Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).     

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.     

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。     

CMIP6全球气候模式对中国极端降水模拟能力的评估及其与CMIP5的比较

对CMIP6全球气候模式在中国地区极端降水的模拟能力进行了综合评估。基于CN05.1观测数据集和32个CMIP6全球气候模式的降水数据,采用8个常用极端降水指数对极端降水进行了定量描述。研究结果表明,在极端降水的气候平均态方面,CMIP6多模式集合对1961—2005年中国地区区域平均的8个极端降水指数模拟的平均相对误差为29.94%,相较CMIP5降低了2.95个百分点。极端降水的气候变率方面,CMIP6多模式集合对区域平均的8个极端降水指数模拟的平均相对误差为10.10%,相较CMIP5降低5.45个百分点。此外,利用TS评分进行模式间比较,CMIP6的平均分（0.78）高于CMIP5（0.75）,且模拟能力排名前五的模式中CMIP6占4个。对比14个同源模式的TS评分可以发现,CMIP6（0.91）相对于CMIP5（0.68）的模拟能力显著提高。进一步研究发现,CMIP6相对于CMIP5对不同区域极端降水模拟能力的改进有所区别:CMIP6对干旱区平均的气候态和变率方面改进明显,而对于湿润区的改进主要表现在对极端降水空间相关模拟能力的提高。综上,在中国地区,CMIP6相较于CMIP5对极端降水的模拟能力总体上有提升。      

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.     

8个CMIP5模式对中国极端气温的模拟和预估

利用8个耦合模式比较计划第五阶段（CMIP5）模式结果,采用加权平均方法进行多模式集合,并与NCEP再分析资料进行对比分析,评估了CMIP5模式对中国极端气温的模拟效果,在此基础上,对未来极端气温进行预估。CMIP5模式对中国8个极端气温指数和20年一遇最高（低）气温有模拟能力,所有极端气温指数模拟和观测结果的时间相关均达到0.10显著性水平,20年一遇最高、最低气温模拟和观测结果空间相关系数均超过0.98。在中等排放RCP4.5情景下,未来中国极暖（冷）日数增多（减少）,到21世纪中期热浪指数增加2.6倍,到21世纪末期寒潮指数减少71%,20年一遇最高（低）气温在中国地区均呈现升高趋势,局部升温幅度达到4℃。     

Projection of heat waves over China for eight different global warming targets using 12 CMIP5 models

Simulation and projection of the characteristics of heat waves over China were investigated using 12 CMIP5 global climate models and the CN05.1 observational gridded dataset. Four heat wave indices (heat wave frequency, longest heat wave duration, heat wave days, and high temperature days) were adopted in the analysis. Evaluations of the 12 CMIP5 models and their ensemble indicated that the multi-model ensemble could capture the spatiotemporal characteristics of heat wave variation over China. The inter-decadal variations of heat waves during 1961–2005 can be well simulated by multi-model ensemble. Based on model projections, the features of heat waves over China for eight different global warming targets (1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, and 5.0 °C) were explored. The results showed that the frequency and intensity of heat waves would increase more dramatically as the global mean temperature rise attained higher warming targets. Under the RCP8.5 scenario, the four China-averaged heat wave indices would increase from about 1.0 times/year, 2.5, 5.4, and 13.8 days/year to about 3.2 times/year, 14.0, 32.0, and 31.9 days/year for 1.5 and 5.0 °C warming targets, respectively. Those regions that suffer severe heat waves in the base climate would experience the heat waves with greater frequency and severity following global temperature rise. It is also noteworthy that the areas in which a greater number of severe heat waves occur displayed considerable expansion. Moreover, the model uncertainties exhibit a gradual enhancement with projected time extending from 2006 to 2099.     

Future change of extreme temperature climate indices over East Asia with uncertainties estimation in the CMIP5

How well the climate models simulate extreme temperature over East Asia and how the extreme indices would change under anthropogenic global warming are investigated. The indices studied include hot days (HD), tropical nights (TN), growing degree days (GDD), and cooling degree days (CDD) in summer and heating degree days (HDD) and frost days (FD) in winter. The representative concentration pathway 4.5 (RCP 4.5) experiments for the period of 2075–2099 are compared with historical simulations for the period of 1979–2005 from 15 coupled models that are participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5). To optimally estimate future change and its uncertainty, groups of best models are selected based on Taylor diagrams, relative entropy, and probability density function (PDF) methods previously suggested. Overall, the best models’ multi-model ensemble based on Taylor diagrams has the lowest errors in reproducing temperature extremes in the present climate among three methods. Selected best models in three methods tend to project considerably different changes in the extreme indices from each other, indicating that the selection of reliable models are of critical importance to reduce uncertainties. Three groups of best models show significant increase of summerbased indices but decrease of the winter-based indices. Over East Asia, the most significant increase is seen in the HD (336 ± 23.4% of current climate) and the most significant decrease is appeared in the HDD (82 ± 4.2%). It is suggested that the larger future change in the HD is found over in the Southeastern China region, probably due to a higher local maximum temperature in the present climate. All of the indices show the largest uncertainty over Southeastern China, particularly in the TN (~3.9 times as large as uncertainty over East Asia) and in the HD (~2.4). It is further noted that the TN reveals the largest uncertainty over three East Asian countries (~1.7 and 1.4 over Korea and Japan, respectively). These future changes in extreme temperature events have an important implication for energy-saving applications and human molarity in the future.     

Analyses of extreme climate events over china based on CMIP5 historical and future simulations

Based on observations and 12 simulations from Coupled Model Intercomparison Project Phase 5 （CMIP5） models, cli- matic extremes and their changes over China in the past and under the future scenarios of three Representative Concentration Pathways （RCPs） are analyzed. In observations, frost days （FD） and low-temperature threshold days （TN10P） show a de- creasing trend, and summer days （SU）, high-temperature threshold days （TX90P）, heavy precipitation days （R20）, and the contribution of heavy precipitation days （P95T） show an increasing trend. Most models are able to simulate the main char- acteristics of most extreme indices. In particular, the mean FD and TX90P are reproduced the best, and the basic trends of FD, TN10P, SU and TX90P are represented. For the FD and SU indexes, most models show good ability in capturing the spatial differences between the mean state of the periods 1986--2005 and 1961-80; however, for other indices, the simulation abilities for spatial disparity are less satisfactory and need to be improved. Under the high emissions scenario of RCP8.5, the century-scale linear changes of the multi-model ensemble （MME） for FD, SU, TN10P, TX90P, R20 and P95T are -46.9, 46.0, -27.1, 175.4, and 2.9 days, and 9.9%, respectively; and the spatial change scope for each index is consistent with the emissions intensity. Due to the complexities of physical process pararneterizations and the limitation of forcing data, great uncertainty still exists with respect to the simulation of climatic extremes.     

Statistical modeling of CMIP5 projected changes in extreme wet spells over China in the late 21st century

The observed intensity, frequency, and duration (IFD) of summer wet spells, defined here as extreme events with one or more consecutive days in which daily precipitation exceeds a given threshold (the 95th percentile), and their future changes in RCP4.5 and RCP8.5 in the late 21st century over China, are investigated by using the wet spell model (WSM) and by extending the point process approach to extreme value analysis. Wet spell intensity is modeled by a conditional generalized Pareto distribution, frequency by a Poisson distribution, and duration by a geometric distribution, respectively. The WSM is able to realistically model summer extreme rainfall spells during 1961–2005, as verified with observations at 553 stations throughout China. To minimize the impact of systematic biases over China in the global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), five best GCMs are selected based on their performance to reproduce observed wet spell IFD and average precipitation during the historical period. Furthermore, a quantile–quantile scaling correction procedure is proposed and applied to produce ensemble projections of wet spell IFD and corresponding probability distributions. The results show that in the late 21st century, most of China will experience more extreme rainfall and less low-intensity rainfall. The intensity and frequency of wet spells are projected to increase considerably, while the duration of wet spells will increase but to a much less extent. The IFD changes in RCP8.5 are in general much larger than those in RCP4.5.     

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。     

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。     

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.     

CMIP5模式对中国东北气候模拟能力的评估

利用CN05观测资料和参与IPCC第五次评估报告的45个全球气候系统模式的模拟结果,分析了新一代全球气候模式对中国东北三省(1961~2005年)气温和降水的模拟能力。结果表明:1)绝大多数模式都能较好地模拟出研究区内显著增温的趋势,对气温的年际变化模拟能力则相对有限;2)所有模式均能很好地再现气温气候态的空间分布特征,且多模式集合模拟结果优于绝大多数单个模式,空间相关系数达到了0.96;3)对于降水的模拟结果,模式间差异较大,多模式集合能较好地再现其空间分布规律(空间相关系数为0.86),对降水年际变化及线性变化趋势的模拟能力则较差。总体来说,多模式集合对东北气候的时空变化特征具有一定的模拟能力,且对气温模拟效果优于降水,对空间分布的模拟能力优于时间变化。     

近40年我国极端温度变化趋势和季节特征

利用1961—2000年我国194个测站逐日最高温度和最低温度器测资料,结合具有实际意义的季节极端温度指数,分析了我国近40年极端温度事件的年变化趋势和季节特征。对年极端气候指数的研究表明:绝对阈值定义的冷暖指数由于无法考虑南北气候差异,其结果不理想。百分比阈值所得的冷暖指数中,冷日指数和暖日指数具有不对称性,冷夜指数和暖夜指数具有较强的对称性。对季节极端温度指数研究表明:冬季极端冷指数变化趋势最为明显,夏季极端暖指数的变化趋势次之,春、秋两季极端冷指数的变化趋势不明显;年和季节尺度的极端冷暖指数均反映出增暖趋势。     

Detection of the anthropogenic signal and urbanization effects in extreme temperature changes in eastern China

With its rapid rise in temperatures and accelerated urbanization in recent decades, eastern China may be affected by both global warming and the urban heat island effect. To investigate the influence of anthropogenic forcing and urbanization on extreme temperature, the authors conducted detection and attribution analyses on 16 extreme indices using extended observational data during 1958–2020 and the models that participated in CMIP5 and CMIP6. The extended observational data till 2020 show continued warming in extreme temperatures in recent years. Most of the indices display an increase in warm extremes and decrease in cold extremes. Both CMIP5 and CMIP6 models are able to reflect these warming features, albeit the models can over- or underestimate some extreme indices. The two-signal detection with anthropogenic and urbanization effects jointly considered showed that the anthropogenic and urban signals can be simultaneously detected and separated only in two frequency indices, i.e., the frequency of warm and cold nights. The anthropogenic forcing explains about two-thirds of the warming, while URB contributes about one-third for these two indices. For most of the other indices, only the anthropogenic signal can be detected. This indicates that the urban signal is distinct from the natural variability mainly for the nighttime frequency indices but not for the other extreme temperature indies. Given the important influence of nighttime extremes on human health, this suggests an urgent need for cities to adapt to both global warming and urbanization.摘要作为中国经济最发达的地区, 中国东部受到城市热岛效应和温室气体排放等人类活动的明显影响. 本文利用最新的观测和全球气候模式资料, 对极端温度强度, 频率和持续时间等16个极端温度指数进行了检测归因分析, 研究了人为强迫和城市化效应对中国东部极端温度变化的影响. 结果表明, 近年来极端温度持续增暖, 极端暖事件增加, 极端冷事件减少. 新一代全球气候模式能够合理地反映这些变暖特征, 但是部分模式可能高估或低估了观测到的变化. 基于最优指纹方法的双信号检测表明, 人为信号和城市化效应只能在暖夜和冷夜两个频率指标上同时被检测并分离, 其变化约三分之二可归因于人类活动, 剩余的三分之一可归因于城市化效应. 而在极端温度其他指数的变化中, 只有人类活动的影响能够被检测到.     

CMIP5全球气候模式对中国地区降水模拟能力的评估

使用多种观测资料和43个参加耦合模式比较计划第五阶段（CMIP5）的全球气候模式模拟数据,评估分析了全球气候模式对中国地区1980-2005年降水特征的模拟能力。结果表明：多数CMIP5模式能够模拟出中国降水由西北向东南递增的分布特点,这与耦合模式比较计划第三阶段（CMIP3）的模式模拟结果类似,但华南地区降水模拟偏少,西部高原地区降水模拟偏多。模式能够较好地模拟出降水冬弱夏强的季节变化特征,但降水模拟系统性偏多。从EOF分析结果来看,多数CMIP5模式可以再现中国地区年平均降水的时空变化特征,集合平均的表现优于CMIP3。多模式集合在月、季、年时间尺度下模拟的平均值优于大部分单个模式的结果。CMIP5中6个中国模式的模拟能力与其他模式相当,其中FGOALS-g2、BCC-CSM1-1-m的模拟能力相对较好。     

Changing climate extremes in the Northeast United States: observations and projections from CMIP5

Climate extremes indices are evaluated for the northeast United States and adjacent Canada (Northeast) using gridded observations and twenty-three CMIP5 coupled models. Previous results have demonstrated observed increases in warm and wet extremes and decreases in cold extremes, consistent with changes expected in a warming world. Here, a significant shift is found in the distribution of observed total annual precipitation over 1981-2010. In addition, significant positive trends are seen in all observed wet precipitation indices over 1951-2010. For the Northeast region, CMIP5 models project significant shifts in the distributions of most temperature and precipitation indices by 2041-2070. By the late century, the coldest (driest) future extremes are projected to be warmer (wetter) than the warmest (wettest) extremes at present. The multimodel interquartile range compares well with observations, providing a measure of confidence in the projections in this region. Spatial analysis suggests that the largest increases in heavy precipitation extremes are projected for northern, coastal, and mountainous areas. Results suggest that the projected increase in total annual precipitation is strongly influenced by increases in winter wet extremes. The largest decreases in cold extremes are projected for northern and interior portions of the Northeast, while the largest increases in summer warm extremes are projected for densely populated southern, central, and coastal areas. This study provides a regional analysis and verification of the latest generation of CMIP global models specifically for the Northeast, useful to stakeholders focused on understanding and adapting to climate change and its impacts in the region.     

Changes in climate extremes on the territory of Siberia by the middle of the 21st century: An ensemble forecast based on the MGO regional climate model

The results are analyzed of the ensemble forecast of temperature and precipitation extremes on the territory of Siberia by the middle of the 21st century based on the regional climate model of the Main Geophysical Observatory (MGO) with the resolution of 25 km. The results of computation of oceanic components of CMIP3 coupled models are used as the boundary conditions on the sea surface. It is demonstrated that the high resolution of the regional model enables to simulate the observed climate variability in a more realistic way as compared to the low-resolution models. The analysis of the signal-to-noise ratio for future climate changes made it possible to determine to which degree its internal variability for various time scales (from interannual to interdecennial one) bounds the potential of the ensemble to compute the statistically significant anthropogenic changes of extremes. A comparative analysis of variations of extreme and average seasonal characteristics of the Siberian climate is carried out.