Changes in Mean and Extreme Temperature and Precipitation over the Arid Region of Northwestern China:Observation and Projection

This paper reports a comprehensive study on the observed and projected spatiotemporal changes in mean and extreme climate over the arid region of northwestern China, based on gridded observation data and CMIP5 simulations under the RCP4.5 and RCP8.5 scenarios. The observational results reveal an increase in annual mean temperature since 1961, largely attributable to the increase in minimum temperature. The annual mean precipitation also exhibits a significant increasing tendency. The precipitation amount in the most recent decade was greater than in any preceding decade since 1961. Seasonally,the greatest increase in temperature and precipitation appears in winter and in summer, respectively. Widespread significant changes in temperature-related extremes are consistent with warming, with decreases in cold extremes and increases in warm extremes. The warming of the coldest night is greater than that of the warmest day, and changes in cold and warm nights are more evident than for cold and warm days. Extreme precipitation and wet days exhibit an increasing trend, and the maximum number of consecutive dry days shows a tendency toward shorter duration. Multi-model ensemble mean projections indicate an overall continual increase in temperature and precipitation during the 21 st century. Decreases in cold extremes, increases in warm extremes, intensification of extreme precipitation, increases in wet days, and decreases in consecutive dry days, are expected under both emissions scenarios, with larger changes corresponding to stronger radiative forcing.     

Changes in temperature and precipitation extremes in the CMIP5 ensemble

Twenty-year temperature and precipitation extremes and their projected future changes are evaluated in an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), updating a similar study based on the CMIP3 ensemble. The projected changes are documented for three radiative forcing scenarios. The performance of the CMIP5 models in simulating 20-year temperature and precipitation extremes is comparable to that of the CMIP3 ensemble. The models simulate late 20th century warm extremes reasonably well, compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes. Simulated late 20th century precipitation extremes are plausible in the extratropics but uncertainty in extreme precipitation in the tropics and subtropics remains very large, both in the models and the observationally-constrained datasets. Consistent with CMIP3 results, CMIP5 cold extremes generally warm faster than warm extremes, mainly in regions where snow and sea-ice retreat with global warming. There are tropical and subtropical regions where warming rates of warm extremes exceed those of cold extremes. Relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation. The corresponding waiting times for late 20th century extreme precipitation events are reduced almost everywhere, except for a few subtropical regions. The CMIP5 planetary sensitivity in extreme precipitation is about 6 %/°C, with generally lower values over extratropical land.     

Global changes in extreme events: regional and seasonal dimension

This study systematically analyzes the complete IPCC AR4 (CMIP3) ensemble of GCM simulations with respect to changes in extreme event characteristics at the end of the 21st century compared to present-day conditions. It complements previous studies by investigating a more comprehensive database and considering seasonal changes beside the annual time scale. Confirming previous studies, the agreement between the GCMs is generally high for temperature-related extremes, indicating increases of warm day occurrences and heatwave lengths, and decreases of cold extremes. However, we identify issues with the choice of indices used to quantify heatwave lengths, which do overall not affect the sign of the changes, but strongly impact the magnitude and patterns of projected changes in heatwave characteristics. Projected changes in precipitation and dryness extremes are more ambiguous than those in temperature extremes, despite some robust features, such as increasing dryness over the Mediterranean and increasing heavy precipitation over the Northern high latitudes. We also find that the assessment of projected changes in dryness depends on the index choice, and that models show less agreement regarding changes in soil moisture than in the commonly used ‘consecutive dry days’ index, which is based on precipitation data only. Finally an analysis of the scaling of changes of extreme temperature quantiles with global, regional and seasonal warming shows that much of the extreme quantile changes are due to a seasonal scaling of the regional annual-mean warming. This emphasizes the importance of the seasonal time scale also for extremes. Changes in extreme quantiles of temperature on land scale with changes in global annual mean temperature by a factor of more than 2 in some regions and seasons, implying large changes in extremes in several countries, even for the commonly discussed global 2°C-warming target.     

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。     

不同升温阈值下中国地区极端气候事件变化预估

本文基于耦合模式比较计划第五阶段(CMIP5)的18个全球气候模式的模拟结果,预估了全球平均气温在不同典型浓度路径(RCPs)下达到2℃、3℃和4℃阈值时,中国地区气温和降水的变化,并采用了具有稳定统计意义的27个极端气候指标定量评估了全球平均气温达到不同阈值时,中国地区极端气候事件的可能变化。结果表明,未来我国平均气温增幅将高于全球平均增暖,极端暖事件(如暖夜、暖昼、热带夜)明显增多,达到4℃阈值时,暖夜指数相比参考时段增加约49.9%。极端冷事件(如冷夜、冷昼、霜冻)减少。随全球气温升高,中国北方平均降水增多。在不同升温阈值下,中国地区降水的极端性都体现出增强的趋势,强降水事件发生频率(如中雨日数、大雨日数)和强度(如五日最大降水量、极端强降水量)都明显增加。随升温阈值的升高,这些变化幅度更大,在 RCP8.5 情景下全球升温 3℃和4℃时,中国平均五日最大降水分别增加 12.5mm和17.0mm。我国西南地区极端降水强度的增幅高于其他地区。     

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.     

Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?

Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during1961–2005, the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5), are assessed in terms of spatial distribution and interannual variability. The CMIP6 multi-model ensemble mean(CMIP6-MME) can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature, and minimum daily minimum temperature. However, CMIP6-MME has difficulties in reproducing cold nights and warm days, and has large cold biases over the Tibetan Plateau. Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices. Compared to CMIP5, CMIP6 models show improvements in the simulation of climate indices over China. This is particularly true for precipitation indices for both the climatological pattern and the interannual variation, except for the consecutive dry days. The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME) to 79%(CMIP6-MME). The most striking feature is that the dry biases in southern China, very persistent and general in CMIP5-MME, are largely reduced in CMIP6-MME. Stronger ascent together with more abundant moisture can explain this reduction in dry biases. Wet biases for total precipitation, heavy precipitation, and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME, but smaller, compared to CMIP5-MME.     

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。     

2006～2013年CMIP5模式中国降水预估误差分析

用第五次耦合模式比较计划（CMIP5）的10个模式模拟结果与英国东安格利亚大学（UEA）气候研究机构（CRU）的最新降水格点分析资料比较,评估了三种典型浓度路径（RCPs）排放情景下模式集合对2006～2013年中国降水预估误差,结果发现模式间年降水预估在西北和东部沿海地区差异较明显,在沿海地区模式降水估计偏少,在西部和北方大部分地区偏多;冬半年大部分地区模式降水明显偏多,部分地区甚至偏多一倍以上;夏半年东部季风区降水估计偏少,但西部仍然偏多。模式降水误差随时间变化,夏半年误差变化明显的区域主要集中在北方和东部地区,冬半年在东北南部、华东及华南等地。此外,提高排放情景对年降水量估计影响明显的地区主要集中在我国西部的部分地区,加剧了西北模式降水估计偏多程度,但对东部地区影响不大。El Ni?o与La Ni?a年的模式降水误差分布相似,仅在沿海部分地区和华北北部差异较明显,逐年误差分布特征也与此相似。各种误差的对比分析表明,模式降水误差可能多来自模式本身存在的问题,如积云对流参数化、固体降水物理过程、地形处理及分辨率等。这些误差特征说明,直接使用CMIP5模式集合情景输出资料估计未来降水的方法存在较大的不确定性,必须对其进行评估,以降低潜在用户或决策者们制定未来规划的风险。     

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.     

中国日降水的分布特征和未来变化

通过对1961—2010年中国540个气象站逐日降水观测数据和高精度区域气候模式CCLM（COSMO model in climate mode）3839个格点模拟值的对比,检验CCLM模式对中国日降水的模拟能力,揭示了1961—2010年日降水分布格局的变化特征;同时利用CCLM模式对中国地区2011—2050年的日降水预估值（SRES-A1B情景）,运用概率统计和极值理论方法,分析了2011—2050年日降水序列及其极值的可能变化趋势。结果表明：除华南和青藏高原西部存在着较大的偏差以外,模式和观测日降水序列的峰度和偏度的分布格局较一致,空间相关系数达到0.75以上,CCLM能够很好地模拟中国日降水的分布特征。2011—2050年,峰度和偏度在江淮部分地区、东北与内蒙中东部等地区呈显著增加趋势,降水极端事件将会增多;最大日降水量和汛期最多无降水日数在上述地区的增加,进一步反映干旱和洪涝出现概率将升高。     

Extreme climate events in China: IPCC-AR4 model evaluation and projection

Observations from 550 surface stations in China during 1961–2000 are used to evaluate the skill of seven global coupled climate models in simulating extreme temperature and precipitation indices. It is found that the models have certain abilities to simulate both the spatial distributions of extreme climate indices and their trends in the observed period. The models’ abilities are higher overall for extreme temperature indices than for extreme precipitation indices. The well-simulated temperature indices are frost days (Fd), heat wave duration index (HWDI) and annual extreme temperature range (ETR). The well-simulated precipitation indices are the fraction of annual precipitation total due to events exceeding the 95th percentile (R95T) and simple daily intensity index (SDII). In a general manner, the multi-model ensemble has the best skill. For the projections of the extreme temperature indices, trends over the twenty-first century and changes at the end of the twenty-first century go into the same direction. Both frost days and annual extreme temperature range show decreasing trends, while growing season length, heat wave duration and warm nights show increasing trends. The increases are especially manifested in the Tibetan Plateau and in Southwest China. For extreme precipitation indices, the end of the twenty-first century is expected to have more frequent and more intense extreme precipitation. This is particularly visible in the middle and lower reaches of the Yangtze River, in the Southeast coastal region, in the west part of Northwest China, and in the Tibetan Plateau. In the meanwhile, accompanying the decrease in the maximum number of consecutive dry days in Northeast and Northwest, drought situation will reduce in these regions.     

Propagation characteristic of atmospheric responses to abnormal warm SST in the Kuroshio Extension in winter

A complete picture of changes in climate extremes has been presented for Shanxi Province, China using data from all 61 available stations. The results reveal large spatial coherence of trends for the majority of extremes, especially for temperature extremes. Significant and symmetric increasing trends of the annual mean maximum and mean minimum temperatures (TXam, TNam) are detected over the past 50 years. Significant positive trends are detected for warm days and nights (TX90p, TN90p), the highest and lowest maximum and minimum temperatures (TXx, TXn, TNx, TNn), and the growing season length (GSL). Significant negative trends are revealed for cold days and nights (TX10p, TN10p) and frost days (FD). Significant decreases are found in the number of heavy precipitation days (R10mm) and wet day precipitation (PRCPTOT). Although Shanxi and the northern half of North China Plain (NNCP) have been grouped into the North China region and assessed together in previous studies for China, the changes in climate extremes in the NNCP have some pronounced differences in comparison with Shanxi. Noticeably, the increase of the TNam is at a rate nearly three times that of the TXam during 1959–2008 over the NNCP. The warming for the nighttime indices TN90p, TN10p, TNx, and TNn is stronger, but the warming for the daytime indices TX10p, TX90p, and TXx is weaker in the NNCP. There is no significant decrease for R10mm and PRCPTOT in the NNCP.     

全球海气耦合模式对中国区域年代际气候变化预测能力的评估

利用4个海气耦合模式对1960～2005年的多年代际回报结果,评估模式对中国区域年代际气候变化(温度和降水)的预测潜力,并初步给出2005～2015年的气候预测结果。与CMIP3多模式集合1960～2000年结果以及观测实况比较的结果表明:融入观测资料进行同化的年代际气候预测模式,对中国区域温度和降水的模拟能力总体好于CMIP3模式。年代际气候预测模式对温度气候场的模拟仍以"冷偏差"为主,但较之CMIP3模式已有显著改进,中国区域平均的冷偏差减少1.3°C;对降水气候场的模拟仍以"湿偏差"为主,但在华南沿海和西北内陆降水的模拟能力优于CMIP3模式,中国区域平均的湿偏差降低了20%。年代际模式和CMIP3模式都能较好地模拟出中国区域尤其是北方20世纪后期的增暖信号;但CMIP3模式对20世纪后期中国东部降水的旱涝结构演变的模拟与观测相反;而年代际气候预测模式未能再现华北偏旱的变化,但能成功地模拟江淮流域和华南沿海的旱涝演变。2005～2015年的10年预测表明中国区域将继续增暖0.3～0.7°C,且增温幅度北方大于南方,增幅中心位于西北内陆和青藏高原;而降水的变化趋势不显著,黄淮地区、西北内陆和青藏高原的降水略有增加,而西南地区降水将减少。但需要指出的是,这种预测的不确定性是相当大的。     

An intercomparison of model-simulated in extreme rainfall and temperature events during the last half of the twentieth century. Part 1: mean values and variability

In this study we examine the performance of eight of the IPCC AR4 global coupled climate models used in the WCRP CMIP3 Multimodel Dataset, as well as their ensemble mean, in simulating annual indices of extreme temperature and precipitation climate events in South America. In this first part we focus on comparing observed and modeled mean values and interannual variability. Two extreme temperature indices based on minimum temperature (warm nights and frost days) and three indices of extreme precipitation (R95t, R10 and consecutive dry days), obtained both from meteorological stations during 1961–2000 and model outputs, were compared. The number of warm nights are better represented by models than the FD. The interannual variability pattern is also in good agreement with the observed values. For precipitation, the index that is best represented by the models is the R95t, which relates the extreme precipitation to local climate. The maximum of dryness observed over the central Argentinian Andes or the extensive dry season of the Amazon region could not be represented by any model.     

Evaluation of 2-m temperature and precipitation products of the Climate Forecast System version 2 over Iran

Using a continuous multi-decadal simulations over the period 1981–2010, subseasonal to seasonal simulations of the Climate Forecast System version 2 (CFSv2) over Iran against the Climatic Research Unit (CRU) dataset are evaluated. CFSv2 shows cold biases over northern hillsides of the Alborz Mountains with the Mediterranean climate and warm biases over northern regions of the Persian Gulf and the Oman Sea with a dry climate. Magnitude of the model bias for 2-m temperature over different regions of Iran varies by season, with the least bias in temperate seasons of spring and autumn, and the largest bias in summer. The model bias decreases as temporal averaging period increases from seasonal to annual. The forecast generally produces dry and wet biases over dry and wet regions of Iran, respectively. In general, 2-m temperature over Iran is better captured than precipitation, but the prediction skill of precipitation is generally high over western Iran. Averaged over Iran, observations indicated that 2-m temperature has been gradually increasing during the studied period, with a rate of approximately 0.5 °C per decade, and the upward trend is well simulated by CFSv2. Averaged over Iran, both observations and simulation results indicated that precipitation has been decreasing in spring, with averaged decreasing trends of 0.8 mm (observed) and 1.7 mm (simulated) per season each year during the period 1981–2010. Observations indicated that the maximum increasing trend of 2-m temperature has occurred over western Iran (nearly 0.7 °C per decade), while the maximum decreasing trend of annual precipitation has occurred over western and parts of southern Iran (nearly 45 to 50 mm per decade).     

未来30年亚洲降水情景预估及偏差订正

借助第五次国际耦合模式比较计划(Coupled Model Intercomparison Project Phase 5,CMIP5)多模式集合数据及英国气候研究所(Climatic Research Unit Time-Series version 4.0,CRU TSv4.0)的格点降水资料,分析了多模式集合平均...     

21世纪前期中国降水预估及其订正

用全球格点分析数据集（CRU TSv4.0）月降水资料和24个CMIP5（Coupled Model Intercomparison Project Phase 5）模式历史模拟数据以及RCP4.5情景下的预估数据,分析了多模式集合平均降水的偏差特征并进行了扣除模式气候漂移和一元对数差分回归订正。结果表明,模式降水在西部和北部明显偏多,东南沿海偏少;冷季（11月至次年4月）在全国大部分地区模式降水偏多,暖季（5～10月）东南沿海季风区偏少。1956～2005年多模式集合平均历史模拟降水偏差中84%属于气候漂移,其余是偏差的非定常模态。扣除气候漂移后,RCP4.5情景下2006～2015年中国模式降水预估偏差减小90%以上,大部分地区降水偏差百分率分布在±5%以内,仅在青藏高原西部和西北中部等地区模式降水偏多10%～40%;暖季降水偏差分布与年降水量类似;冷季偏差较大,北方降水偏多,南方偏少。检验表明,一元线性对数差分回归方程订正后,模式降水对于2006～2015年期间西南和江南中部的干旱少雨气候均能再现,且距平同号率高于多模式集合平均和扣除气候漂移的结果。用该方法对RCP4.5情景下2016～2035年模式预估降水进行订正,结果显示,南方（淮河以南）降水减少5%～20%,河套、内蒙古和华北北部减少20%～40%,东北南部、淮河流域、西北大部增加10%～40%及以上,东南沿海和台湾省降水增加10%～20%。以上降水预估结果说明,在RCP4.5情景下,21世纪前期持续十年的西南干旱会略有缓解,但南方降水偏少格局变化不大,淮河流域和三江源区及其以西等地降水可能明显增加。中国降水异常分布总体呈现南北少、中间多的格局,但北方和西部高山地带的降水预估存在较大的不确定性。     

Changes in temperature extremes based on a 6-hourly dataset in China from 1961–2005

Changes in Chinese temperature extremes are presented based on a six-hourly surface air temperature dataset for the period 1961--2005. These temperature series are manually observed at 0200, 0800, 1400, and 2000 Beijing Time (LST), and percentile based extreme indices of these time series are chosen for analysis. Although there is a difference in time among the different time zones across China, as more than 80% of the stations are located in two adjacent time zones, these indices for all the stations are called warm (cold) nights (0200 LST), warm (cold) mornings (0800 LST), warm (cold) days (1400 LST), and warm (cold) evenings (2000 LST), respectively for convenience. The frequency of the annual warm extremes has generally increased, while the frequency of the annual cold extremes has decreased, and significant changes are mainly observed in northern China, the Tibetan Plateau, and the southernmost part of China. Based on the national average, annual warm (cold) nights increase (decrease) at a rate of 5.66 (-5.92) d (10 yr)^-1, annual warm (cold) days increase (decrease) at a rate of 3.97 (-2.98) d (10 yr)^-1, and the trends for the annual warm (cold) mornings and evenings are 4.35 (-4.96) and 5.95 (-4.35) d (10 yr)^-1, respectively. For China as a whole, the increasing rates for the occurrence of seasonal warm extremes are larger in the nighttime (0200, 2000 LST) than these in the daytime (0800, 1400 LST), the maximal increase occurs at 2000 LST except in the summer and the minimal increase occurs at 1400 LST except in autumn; the maximal decrease in the occurrence of seasonal cold extremes occurs at 0200 LST and the minimal decrease occurs at 1400 LST.     

Future changes and uncertainties in temperature and precipitation over China based on CMIP5 models

Climate changes in future 21 st century China and their uncertainties are evaluated based on 22 climate models from the Coupled Model Intercomparison Project Phase 5(CMIP5). By 2081–2100, the annual mean surface air temperature(SAT) is predicted to increase by 1.3℃± 0.7℃, 2.6℃± 0.8℃ and 5.2℃± 1.2℃ under the Representative Concentration Pathway(RCP) scenarios RCP2.6, RCP4.5 and RCP8.5, relative to 1986–2005, respectively. The future change in SAT averaged over China increases the most in autumn/winter and the least in spring, while the uncertainty shows little seasonal variation.Spatially, the annual and seasonal mean SAT both show a homogeneous warming pattern across China, with a warming rate increasing from southeastern China to the Tibetan Plateau and northern China, invariant with time and emissions scenario.The associated uncertainty in SAT decreases from northern to southern China. Meanwhile, by 2081–2100, the annual mean precipitation increases by 5% ± 5%, 8% ± 6% and 12% ± 8% under RCP2.6, RCP4.5 and RCP8.5, respectively. The national average precipitation anomaly percentage, largest in spring and smallest in winter, and its uncertainty, largest in winter and smallest in autumn, show visible seasonal variations. Although at a low confidence level, a homogeneous wetting pattern is projected across China on the annual mean scale, with a larger increasing percentage in northern China and a weak drying in southern China in the early 21 st century. The associated uncertainty is also generally larger in northern China and smaller in southwestern China. In addition, both SAT and precipitation usually show larger seasonal variability on the sub-regional scale compared with the national average.