温模拟优于降水模拟,但春、夏季的降水好于其他季节,使得全年的总降水好于秋、冬两季。对未来情景预估表明,研究区域未来50年气温呈现显著的线性上升趋势,降水量保持年代际振荡特征并有所增加,2020年之前我国云南及其南部区域将经历相对的干旱时期。     

The Projection of Temperature and Precipitation over China under RCP Scenarios using a CMIP5 Multi-Model Ensemble

Climate changes in 21st century China are described based on the projections of 11 climate models under Representative Concentration Pathway (RCP) scenarios. The results show that warming is expected in all regions of China under the RCP scenarios, with the northern regions showing greater warming than the southern regions. The warming tendency from 2011 to 2100 is 0.06°C/10 a for RCP2.6, 0.24°C/10 a for RCP4.5, and 0.63°C/10 a for RCP8.5. The projected time series of annual temperature have similar variation tendencies as the new greenhouse gas (GHG) emission scenario pathways, and the warming under the lower emission scenarios is less than under the higher emission scenarios. The regional averaged precipitation will increase, and the increasing precipitation in the northern regions is significant and greater than in the southern regions in China. It is noted that precipitation will tend to decrease in the southern parts of China during the period of 2011-2040, especially under RCP8.5. Compared with the changes over the globe and some previous projections, the increased warming and precipitation over China is more remarkable under the higher emission scenarios. The uncertainties in the projection are unavoidable, and further analyses are necessary to develop a better understanding of the future changes over the region.     

基于CMIP5模式集合预估21世纪中国气候带变迁趋势

本文选用耦合模式比较计划第五阶段（CMIP5）数据,结合英国东英吉利大学气候研究中心（CRU）气温和降水资料,分析了中国20世纪末期气候带分布;以此为基础,模拟并分析了RCP2.6和RCP8.5两种情景下中国21世纪中期和末期气候带的变迁趋势。结果表明：CMIP5模式集合数据能较好地模拟出中国区域气温和降水空间分布形态,CRU分析资料描述的气候带分布与柯本气候分类吻合较好。21世纪中期、末期与20世纪末期相比,RCP2.6情景下,气候类型及分布变化并不显著,RCP8.5情景下,热夏冬干温暖型分别增加了28.2%（中期）、86.9%（末期）,草原气候分别增加了24.1%（中期）、49.4%（末期）。热夏冬干冷温型到21世纪末期有明显的增加,但苔原气候和沙漠气候类型所占比重减少。     

Assessment of indices of temperature extremes simulated by multiple CMIP5 models over China

Given that climate extremes in China might have serious regional and global consequences, an increasing number of studies are examining temperature extremes in China using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. This paper investigates recent changes in temperature extremes in China using 25 state-of-the-art global climate models participating in CMIP5. Thirteen indices that represent extreme temperature events were chosen and derived by daily maximum and minimum temperatures, including those representing the intensity (absolute indices and threshold indices), duration (duration indices), and frequency (percentile indices) of extreme temperature. The overall performance of each model is summarized by a "portrait" diagram based on relative root-mean-square error, which is the RMSE relative to the median RMSE of all models, revealing the multi-model ensemble simulation to be better than individual model for most indices. Compared with observations, the models are able to capture the main features of the spatial distribution of extreme temperature during 1986-2005. Overall, the CMIP5 models are able to depict the observed indices well, and the spatial structure of the ensemble result is better for threshold indices than frequency indices. The spread amongst the CMIP5 models in different subregions for intensity indices is small and the median CMIP5 is close to observations; however, for the duration and frequency indices there can be wide disagreement regarding the change between models and observations in some regions. The model ensemble also performs well in reproducing the observational trend of temperature extremes. All absolute indices increase over China during 1961-2005.     

RCP4.5情景下中国季风区及降水变化预估

本文使用国际耦合模式比较计划第五阶段(CMIP5)中共46个全球气候模式的数值试验结果,通过对中国区域的年、夏季和冬季降水气候态的模拟能力评估,择优选取了18个气候模式用来预估RCP4.5情景下21世纪中国季风区范围、季风降水及其强度变化。结果表明,相对于1986~2004年参考时段,RCP4.5情景下多数模式和所有模式集合平均在不同时段内均模拟出中国季风区面积、季风降水及其强度的增加趋势,最明显的时段出现在2081~2099年。其中,季风区面积扩张是导致季风降水增加的主要因素。在机制上,热力与动力条件变化均有利于季风降水强度的增加以及更多的水汽进入中国东部,从而引起季风区范围的扩大。     

Change in Extreme Climate Events over China Based on CMIP5

The changes in a selection of extreme climate indices(maximum of daily maximum temperature(TXx),minimum of daily minimum temperature(TNn),annual total precipitation when the daily precipitation exceeds the 95th percentile of wet-day precipitation(very wet days,R95p),and the maximum number of consecutive days with less than 1 mm of precipitation(consecutive dry days,CDD))were projected using multi-model results from phase 5 of the Coupled Model Intercomparison Project in the early,middle,and latter parts of the 21st century under different Representative Concentration Pathway(RCP)emissions scenarios.The results suggest that TXx and TNn will increase in the future and,moreover,the increases of TNn under all RCPs are larger than those of TXx.R95p is projected to increase and CDD to decrease significantly.The changes in TXx,TNn,R95p,and CDD in eight sub-regions of China are different in the three periods of the 21st century,and the ranges of change for the four indices under the higher emissions scenario are projected to be larger than those under the lower emissions scenario.The multi-model simulations show remarkable consistency in their projection of the extreme temperature indices,but poor consistency with respect to the extreme precipitation indices.More substantial inconsistency is found in those regions where high and low temperatures are likely to happen for TXx and TNn,respectively.For extreme precipitation events(R95p),greater uncertainty appears in most of the southern regions,while for drought events(CDD)it appears in the basins of Xinjiang.The uncertainty in the future changes of the extreme climate indices increases with the increasing severity of the emissions scenario.