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。     

1.5和2℃升温阈值下中国温度和降水变化的预估

基于CMIP5耦合气候模式模拟结果对1.5和2℃升温阈值时中国温度和降水变化的分析表明,1.5℃升温阈值时,中国年平均升温由南向北加强且在青藏高原地区有所放大,季节尺度上升温的空间分布与其类似,就区域平均而言,RCP2.6、RCP4.5和RCP8.5情景下中国年平均气温分别升高1.83、1.75和1.88℃,气温的季节变幅以冬季升高最为显著;除华南和西南地区外中国大部分地区年平均降水量增多,降水的季节差异明显,以夏季降水的分布模态与年平均降水量的分布最为相似,区域平均的年降水量分别增加5.03%、2.82%和3.27%,季节尺度上以冬季降水增幅最大。2℃升温阈值时,RCP4.5和RCP8.5情景下中国年平均温度的空间分布与1.5℃升温阈值基本一致,中国年平均气温分别升高2.49和2.54℃,季节尺度上气温的变化以秋、冬季增幅最大;中国范围内年平均降水量基本表现为增多趋势,其中,西北和长江中下游部分地区表现为明显的季节差异,区域平均的年降水量分别增加6.26%和5.86%。与1.5℃升温阈值相比较,2℃升温阈值时中国年平均温度在RCP4.5和RCP8.5情景下分别升高0.74和0.76℃,降水则分别增加3.44%和2.59%,空间上温度升高以东北、西北和青藏高原最为显著,降水则在东北、华北、青藏高原和华南地区增加最为明显。      

Change in Precipitation over the Tibetan Plateau Projected by Weighted CMIP6 Models

Precipitation over the Tibetan Plateau (TP) is important to local and downstream ecosystems. Based on a weighting method considering model skill and independence, changes in the TP precipitation for near-term (2021–40), mid-term (2041–60) and long-term (2081–2100) under shared socio-economic pathways (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSSP3-7.0, SSP5-8.5) are projected with 27 models from the latest Sixth Phase of the Couple Model Intercomparison Project. The annual mean precipitation is projected to increase by 7.4%–21.6% under five SSPs with a stronger change in the northern TP by the end of the 21st century relative to the present climatology. Changes in the TP precipitation at seasonal scales show a similar moistening trend to that of annual mean precipitation, except for the drying trend in winter precipitation along the southern edges of the TP. Weighting generally suggests a slightly stronger increase in TP precipitation with reduced model uncertainty compared to equally-weighted projections. The effect of weighting exhibits spatial and seasonal differences. Seasonally, weighting leads to a prevailing enhancement of increase in spring precipitation over the TP. Spatially, the influence of weighting is more remarkable over the northwestern TP regarding the annual, summer and autumn precipitation. Differences between weighted and original MMEs can give us more confidence in a stronger increase in precipitation over the TP, especially for the season of spring and the region of the northwestern TP, which requires additional attention in decision making.     

中国东北地区气温变化的模拟评估与未来情景预估

基于RegCM4区域气候模式、CMIP5全球气候模式数据集和中国东北地区162个气象站气温观测资料,采用偏差分析和相关分析评估了RegCM4和CMIP5对东北地区气温的模拟能力,预估了RCP2.6、RCP4.5和RCP8.5排放情景下东北地区未来气温的变化。结果表明：区域模式和全球模式均能较好地再现气温时空变化特征,模式对冬季和夏季的模拟效果优于秋季和春季;在区域尺度信息上,区域模式和全球模式的模拟值均较观测值偏小,RegCM4模式的模拟结果明显优于CMIP5模式,且对模拟的冷偏差有改善。未来东北地区年及四季气温均呈升高趋势,RCP2.6情景下增温相对较小,RCP4.5次之,RCP8.5情景下增温最显著;冬季和秋季气温增幅较大,夏季气温增幅最小;与CMIP5模式相比,RegCM4模式的增温幅度更大,且年际振荡特征更加明显。空间上,区域模式和全球模式预估的近期、中期、末期增温分布格局比较一致,均呈自北向南逐渐减小的纬向分布特征,辽宁地区增温幅度最小,增幅高值区位于黑龙江省大兴安岭地区,虽然北部升温幅度较南部明显,但是升温后未来东北地区的气温分布特征仍是南部气温高于北部。     

1980～2014年中国生态脆弱区气候变化特征分析

为了全面把握20世纪80年代以来中国生态脆弱区气候变化的特征,利用基于全国2000多个站点的格点化逐月资料,对中国典型生态脆弱区1980～2014年的日平均气温、日最高和最低气温、降水、相对湿度、风速和蒸发皿蒸发量的变化特征进行了分析。结果表明:（1）中国生态脆弱区日平均气温、日最高和最低气温几乎都呈上升趋势;日平均气温增幅北方大于南方;北方生态脆弱区日平均气温、日最高和最低气温、南方生态脆弱区日最低气温的季节增幅多为春季最大,秋季或冬季最小。（2）全区平均降水变化趋势不明显;生态脆弱区降水距平百分率春季多为增长趋势,夏季多为减少趋势,秋、冬季和年北方多为增长趋势,南方多为减少趋势。（3）相对湿度以减少趋势为主,只有黄土高原南部脆弱区秋、冬季和干旱半干旱区脆弱区冬季相对湿度距平百分率的趋势为正,这几个正值区同时也是降水增长大值区。（4）风速基本为减少趋势,春季减少趋势最大。（5）全区平均蒸发皿蒸发量春、夏季和年为减少趋势,冬季为增长趋势;北方生态脆弱区蒸发皿蒸发量四季和年多呈减少趋势;南方生态脆弱区蒸发皿蒸发量春、夏季以减少趋势为主,秋、冬季和年呈增长趋势。     

青藏高原与中国其他地区气候突变时间的比较

基于1961～2006年中国地面观测气温和降水资料,对青藏高原地区以及中国其他6个地区地表气温、降水的变化趋势和突变时间进行了检测和比较。结果发现,(1)地表气温:1961～2006年青藏高原地区年和四季的地表气温都呈增加趋势。年平均地表气温在20世纪80年代中期开始变暖,但显著快速增暖的突变发生在90年代中期,该时间比东北、华北、西北和淮河地区晚,与长江中下游和华南地区接近,不同季节青藏高原地区与其他地区变暖突变时间的差别也各有不同,但所有季节快速变暖突变的时间都比东北地区晚,中国东部陆地地区年和冬季平均地表气温表现出北早南晚的经向差异;(2)降水:1961～2006年青藏高原地区年降水量没有检测到显著的变化趋势,冬春降水量显著增加,而夏季降水有微弱的减少,秋季降水显著减少。降水突变的信号明显比温度突变的信号弱,年降水量和春季降水都没有检测到突变的发生,降水突变方向(增或减)和突变时间在区域与区域之间以及不同季节之间都存在较大差异。由上可见,青藏高原气候的显著快速变化比中国东部长江以北地区有明显的滞后现象,尤其是冬春温度变化,这可能是由于青藏高原地区积雪增加导致的反照率增加和冰川融化吸热对青藏高原变暖的减弱作用所致。     

CMIP6年代际试验对中国气温预测能力的初步评估

利用参加第六次国际耦合模式比较计划（CMIP6）年代际气候预测计划（DCPP）的加拿大CanESM5模式和日本MIROC6模式的结果,评估了模式对中国近地面气温的预测能力。在年代际尺度上,两个模式年代际试验对近地面气温的回报技巧均高于历史试验的模拟能力,采用海温初始化可以提高模式对中国近地面气温的年代际预报技巧。对年代际回报试验的进一步分析表明,两个模式均能较好地预测年平均气温的变化;对季节平均气温,模式在秋季的回报技巧最高,在冬季较低。就区域平均气温而言,两个模式对中国各个地区年平均和季节平均气温都有较高的回报技巧,其中我国南方和西部地区的气温回报技巧比北方高。年平均以及春季、冬季的气温年代际回报技巧总体随提前时间的增加而降低,夏季和秋季的气温回报技巧随提前时间的增加提高。各区域内年代际预测技巧随提前时间的变化特征与全国整体基本一致。     

全球变暖1.5℃和2℃阈值时青藏高原气温的变化特征

利用国际耦合模式比较计划第5阶段（CMIP5）中的21个气候模式的RCP4.5和RCP8.5情景预估结果,分析了全球变暖1.5℃和2℃阈值时青藏高原气温年和季节的变化特征。结果表明,对应1.5℃和2℃全球变暖,青藏高原变暖幅度明显更大,就整体而言,在RCP4.5/RCP8.5情景下,高原区域平均的平均、最高、最低气温变暖分别为2.11℃/2.10℃和2.96℃/2.85℃、2.02℃/2.02℃和2.89℃/2.77℃、2.34℃/2.34℃和3.20℃/3.14℃,冬季平均气温的变暖幅度（2.19℃/2.31℃和3.13℃/3.05℃）较其他季节更大;从空间分布形势上看,年变暖呈西南高东北低的分布,而春、冬变暖呈南高北低的分布,夏、秋变暖则呈西高东低的分布。到达同一温升阈值时,RCP4.5与RCP8.5情景下高原气温的响应也存在区域差异。高原年与各季平均气温对全球变暖1.5℃与2℃的响应差异均>0.5℃,其中冬季最明显,区域平均差异可达0.94℃,局地差异超过1.1℃。     

Permafrost Thaw Accelerates in Boreal Peatlands During Late-20th Century Climate Warming

Permafrost covers 25% of the land surface in the northern hemisphere, where mean annual ground temperature is less than 0°C. A 1.4–5.8 °C warming by 2100 will likely change the sign of mean annual air and ground temperatures over much of the zones of sporadic and discontinuous permafrost in the northern hemisphere, causing widespread permafrost thaw. In this study, I examined rates of discontinuous permafrost thaw in the boreal peatlands of northern Manitoba, Canada, using a combination of tree-ring analyses to document thaw rates from 1941–1991 and direct measurements of permanent benchmarks established in 1995 and resurveyed in 2002. I used instrumented records of mean annual and seasonal air temperatures, mean winter snow depth, and duration of continuous snow pack from climate stations across northern Manitoba to analyze temporal and spatial trends in these variables and their potential impacts on thaw. Permafrost thaw in central Canadian peatlands has accelerated significantly since 1950, concurrent with a significant, late-20th-century average climate warming of +1.32 °C in this region. There were strong seasonal differences in warming in northern Manitoba, with highest rates of warming during winter (+1.39 °C to +1.66 °C) and spring (+0.56 °C to +0.78 °C) at southern climate stations where permafrost thaw was most rapid. Projecting current warming trends to year 2100, I show that trends for north-central Canada are in good agreement with general circulation models, which suggest a 4–8 °C warming at high latitudes. This magnitude of warming will begin to eliminate most of the present range of sporadic and discontinuous permafrost in central Canada by 2100.     

全球1.5℃和2.0℃升温对中国小麦产量的影响研究

采用部门间影响模式比较计划（ISI-MIP）的气候模式,确定全球升温1.5℃和2.0℃出现的时间,并结合农业技术转移决策支持系统（DSSAT）模型模拟小麦的产量,最终选取4套数据对比研究中国小麦区温度和降水变化特征以及各区域小麦产量变化趋势,综合评价了不同升温情景对中国小麦产量的影响。结果表明：(1)在全球升温1.5℃和2.0℃背景下,我国小麦生育期内温度相对于工业革命前分别升高1.17℃和1.81℃。两种升温情景下我国春麦区升温幅度大于冬麦区升温幅度。春麦区中新疆春麦区升温幅度最大,西北春麦区升温幅度最小;冬麦区中温度变化最大和最小的麦区分别为西南冬麦区和黄淮冬麦区。(2)在全球升温1.5℃和2.0℃情景下,我国小麦生育期内降水相对于历史时段(1986—2005年)分别增加9.1%和11.3%。从各麦区来看,两种升温情景下春麦区降水增加幅度略大于冬麦区的增加幅度。所有麦区中只有新疆春麦区降水低于历史时段降水。春麦区降水增加幅度最大的麦区为北部春麦区。冬麦区中降水增加较大的麦区为北部冬麦区和黄淮冬麦区,降水增加较小的麦区为华南冬麦区和西南冬麦区。(3)两种升温情景下,我国小麦单产相对于历史时段(1986—2005年)平均减产分别为5.2%和4.6%,两种升温情景对中国小麦产量并没有显著的差异。在全球升温大背景下我国春小麦主要呈现增产趋势,冬小麦主要呈现减产趋势。减产幅度较大的麦区为华南冬麦区和青藏春麦区,增产幅度最大的麦区为西北春麦区。从各麦区产量减产面积比例上看,我国各麦区减产面积所占比例趋势为从北向南由多变少再变多,其中华南冬麦区减产面积所占比例最大,北部冬麦区最小。     

RCP情景下内蒙古黄河流域径流预估及其对水资源的影响

根据内蒙古黄河流域内72个国家气象站观测的1961—2005年和区域气候模式CCLM模拟的1961—2100年的气温和降水数据,采用BP人工神经网络模型,预估分析3种RCP情景下头道拐水文站2011—2100年流量变化,评估未来气候变化对流域水资源的可能影响。结果表明:①2011—2100年内蒙古黄河流域气温升高,降水变化不明显,年平均流量呈减少趋势,RCP2.6、RCP4.5和RCP8.5情景分别减少3.6%、2.7%和23.4%。②未来春季流量以增加为主;夏季在不同情景的变化趋势不一致;秋季在21世纪50年代前以增加为主,之后以减少为主;冬季则以减少为主。③未来流域可利用水资源呈减少趋势,尤其夏季水资源的供需矛盾加剧,以及径流季节分配发生变化,可能产生更大的春季径流。     

CMIP5多模式集合对江苏省气候变化模拟评估及情景预估

利用中国气象局所属的2 400余个台站观测资料制作的分辨率为0.25°×0.25°数据集中的气温、降水量资料评估了CMIP5中17个模式对于1961—2004年江苏省气温和降水量空间分布特征的模拟能力,筛选出了5个对江苏省气候特征模拟较好的模式。之后基于5个优选模式集合平均的结果预估了3种典型浓度路径(Representative Concentration Pathways,RCPs)下江苏省2006—2100年的气温和降水量变化趋势。结果表明:(1)全球耦合气候模式对江苏省的气温和降水量空间分布特征具有一定的模拟能力,并且模式集合平均的气温和降水量与观测资料的空间相关系数分别为0.85和0.93;(2)在低浓度路径(RCP2.6)、中浓度路径(RCP4.5)和高浓度路径(RCP8.5)3种温室气体排放情景下,江苏省2006—2100年的地表温度均呈现明显的增温趋势,并且苏北的增温幅度要高于苏南;(3)3种温室气体排放情景下,江苏省未来百年降水量均呈现出北方增多南方减少的趋势;(4)未来百年江苏省降水量随气温变化的趋势并不稳定,RCP2.6和RCP4.5情景下降水量随气温的升高而增加,而RCP8.5情景下降水量随气温的增加而减少。     

Asymmetry of surface climate change under RCP2.6 projections from the CMIP5 models

The multi-model ensemble (MME) of 20 models from the Coupled Model Intercomparison Project Phase Five (CMIP5) was used to analyze surface climate change in the 21st century under the representative concentration pathway RCP2.6, to reflect emission mitigation efforts. The maximum increase of surface air temperature (SAT) is 1.86°C relative to the pre-industrial level, achieving the target to limit the global warming to 2°C. Associated with the “increase-peak-decline” greenhouse gases (GHGs) concentration pathway of RCP2.6, the global mean SAT of MME shows opposite trends during two time periods: warming during 2006–55 and cooling during 2056–2100. Our results indicate that spatial distribution of the linear trend of SAT during the warming period exhibited asymmetrical features compared to that during the cooling period. The warming during 2006–55 is distributed globally, while the cooling during 2056–2100 mainly occurred in the NH, the South Indian Ocean, and the tropical South Atlantic Ocean. Different dominant roles of heat flux in the two time periods partly explain the asymmetry. During the warming period, the latent heat flux and shortwave radiation both play major roles in heating the surface air. During the cooling period, the increase of net longwave radiation partly explains the cooling in the tropics and subtropics, which is associated with the decrease of total cloud amount. The decrease of the shortwave radiation accounts for the prominent cooling in the high latitudes of the NH. The surface sensible heat flux, latent heat flux, and shortwave radiation collectively contribute to the especial warming phenomenon in the high-latitude of the SH during the cooling period.     

Time of emergence of anthropogenic warming signals in the Northeast Asia assessed from multi-regional climate models

Time of Emergence (ToE) is the time at which the signal of climate change emerges from the background noise of natural climate variability, and can provide useful information for climate change impacts and adaptations. This study examines future ToEs for daily maximum and minimum temperatures over the Northeast Asia using five Regional Climate Models (RCMs) simulations driven by single Global Climate Model (GCM) under two Representative Concentration Pathways (RCP) emission scenarios. Noise is defined based on the interannual variability during the present-day period (1981-2010) and warming signals in the future years (2021-2100) are compared against the noise in order to identify ToEs. Results show that ToEs of annual mean temperatures occur between 2030s and 2040s in RCMs, which essentially follow those of the driving GCM. This represents the dominant influence of GCM boundary forcing on RCM results in this region. ToEs of seasonal temperatures exhibit larger ranges from 2030s to 2090s. The seasonality of ToE is found to be determined majorly by noise amplitudes. The earliest ToE appears in autumn when the noise is smallest while the latest ToE occurs in winter when the noise is largest. The RCP4.5 scenario exhibits later emergence years than the RCP8.5 scenario by 5-35 years. The significant delay in ToEs by taking the lower emission scenario provides an important implication for climate change mitigation. Daily minimum temperatures tend to have earlier emergence than daily maximum temperature but with low confidence. It is also found that noise thresholds can strongly affect ToE years, i.e. larger noise threshold induces later emergence, indicating the importance of noise estimation in the ToE assessment.     

“一带一路”区域未来气候变化预估

利用耦合模式比较计划第5阶段(CMIP5)提供的18个全球气候模式的模拟结果,预估了3种典型浓度路径(RCP2.6、RCP4.5、RCP8.5)下“一带一路”地区平均气候和极端气候的未来变化趋势。结果表明:在温室气体持续排放情景下,“一带一路”地区年平均气温在未来将会持续上升,升温幅度随温室气体浓度的增加而加大。在高温室气体排放情景(RCP8.5)下,到21世纪末期,平均气温将普遍升高5℃以上,其中北亚地区升幅最大,南亚和东南亚地区升幅最小。对于降水的变化,预估该区域大部分地区的年降水量将增加,其中西亚和北亚增加最为明显,而且在21世纪中期,RCP2.6情景下的增幅要比RCP4.5和RCP8.5情景下的偏大,而在21世纪后期,RCP8.5情景下降水的增幅比RCP2.6和RCP4.5情景下的偏大。未来极端温度也将呈升高的趋势,增温幅度高纬度地区大于低纬度地区、高排放情景大于低排放情景。而且在高纬度区域,极端低温的增暖幅度要大于极端高温的增幅。连续干旱日数在北亚和东亚总体呈现减少趋势,而在其他地区则呈增加趋势。极端强降水在“一带一路”区域总体上将增强,增强最明显的地区位于南亚、东南亚和东亚。     

Climate Change of 4°C Global Warming above Pre-industrial Levels

Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4°C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4°C global warming will occur is 2084. Based on the median results of models that project a 4°C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-to-noise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5°C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the inter-model consistency is better for temperature than for precipitation.     

基于国际大气化学—气候模式比较计划模式数据评估未来气候变化对中国东部气溶胶浓度的影响

气候变化引起的地面气溶胶浓度变化与区域空气质量密切相关。本文利用“国际大气化学—气候模式比较计划”（Atmospheric Chemistry and Climate Model Intercomparison Project, ACCMIP）中4个模式的试验数据分析了RCP8.5情景下2000~2100年气候变化对中国气溶胶浓度的影响。结果显示,在人为气溶胶排放固定在2000年、仅考虑气候变化的影响时,2000~2100年气候变化导致中国北部地区（31°N~45°N, 105°E~122°E）硫酸盐、有机碳和黑碳气溶胶分别增加28%、21%和9%,硝酸盐气溶胶在中国东部地区减少30%。气候变化对细颗粒物（PM_2.5）浓度的影响有显著的季节变化特征,冬季PM_2.5浓度在中国东部减少15%,这主要是由硝酸盐气溶胶在冬季的显著减少造成的;夏季PM_2.5浓度在中国北部地区增加16%,而长江以南地区减少为9%,这可能与模式模拟的未来东亚夏季风环流的增强有关。     

Climate Change of 4℃ Global Warming above Pre-industrial Levels

Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4?C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4?C global warming will occur is 2084.Based on the median results of models that project a 4?C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-tonoise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5?C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the intermodel consistency is better for temperature than for precipitation.     

青藏高原未来气候变化预估:CMIP5模式结果

本文使用国际耦合模式比较计划第5阶段(CMIP5)中对青藏高原气候模拟较优的气候模式, 在RCP4.5中等偏低辐射强迫情景下对青藏高原未来气候变化进行了预估研究。结果表明, 青藏高原年均地表气温在2006~2100年的线性趋势平均为0.26℃/10a, 增暖幅度与海拔高度大体成正比;相比于1986~2005年参考时段, 2090年代平均升温2.7℃, 21世纪末期增温幅度明显高于早期和中期;在早、中和末期, 年均增温分别为0.8~1.3℃、1.6~2.5℃和2.1~3.1℃;各季节也均为变暖趋势, 其中冬季增温最大。对于年均降水来说, 未来百年将小幅增加, 集合平均趋势为1.15%/10a, 2090年代较参考时段增加10.4%;在早、中和末期的变化范围分别为-1.8%至15.2%、-0.9%至17.8%和1.4%至21.3%;季节降水也呈增加趋势, 夏季增幅明显高于其余三个季节且在21世纪末期较大, 青藏高原未来年均降水增加主要来自于夏季。需要指出的是, 上述预估结果在气候模式间存在着一定的差异, 未来气候变化的不确定性范围较大, 地表气温的可信度相对较高, 而降水的则偏低。     

概率密度分布法在“一带一路”地区极端月气温评估和预估中的应用

“一带一路”地区人口众多,气候类型复杂,亟待加强区域气候变化风险的认识。文中将该区分成10个区域,基于第五次耦合模式比较计划（CMIP5）中的31个全球模式模拟结果,应用概率密度分布（PDF）方法评估历史阶段（1986—2005年）各模式模拟暖月和冷月气温的能力,挑选并建立较优模式集合,用以预估21世纪中叶（2041—2060年）和21世纪末（2081—2100年）的极端月气温。结果表明,模式对观测中冷月气温距平PDF的模拟水平整体较暖月高。与多模式平均以及中位值相比,较优模式集合方法更适于极端暖/冷月气温的评估。在中等排放RCP4.5情景下,与低纬度地区相比,较优模式模拟中高纬地区未来极端暖/冷月气温的增温幅度的不确定性范围较大。21世纪中叶和21世纪末较优模式模拟的极端暖月气温在地中海增幅整体最大,东南亚增幅整体最小。对较优模式集合预估的极端冷月气温而言,无论是21世纪中叶还是世纪末,北欧增幅整体最大,东南亚增幅整体最小。