东亚地区区域气候模拟的研究进展

由于大气环流模式对东亚地区区域气候特征的模拟存在很大不足,采用区域气候模式模拟该地区特殊的季风气候成为目前发展的一个重要研究方向,并取得了显著的研究进展。通过回顾当前东亚地区区域气候模拟的现状,表明大部分区域气候模式都不同程度地模拟出了东亚季风区持续性洪涝现象的大尺度环流特征和演变过程,再现了东亚各主要气候区降水的年际、季节和季节内变化及主要雨带的季节进退和降水的时空演变特征。但是,大部分模式没能很好地模拟出大尺度特征的强度和量值,模拟的温度和降水存在系统性偏差。原因分析表明,进一步完善和改进区域气候模式的物理过程参数化方案及动力框架可以改善模拟效果。最后对区域气候模式未来的发展给出展望。     

Using Statistical Downscaling to Quantify the GCM-Related Uncertainty in Regional Climate Change Scenarios： A Case Study of Swedish Precipitation

There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project （CMIP2） are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.     

Inter-Comparison of 10-year Precipitation Simulated by Several RCMs for Asia

In phase Ⅱ of the Regional Climate Model Inter-comparison Project (RMIP) for Asia, the regional climate has been simulated for July 1988 through December 1998 by five regional climate models and one global variable resolution model. Comparison of the 10-year simulated precipitation with the observations was carried out. The results show that most models have the capacity to reproduce the basic spatial pattern of precipitation for Asia, and the main rainbelt can be reproduced by most models, but there are distinctions in the location and the intensity. Most models overestimate the precipitation over most continental regions. Interannual variability of the precipitation can also be basically simulated, while differences exist between various models and the observations. The biases in the stream field are important reasons behind the simulation errors of the Regional Climate Models (RCMs). The cumulus scheme and land surface process have large influences on the precipitation simulation. Generally, the Grell cumulus scheme produces more precipitation than the Kuo scheme.     

Multi-year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model (RegCM_NCC). Part Ⅰ: Sensitivity Study

A modified version of the NCAR/RegCM2 has been developed at the National Climate Center (NCC), China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP (Institute of Atmospheric Physics) T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year (2001 to 2004) prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process parameterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme (MFS) and Betts-Miller scheme (BM) for convective precipitation, the LPMI (land surface process model I) and LPMII (land surface process model Ⅱ) for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE (turbulent kinetic energy) scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 (RegCM_NCC) has been set up for climate simulations and seasonal predictions.     

Some phenomena of the interaction between vegetation and a atmosphere on multiple scales

This article studies the response of the distribution pattern and the physiological characteristics of the ecosystem to the spontaneous precipitation and the interaction between vegetation and the atmosphere on multiple scales in arid and semi-arid zones, based on measured data of the ecological physiological parameters in the Ordas Plateau of northern China. The results show that the vegetation biomass and the energy use efficiency of photosynthesis are especially sensitive to the annual precipitation; strong and complex interactions exist between the vegetation and the atmosphere on multiple scales leading to supernormal thermal heterogeneity of the underlying surface, the strong vortex movement and turbulence. This study can facilitate understanding of the land surface processes and the influences of global climate change as well as human activities on the human environment in the arid and semi-arid zones. It also aids in improving the parameterization schemes of turbulent fluxes of a heterogeneous underlying surface for land surface processes in climate models.     

关于水资源总量计算的探讨

一个地区的水资源量,相对来说无论是地表水资源还是地下水资源均处于相对动态平衡之中。天然状态下,水资源总量等于地表水径流量与地下水天然排泄量之和,再减去地下水枯月天然排泄量(即地下水恒转化为河川基流量的部分)。     

延庆发展奶牛的气候优势

依据奶牛生物学特性及与气象条件关系,利用延庆地区30年的气候资料,从地理位置、体高、适温条件、不适温条件、温湿指数、相对湿度和日照、风寒指数、饲料条件等多方面,分析论证了延庆在发展奶牛相对于北京平原地区的气候优势.综合分析表明,相对于北京平原地区,延庆气候更适于发展奶牛养殖.     

1月北大西洋东部-乌拉尔山阻塞高压频次年际尺度偶极子模态特征

基于观测和再分析资料,本文研究了近几十年来1月北大西洋东部-乌拉尔山阻塞高压频次年际变异主导模态特征及与其相联的大气背景场。结果表明,1980—2019年冬季(12月—次年2月)该地区阻塞高压频次年际变异的主导模态存在明显月际差异:12月表现为北大西洋东部-欧洲西部地区阻塞高压频次的显著同位相变化,1月为北大西洋东部-欧洲西部与乌拉尔山地区阻塞高压频次的具有显著的反位相变化即偶极子模态,2月则为北大西洋东部-乌拉尔山阻塞高压频次的显著同位相变化。进一步研究表明:1月北大西洋东部-乌拉尔山阻塞高压频次偶极子模态与同期局地纬向西风、纬向风垂直切变、经向位涡梯度等大气背景场异常偶极型变化相联系。当乌拉尔山地区关键大气背景场为负异常,而北大西洋东部-欧洲西部为正异常时,两个地区阻塞高压频次分别增加和减少,呈现偶极子模态;反之亦然。阻塞高压频次偶极子模态及相关的背景环流异常可通过调节水平温度平流、垂直运动和水汽输送等来影响1月欧亚北部气温和降水,以及它们的极端事件频次。当阻塞高压频次偶极子模态处于正位相时,乌拉尔山北部(南部)和欧洲南部增温(降温),极端暖、冷事件频次分别增加(减少)和减少(增加...     

1980—2018年黄河上游气候变化及其对生态植被和径流量的影响

黄河上游是黄河流域最重要的水源涵养地和产流区,对黄河流域的水资源安全、生态环境和粮食安全有决定性的意义。近年来在西北地区气候暖湿化的背景下,黄河上游气候生态水文等问题受到了各方的高度关注。本文利用卫星遥感数据、格点融合数据和水文监测数据,分析了黄河上游气候的多尺度变化特征及其对植被和径流量的影响。结果表明：1）1980-2018年黄河上游暖湿化趋势呈现全区域较一致的气候特征,温度增加率为0.023℃/a,降水增加率为1.09 mm/a,但同时又存在明显的区域差异性,湟水流域至甘肃中部降水增加最显著,宁蒙荒漠地带增温趋势最明显,2000年以来整个黄河上游降水明显增加。2000年后汇流区与流径区的蒸散发明显增加,但源头区南部波动减少。2）当前的暖湿化有利于黄河上游植被生长,1999年以来汇流区和源头区部分区域的植被增加率达到0.04/（10 a）;从长期趋势看,源头区、汇流区植被指数与上年降水呈显著正相关关系,而流径区植被指数与当年降水相关性显著;降水对黄河上游流域植被具有明显的改善作用,而温度对其影响较复杂,各区域不同的植被类型是导致降水、温度、蒸散影响存在差异的可能原因。3）1980-2018年唐乃亥站和兰州站的年径流量均呈减少趋势,但1998年以来两站的年径流量明显增加,兰州站年径流量的增加率是唐乃亥站的近3倍。长期趋势表明,唐乃亥站年径流量与当年降水呈显著正相关关系,兰州站年径流量与当年降水、蒸散的相关系数均明显低于唐乃亥站;从年际波动看,降水是决定年径流量的最主要影响因子,而生态植被、冻土退化、水储量变化及社会活动等因素对径流量的影响也不容忽视。该研究为科学应对黄河上游生态保护及实现黄河流域高质量发展提供了参考依据。     

基于全球及区域气候模式的江苏省降水变化趋势预估

利用气象观测资料,8个全球耦合气候系统模式的集合平均以及区域气候模式(RegCM4)的结果,通过方差分析、相关分析、趋势分析、扰动法等方法对模式性能进行了评估,并对江苏省在未来RCP8.5高端排放情景下降水的变化趋势进行了预估。结果表明,在RCP8.5情景下,至2020、2030和2050年,全球模式模拟的江苏省年平均降水在未来有逐渐增加的趋势,线性增加率约为7 mm/(10 a)。至2050年,江苏省年平均降水量将增加2%左右;区域模式模拟的年平均降水在未来线性增加率为1.5 mm/(10 a),变化不显著。区域模式模拟的夏季降水在未来有所增加,最多可增加20%～30%,但增幅随时间逐渐减小;全球模式模拟的夏季降水比现在有所减少,至2050年,减少了大约10%。区域模式模拟的冬季降水在未来不同时间段均比现在有所减少,同现在相比,最多可减少30%～40%;而全球模式模拟的冬季降水在未来则是先减少,后增加,至2050年,比现在大约增加10%。对于不同季节,总体而言,南部地区降水量的变化较北部地区显著。对于极端降水事件来说,江苏省未来小雨日数将减少,而暴雨日数则微弱增加。但由于全球模式本身的性能、区域模式对全球模式的依赖性以及温室气体排放的不确定性使上述预估结果仍具有不确定性。