Integrating downscaled CMIP5 data with a physically based hydrologic model to estimate potential climate change impacts on streamflow processes in a mixed‐use watershed

Climatic changes have altered surface water regimes worldwide, and climate projections suggest that such alterations will continue. To inform management decisions, climate projections must be paired with hydrologic models to develop quantitative estimates of watershed scale water regime changes. Such modeling approaches often involve downscaling climate model outputs, which are generally presented at coarse spatial scales. In this study, Coupled Model Intercomparison Project Phase 5 climate model projections were analyzed to determine models representing severe and conservative climate scenarios for the study watershed. Based on temperature and precipitation projections, output from GFDL‐ESM2G (representative concentration pathway 2.6) and MIROC‐ESM (representative concentration pathway 8.5) were selected to represent conservative (Δ_C) and severe (Δ_S) change scenarios, respectively. Climate data were used as forcing for the soil and water assessment tool to analyze the potential effects of climate change on hydrologic processes in a mixed‐use watershed in central Missouri, USA. Results showed annual streamflow decreases ranging from ?5.9% to ?26.8% and evapotranspiration (ET) increases ranging from +7.2% to +19.4%. During the mid‐21st century, sizeable decreases to summer streamflow were observed under both scenarios, along with large increases of fall, spring, and summer ET under Δ_S. During the late 21st century period, large decreases of summer streamflow under both scenarios, and large increases to spring (Δ_S), fall (Δ_S) and summer (Δ_C) ET were observed. This study demonstrated the sensitivity of a Midwestern watershed to future climatic changes utilizing projections from Coupled Model Intercomparison Project Phase 5 models and presented an approach that used multiple climate model outputs to characterize potential watershed scale climate impacts.     

基于CMIP5的东亚地区降雪量变化特征分析

利用JMA的JRA-55降雪量及CMIP5的6个模式模拟的降雪量资料, 分析了东亚地区降雪量年变化特征及年际变化特征. 结果表明: 东亚地区降雪量在1958-2004年期间具有明显的年际变化特征及区域分布特征; 降雪主要集中在11月至翌年的4月, 这6个月中降雪量占年总降雪量的82%; 年际变化特征呈现出一种波动变化略有增加的趋势, 但是增加的幅度有所不同. 从区域分布特征来看, 东亚地区降雪主要分布在东北亚、青藏高原及新疆等3个区域. CMIP5的6个模式对东亚区域及其子区域东北亚、青藏高原、新疆1850-2004年降雪量年际变化特征的模拟差异较大. 多模式集合预报的结果表现为, 在过去155 a(1850-2004年)东亚区域降雪量呈现明显减小趋势, 东北亚和青藏高原降雪量为波动略有减小趋势, 新疆降雪量为明显增加趋势.     

CMIP3模式对未来50a欧亚大陆雪水当量的预估

为研究预估未来50a欧亚大陆雪水当量,基于遥感数据,用误差百分率、空间相关和误差标准差等统计方法,评估了14个CMIP3模式在20C3M的雪水当量产品,诊断各模式对欧亚大陆雪水当量的模拟能力,在此基础上对模拟效果较好的10个模式产品进行多模式集合,分析了A2和B1情景下2002—2060年欧亚大陆雪水当量的变化．结果表...     

基于贝叶斯模型的中国未来气温变化预估及不确定性分析

利用第5次耦合模式比较计划(CMIP5)中35个全球气候模式历史模拟与RCP4.5预估结果,通过贝叶斯模型平均(Bayesian Model Averaging,BMA)对中国气温进行多模式集合研究,给出了中国未来气温变化预估及其不确定性的时空分布。结果表明,中国21世纪冬夏将持续升温,且升温具有冬季高于夏季,北方高于南方的特点。初期(2016—2035年)北方有很大可能(80%)升温超过0.7℃,南方升温相同幅度的概率则超过50%;中期(2046—2065年)北方和南方升温超过1.5℃的概率分别为80%和50%;末期(2081—2100年),北方(南方)有80%(50%)的可能的升温超过2℃。气温预估的不确定性研究发现,无论冬夏,21世纪不同时期升温相对较弱的塔里木盆地、青藏高原南侧和中国东南地区为不确定性低值区,基本低于0.6℃,对应可信度较高,如21世纪初期信噪比超过4;而不确定性的高值区则主要分布在新疆北部、东北平原北部和青藏高原东南侧等升温相对较大的地区,普遍高于1℃,对应可信度较低,如初期信噪比低于2.5。此外,基于信噪比对比发现除青藏高原东部外,其他区域夏季预估的可信度均高于冬季,21世纪末期高于初期,且空间分布特征一致。     

未来50a中国地区冻土面积分布变化

在检验CMIP3模式比较计划中模式在中国地区的温度模拟效果的基础上,选取模拟效果相对较好的HadCM3、EACHE5模拟结果,采用Kudryavtsev方法,应用数字化土壤和植被资料,借助Arc-GIS,对未来50 a中国地区在A2情景下的冻土空间变化趋势进行了模拟计算. 结果表明,在A2情景下,未来50 a中国地区的冻土呈现出退缩趋势,在2050年,多年冻土在青藏高原地区的巴颜喀拉山-唐古拉山之间、冈底斯山地区出现退化,中国的冻土面积较2006年减少约10.7%.     

模式内部变率引起的1.5℃和2℃升温阈值出现时间模拟的不确定性研究

模式内部变率是模拟结果不确定性的重要来源,然而它对于1.5℃和2℃升温阈值出现时间不确定性的影响尚不清楚。因此,基于耦合模式比较计划第五阶段(CMIP5)的多模式数据研究了模式内部变率对1.5℃和2℃升温阈值出现时间不确定性的影响以及对未来排放情景的敏感性。结果表明,模式内部变率对升温阈值出现时间模拟的影响与外强迫的影响相当,单个模式内部不同成员达到全球平均1.5℃或2℃增温的年份相差2~12年;其影响具有明显的空间差异,影响极大值出现在欧亚大陆以北洋面、白令海峡周围区域、北美东北部及其与格陵兰岛之间的海域、南半球高纬地区等;低排放情景下模式内部变率的影响大于高排放情景。     

Simulation of the equatorially asymmetric mode of the Hadley circulation in CMIP5 models

The tropical Hadley circulation (HC) plays an important role in influencing the climate in the tropics and extra-tropics. The realism of the climatological characteristics, spatial structure, and temporal evolution of the long-term variation of the principal mode of the annual mean HC (i.e., the equatorially asymmetric mode, EAM) was examined in model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The results showed that all the models are moderately successful in capturing the HC's climatological features, including the spatial pattern, meridional extent, and intensity, but not the spatial or temporal variation of the EAM. The possible reasons for the poor simulation of the long-term variability of the EAM were explored. None of the models can successfully capture the differences in the warming rate between the tropical Southern Hemisphere (SH) and Northern Hemisphere (NH), which is considered to be an important driver for the variation of the AM. Most of the models produce a faster warming in the NH than in the SH, which is the reverse of the observed trend. This leads to a reversed trend in the meridional gradient between the SH and NH, and contributes to the poor simulation of EAM variability. Thus, this aspect of the models should be improved to provide better simulations of the variability of the HC. This study suggests a possible reason for the poor simulation of the HC, which may be helpful for improving the skill of the CMIP5 models in the future.     

Chinese Contribution to CMIP5：An Overview of Five Chinese Models’Performances

An overview of Chinese contribution to Coupled Model Intercomparison Project-Phase 5 （CMIP5） is presented. The performances of five Chinese Climate/Earth System Models that participated in the CMIP5 pro ject are assessed in the context of climate mean states, seasonal cycle, intraseasonal oscillation, interan-nual variability, interdecadal variability, global monsoon, Asian-Australian monsoon, 20th-century historical climate simulation, climate change pro jection, and climate sensitivity. Both the strengths and weaknesses of the models are evaluated. The models generally show reasonable performances in simulating sea surface tem-perature （SST） mean state, seasonal cycle, spatial patterns of Madden-Julian oscillation （MJO） amplitude and tropical cyclone Genesis Potential Index （GPI）, global monsoon precipitation pattern, El Ni-no-Southern Oscillation （ENSO）, and Pacific Decadal Oscillation （PDO） related SST anomalies. However, the perfor-mances of the models in simulating the time periods, amplitude, and phase locking of ENSO, PDO time periods, GPI magnitude, MJO propagation, magnitude of SST seasonal cycle, northwestern Pacific mon-soon and North American monsoon domains, as well as the skill of large-scale Asian monsoon precipitation need to be improved. The model performances in simulating the time evolution and spatial pattern of the 20th-century global warming and the future change under representative concentration pathways pro jection are compared to the multimodel ensemble of CMIP5 models. The model discrepancies in terms of climate sensitivity are also discussed.     

BCC_CSM对全球海表温度和混合层深度的模拟评估

为了定量评估北京气候中心(BCC)发展的BCC_CSM对当代全球海表温度和混合层深度的模拟能力,以WOA09(World Ocean Atlas 2009)观测资料作为检验模式的气候态实况场,提取包括BCC_CSM在内的CMIP5中的17个海气耦合模式的模拟结果,评估BCC_CSM模拟的全球海表温度和混合层深度的气候平均态并分析造成偏差的可能原因。结果表明:BCC_CSM模拟的海表温度在北半球中高纬的误差较大,而在其余纬度的模拟性能较佳。偏差的产生主要归因于海洋环流偏差。BCC_CSM模拟的最深混合层在北半球中高纬和南半球高纬地区的误差较大,同时这些区域也是多模式模拟差异最大的区域;其模拟的最浅混合层在南半球中高纬的偏差较大。冬季大西洋经向翻转环流的模拟在北大西洋下沉的位置偏南导致北半球高纬地区海表温度偏冷。由此认为包括BCC_CSM在内的许多海气耦合模式需重点改进对南、北半球深对流海域物理过程的描述,以提高气候预测的可信度。