Development of a high resolution runoff routing model, calibration and application to assess runoff from the LMD GCM

Large-scale runoff routing models (RRMs) are important as a validation tool for GCMs, and to close the hydrological cycle in fully-coupled climate models. The model RiTHM was developed to simulate the discharge of large rivers from the total runoff simulated by the LMD GCM. It uses a 1024×800 grid, nested in the 64×50 grid of the LMD GCM. The runoff simulated in a GCM grid cell is uniformly distributed over the underlying cells, where a series of two reservoirs accounts for the delay related to infiltration through the unsaturated zone and aquifers. The resulting riverflow is routed assuming pure translation along the drainage network, extracted with a GIS from a 5 min DEM. The transfer time from a cell to the outlet depends on topography, and on a basin-wide parameter, the time of concentration. RiTHM was calibrated in 11 river basins, using a realistic runoff forcing (computed by the land surface model SECHIBA from reanalyzed meteorological forcing). This led to a very satisfactory reproduction of observed hydrographs. The main problems were related to hydraulic processes neglected in RiTHM (reservoirs, diversion of riverflow because of flooding or irrigation). These results helped to validate SECHIBA, except for its snow processes, shown to be too simple. With the same parameters, RiTHM was also forced with runoff from the LMD GCM. This induced an important degradation of the simulated hydrographs, regarding both volume and timing. It was largely explained by errors in precipitation, and more generally climate, in the GCM. The direct calibration of RiTHM under the GCM-runoff forcing markedly improved the timing of simulated discharge, which could be interesting for land–atmosphere–ocean coupling. This work demonstrated that the usefulness of RRMs for GCMs strongly depends on their adequate calibration.     

古气候数值模拟:进展评述

数值模拟是古气候研究的一个重要内容。过去30年来,古气候数值模拟研究在相当程度上深化了我们对古气候变化机制的理解。在轨道尺度上,数值模拟证明了冰后期气候系统变化主要是对地球轨道参数变化的响应,同时揭示了温室气体、植被、海洋、冰盖等反馈因子的重要性。针对短尺度气候变化,数值模拟揭示出大洋传送带对北大西洋淡水注入的敏感性。在构造尺度上,数值模拟揭示了气候系统对于高原抬升、海道开合、大陆漂移导致的古地理变化、大气CO2浓度变化和太阳常数变化等的响应,揭示了气候系统突变对驱动因子阈值的敏感性。目前,古气候模拟研究中还存在分辨率不高、模拟结果与记录不完全吻合、模拟的边界条件不清楚等诸多问题。今后古气候模拟研究的改进有赖于模式的改进和计算机运算速度的提高,也有赖于对变化机制的更深理解和对边界条件更精确的重建。     

GCM STUDIES ON ANTHROPOGENIC CLIMATE CHANGE IN CHINA*

Impacts of human activities on climate change as simulated by the general circulation models (GCMs)in China for the recent ten years have been summarized and reviewed in this paper.The researches show that it might be getting warmer over China due to the greenhouse effects.The atmospheric circulation and precipitation also might be changed due to the greenhouse effects.The assessments and evaluations of the models over the globe and China have also been presented in this paper.     

Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.     

统计降尺度方法和Delta方法建立黄河源区气候情景的比较分析

大气环流模型(GCMs)预测的气候变化情景,必须经降尺度处理得出小尺度上未来气候变化的时空分布资料,才能满足气候变化对资源、环境和社会经济等影响进行评估的需要.文中研究同时应用Delta方法和统计降尺度(SDS)方法对黄河源区的日降水量和日最高、最低气温进行降尺度处理,建立起未来3个时期(2006-2035、2036-2065和2066-2095 年,简记为2020s、2050s和2080s)的气候变化情景,并比较分析两种方法的优缺点和适用性.结果表明,未来降水量有一定的增加趋势,但是增幅不大,而日最高、最低气温存在明显的上升趋势,且增幅较大.与基准期相比,Delta方法模拟的未来3个时期降水量将分别增加8.75%、19.70%和18.49%;日最高气温将分别升高1.41、2.42和3.44℃,同时,日最低气温将分别升高1.49、2.68和3.76℃,未来极值气温变幅减小.SDS法借助站点实测数据和NCEP再分析资料建立GCM强迫条件下的降尺度模型,模拟结果表明,未来3个时期降水量将分别增加3.47%、6.42%和8.67%,季节变化明显;气温随时间推移增幅明显,未来3个时期的日最高气温将分别升高1.34、2.60和3.90℃,最低气温增幅相对较小,3个时期将分别升高0.87、1.49和2.27℃,由此模拟的未来时期无霜期将延长.在降尺度方法的应用上,SDS方法存在明显的优势,但同时也存在不可避免的缺陷.因此,在实际的气候变化影响评估中,需要多种方法综合比较,以期为决策部门提供参考和依据.     

气候变化对沅江流域径流影响研究

温室气体排放量增加造成气候变化,对全球资源环境产生重要影响.本文在水量平衡基础上,建立考虑气象要素和地形变化的月水文模型,利用实测径流资料对模型在时空尺度上进行验证.利用全球气候模型(GCMs)预测的未来气候变化情形,对处于湿润区的沅江流域径流过程进行预测.分析结果表明,该区域径流过程对降雨和气温变化十分敏感.根据英国Hadcm2模型对本世纪中叶气候变化预测结果,沅江流域未来年降雨量减少0.43%气温升高1.55℃,丰水期降雨增加,而枯水期将有较大幅度减少.年径流量相应减少6.8%,丰水期径流量增大11%,枯水期径流减少47%,不利于防洪和水资源开发利用.     

IPCC AR5 全球气候模式模拟的中国地区日平均降水精度评价

本文利用中国区域660个站点逐日地面降水资料,评估了由IPCC（the Intergovernmental Panel on Climate Change）数据中心于2014年最新发布的15个全球气候模式（Global Climate Models, GCMs）以及多模式集合（Multi-Model Ensemble, MME）对中国降水的模拟精度。首先,从全球范围数据集中读取研究区范围内的GCMs降水模拟数据;然后,提取各个气象站点处的GCMs模拟值;其次,将GCMs在同一站点的模拟值取平均,得到MME模拟值;最后,以气象站点实际观测值为基准,对GCMs的模拟值精度进行评估。研究结果表明：IPCC AR5 GCMs 1996-2005年平均日降水模拟值偏差在中国地区的空间分布均呈现出西北向东南逐渐减小的特征,东部地区平均相对误差较小,平均相对误差较大的点主要分布在西部,但均方根误差呈现出从西北向东南增加的趋势;MRI-CGCM3有82.3%的日平均降水模拟值偏差都比较小,偏差介于-0.5到0.5之间;对于中国地区1996-2005年平均日降水量,BNU和MIROC-ESM模拟精度最低;MME模式模拟值的相关系数>0.5、平均相对误差<0.5和均方根误差<4 mm的百分率均为最高,分别达到64.8%、25.8%和86.4%,偏差介于-0.5到0.5之间的比例为56.7%,说明MME对中国地区日平均降水的模拟精度优于大部分模式,MME模式可在一定程度上减少单个模式未来情景模拟的不确定性。     

百分位统计降尺度方法及在GCMs日降水订正中的应用

在格点观测的逐日降水量数据基础上,采用百分位统计降尺度方法对全球气候模式(GCM)输出的日降水量进行了订正处理。5种订正方案的比较结果表明,取12个百分位数进行日降水量订正是合理的。观测资料与3个GCMs订正前后全国平均年、季降水量空间分布以及主要流域平均年、月和日降水序列多年平均、变化趋势及概率密度的对比分析表明:(1)统计降尺度处理可在一定程度上降低GCMs模拟的降水量偏差,特别是中国中部、长江以南和东北部分地区,对德国马普研究所的海气耦合模式(MPI/ECHAM5)模拟的降水量订正效果最显著;(2)GCMs统计降尺度处理的降水量季节分布特征与观测更为接近,所有流域MPI/ECHAM5订正的降水量优于或接近直接输出结果;(3)与GCM直接输出的降水相比,部分流域经统计降尺度处理后降水量变化趋势与观测的一致性有所增加,但不明显;(4)当日降水量<30mm时,订正的降水量与观测的偏差明显减小;当日降水量>30mm时,部分流域由负偏差转为正偏差。由于GCMs结构和降尺度方法的局限性,在用于具体流域未来气候变化预估及气候变化影响评估时,应选择尽可能多的、模拟能力强的GCMs数据,以包含尽可能多的模拟气候情景。     

2011—2050年长江流域气候变化预估问题的探讨

利用长江流域1961—2008年观测气象资料,对IPCC 第四次评估报告中12个全球气候模式及所有模式集合平均进行比较验证,结果表明：MIUB_ECHO_G模式对该地区降水模拟能力较强,NCAR_CCSM3模式对温度模拟效果较好。进一步利用MIUB_ECHO_G模式和NCAR_CCSM3模式结果在SRES-A2、-A1B、-B1 3种排放情景下的降水和温度数据,分析2011—2050年3种排放情景下长江流域降水和温度变化特征。结果表明,2011—2050年长江流域降水变化趋势不明显,温度呈增加趋势,增幅在2℃内。     

大气环流模式在松花江流域的适用性评价

不同GCMs的输出变量在区域上的表现差异较大。以11个统计特征量为基础,构建了基于秩评分的评价方法,分别对比分析了21个GCMs的17个输出变量在松花江流域与ERA-40再分析资料的吻合程度,以秩评分进行了定量评价。结果显示:不同GCMs对高空气象变量的模拟表现与地面气候要素的模拟表现并不一致,IPSL:CM4、GISS:ER、HadCM3和CSIRO:MK30在松花江流域高空气象变量模拟方面表现相对较好,而CSIRO:MK30、CGCM3.1_T63、GFDL:CM21和BCCR:BCM20在地面气候要素的模拟方面表现相对较好。综合评分结果显示,IPSL:CM4、CSIRO:MK30、GISS:ER和BCCR:CM20在松花江流域的综合表现相对较好。