黄河源区未来地面气温变化的统计降尺度分析

大气环流模式(GCMs)模拟预测的气候变化情景,必须经过降尺度处理后才能得出次网格尺度上未来气候变化的时空分布细节,才能满足评估气候变化对资源、环境和社会经济等影响的需要.本文在简单介绍了目前降尺度模型的研究现状后,重点分析了统计降尺度方法的优缺点及适用性,并应用黄河源区7个站点1961-1990年的实测地区最高气温和最低气温资料,对统计降尺度模型(SDSM)的应用进行了分析和验证.首先利用SDSM建立大尺度气候要素和地面气温变量间的统计转换关系,确定模型应用的预报因子变量,然后用独立的观测资料验证模型的可靠性,最后把建立好的统计关系应用于英国Hadley中心海气耦合模式(HadCM3 SERS B2)的输出,分别生成了黄河源区7个站点未来3个时段2020s,2050s和2080s的气温变化情景.在此基础上,应用Arc/GIS的Kriging插值方法获得整个区域的气温变化情景进行分析.结果表明,日最高气温模拟值随时间推移增幅很快,3个时段(2020s,2050s和2080s)的平均气温变化情景分别为1.34,2.60和3.90℃,而日最低气温变化相对不明显,3个时段的平均气温变化情景分别为0.87,1.49和2.27℃.表现在每个季节和每个月的变化情景又各不相同,日最高气温以春季和秋季变化最显著,而日最低气温则以夏季和秋季的变化最为明显.     

沙漠绿洲非均匀分布引起的中尺度通量的数值模拟

为了研究大气环流模式次网格中尺度通量的参数化问题，本文发展了一个Pielke中尺度边界层与陆面过程的耦合模式，陆面过程模式中包括一个简单植被水热传输模式及一个裸土沙漠模式。利用这一耦合模式，对黑河试验区中沙漠和绿洲这种典型的非均匀下垫面进行了模拟，20多个数值试验的模拟结果表明:（1）中尺度通量在特定的情况下具有和湍流通量相当的重要性，因此，大尺度模式中对中尺度通量的参数化是十分必要的。（2）对于中尺度通量的发展存在一个明显的最优尺度和最优块数，即当绿洲尺度为60 km，3块时，中尺度通量最大。而且当块数增加到一定数目时，可以忽略非均匀效应。（3）背景风速的增大可以使中尺度通量减小；粗糙度的试验说明非均匀块之间的热力差异的减小可使中尺度通量非线性地减小。     

近50 a来黄河上游水循环要素变化分析

 根据水文、气象台站观测资料,分析了黄河上游有器测资料几十年来降水、温度、径流等水循环素的变化过程与特征。结果显示,温度近几十年来流域各个地方有着不同程度的上升,与全球变暖有着明显的对应关系;而随着气温的上升,蒸发和下渗呈增加的趋势。降水变化的区域性特征十分明显,降水量的增减随地理位置不同而差异较大。受主要产流区域降水减少,气温上升的影响,黄河上游产水量呈持续递减的态势。在上述分析基础上,利用全球气候模式(GCMs)与统计模式对未来流域降水和径流的可能变化进行了预测。结果表明,未来30 a里,随着温度将进一步上升,降水量将比目前有明显增加,黄河上游的径流量将随降水量的增加而进入一个相对丰水的时期。     

INVESTIGATIONS ON SHORT-TERM CLIMATE PREDICTION BY GCMs IN CHINA

Investigations on the short-term climate predictions by general circulation models(GCMs)inChina have been summarized and reviewed in this paper.The research shows that GCMs have thecapability to predict the seasonal and annual characteristics of atmospheric circulation in theNorthern Hemisphere and the patterns of temperature and precipitation over China.It is inspiringto notice that the GCMs have the ability to predict the summer rainfall over China before twoseasons.Several issues for the short-term climate prediction by the GCMs have been discussed inthis paper.     

Simulation evaluation and future prediction of the IPCC-AR4 GCMs on the extreme temperatures in China

On the basis of the temperature observations during 1961-2000 in China, seven coupled general circulation models＇ （GCMs） extreme temperature products are evaluated supplied by the Intergovernmental Panel on Climate Change＇ s 4th Assessment Report （IPCC-AR4）. The extreme temperature indices in use are frost days （FD）, growing season length （GSL）, extreme temperature range （ETR）, warm nights （TN90）, and heat wave duration index （HWDI）. Results indicate that all the seven models are capable of simulating spatial and temporal variations in temperature characteristics, and their ensemble acts more reliable than any single one. Among the seven models, GFDL-CM2.0 and MIROC3.2 performances are much better. Besides, most of the models are able to present linear trends of the same positive/negative signs as the observations but for weaker intensities. The simulation effects are different on a nationwide basis, with 110°N as the division, east （west） of which the effects are better （worse） and the poorer over the Qinghai-Tibetan Plateau in China. The predictions for the 21st century on emissions scenarios show that except decreases in the FD and ETR, other indices display significant increasing trend, especially for the indices of HWDI and TN90, which represent the notable extreme climate. This indicates that the temperature-related climate is moving towards the extreme. In the late 21st century, the GSL and TN90 （HWDI） increase most notably in southwest China （the Qinghai-Tibetan Plateau）, and the FD decrease most remarkably in the Qinghai-Tibetan Plateau, northwest and northeast of China. Apart from South China, the yearly change range of the extreme temperature is reduced in most of China.     

Evaluation of monthly precipitation forecasting skill of the National Multi‐model Ensemble in the summer season

As a test bed, the National Multi‐model Ensemble (NMME) comprises seven climate models from different sources, including the National Oceanic and Atmospheric Administration, the National Aeronautics and Space Administration, the National Center for Atmospheric Research and the International Research Institute for Climate and Society. It provides 89 ensemble members of precipitation forecasts at different lead times. Precipitation forecasting from climate models has been applied to provide streamflow forecasts, and its utility in water resource system operation has been demonstrated in the literature. In this study, 1‐month‐ahead precipitation forecasts from NMME are evaluated for 945 grid points of 1°‐by‐1° resolution over the continental USA using mean square error and rank probability score. The temporal and spatial variabilities of the forecasting skill over different months of the summer season are discussed. The relation between forecasting uncertainty and observed precipitation is investigated. Such analyses have implications for monthly operational forecasts and water resource management at the watershed scale. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessment of GCM simulations of annual and seasonal rainfall and daily rainfall distribution across south‐east Australia

Global warming can potentially lead to changes in future rainfall and runoff and can significantly impact the regional hydrology and future availability of water resources. All the large‐scale climate impact studies use the future climate projections from global climate models (GCMs) to estimate the impact on future water availability. This paper presents results from a detailed assessment to investigate the capability of 15 GCMs to reproduce the observed historical annual and seasonal mean rainfalls, the observed annual rainfall series and the observed daily rainfall distribution across south‐east Australia. The assessment shows that the GCMs can generally reproduce the spatial patterns of mean seasonal and annual rainfalls. However, there can be considerable differences between the mean rainfalls simulated by the GCMs and the observed rainfall. The results clearly show that none of the GCMs can simulate the actual annual rainfall time series or the trend in the annual rainfall. The GCMs can also generally reproduce the observed daily (ranked) rainfall distribution at the GCM scale. The GCMs are ranked against their abilities to reproduce the observed historical mean annual rainfall and daily rainfall distribution, and, based on the combined score, the better GCMs include MPI‐ECHAM5, MIUB, CCCMA_T47, INMCM, CSIRO‐MK3·0, CNRM, CCCMA_T63 and GFDL 2·0 and those with poorer performances are MRI, IPSL, GISS‐AOM, MIROC‐M, NCAR‐PCM1, IAP and NCAR‐CCSM. However, the reduction in the combined score as we move from the best‐ to the worst‐performing GCMs is gradual, and there is no evident cut‐off point or threshold to remove GCMs from climate impact studies. There is some agreement between the results here and many similar studies comparing the performance of GCMs in Australia, but the results are not always consistent and do significantly disagree with several of the studies. Copyright © 2010 John Wiley & Sons, Ltd.     

地表湿度及粗糙度非均匀分布情况下整体输送方法的初步研究

利用一个裸土与Pielke中尺度边界层的耦合模式，对大气环流模式网格尺度的地表湿度和粗糙度的非均匀分布情况下整体输送系数的平均方法进行了初步研究。首先估算了将单点陆面模式应用到大气环流模式的非均匀网格时所产生的误差，并且构造了一种有效阻抗的平均方法，与其他几种方法相比，它可以更有效地消除这种误差。     

全球1.5℃和2.0℃升温下潮白河流域气候和径流量变化预估

潮白河流域为北京主要供水源,其水资源量对北京用水保障至关重要,因此开展该流域在全球1.5℃和2.0℃升温下的径流预估研究具有现实意义。利用1961—2001年WATCH数据对SWAT水文模型进行率定和验证,在此基础上,应用第五次耦合模式比较计划(CMIP5)中5个全球气候模式在典型浓度路径(RCP4.5、RCP6.0和RCP8.5)下预估的全球1.5℃和2.0℃升温下的数据驱动SWAT模型,开展了潮白河流域气温、降水及径流量的变化预估研究,并量化评估由气候模式和RCPs导致的水文效应的不确定性。结果表明：(1) SWAT模型基本能较好地模拟潮白河流域的月径流特征,应用该模型进行气候变化对径流量的影响评估是可行的。(2)在全球1.5℃和2.0℃升温下,潮白河流域年平均温度较基准期(1976—2005年)分别增加1.5℃和2.2℃,年平均降水量也增加4.9%和7.0%。预估的年径流量在全球1.5℃升温下总体略有增加,盛夏和秋初的径流量占全年的比例也有所增加;在全球2.0℃升温下,年径流量增幅达30%以上,但夏季径流量占全年的比例明显减少。(3)在全球2.0℃升温下,潮白河流域极端丰水流量明显增加,洪涝发生风险增大。(4)未来气温、降水量和径流量的预估都存在一定的不确定性,在全球2.0℃升温下不确定性更大;相对而言,径流量的不确定性要远大于降水量的不确定性;无论是全球1.5℃升温下还是2.0℃升温下,预估不确定性主要来源于全球气候模式。     

Climatic analysis of tropopause during the northwestern Indian Ocean tropical cyclones

In this research, tropopause temperature (TT) and tropopause geopotential height (TGH) over the inner-core and environmental regions of all tropical cyclones (TCs) over the northwest of the Indian Ocean (NWIO) from 1990 to 2019 were investigated. To this aim, observational/analysis/reanalysis data and also simulated data from both historical and Representative Concentration Pathway 8.5 (RCP8.5) experiments of some global climate models (GCMs) from the Coupled Model Intercomparision Project (CMIP5) were used. Dynamical and thermo-dynamical environmental factors controlling TC, together with their correlation with different phases of some climatic indices were considered. Results indicated that the eastern part of the NWIO was more favorable for TC genesis and intensification.Lower-level stratospheric (upper-level tropospheric) cooling (warming) was detected over the NWIO during 1990−2019. Over the both inner-core and environmental regions of the NWIO TCs, the coldest tropopause occurred at a CS-Category and the warmest tropopause happened at the first stage of a VSCS event. Over the inner-core (environmental) region, the highest tropopause was detected at the first stage of a CS event (at the end of a VSCS life cycle). A significant majority of the used CMIP5 GCMs produced stratospheric cooling and tropospheric warming trends over the NWIO, similar to those obtained using ERA5 reanalysis dataset. Finally, the decreasing trend of TT over the both inner-core and environmental regions of NWIO TCs together with temperature decreasing trend obtained from the CMIP5 GCMs simulations suggest that the NWIO is prone to experience more TCs, especially the intense ones, in the future.