20世纪中国气候变化研究

Studies on the 20th century climate change in China have revealed that under the background of global warming over the past century,climate in China has also experienced significant change with mean annual temperature increased by about 0.5 °C.More reliable results for the latter part of the 20th century indicate that the largest warming occurred in Northwest China,North China and Northeast China,and the warming in winter is most significant.Although no obvious increase or decrease trends were detected for mean precipitation over China in the past half century,regional differences are very distinct.In the middle and lower reaches of the Yangtze River,precipitation increased,while that in the Yellow River Basin markedly decreased.Studies suggest that climate change in China seems to be related not only with the internal factors such as ENSO,PDO,and the others,but also with the anthropogenic effects such as greenhouse gas emissions,and land use.The future climate change studies in China seem to be important in narrowing understanding the nature of China's climate change and its main causes,since it is significant for projection and for impact assessment of climate change in the future.     

森林火险气象指数及其构建方法回顾

森林火灾是威胁地球生态的主要灾害之一。为实现对林区起火可能性大小、火灾强度、火灾蔓延速度以及火灾扑救难易程度进行评估和预测，国内外专家学者利用森林火灾与气象条件之间的关系研制了诸多森林火险气象指数的构建方法。作者对近几十年来国内外森林火险气象指数的研究工作进行回顾和总结，得出广泛应用的火险指数可以归纳为指数查对法、综合指标法和统计回归法等3种类型，究其原理和使用效果，各有优缺点。在实际使用过程中，需要结合我国的气候和环境特点进行适用性修正和完善。     

IPCC第六次气候变化评估中的气候约束预估方法

得益于第五次评估报告（AR5）以来约束预估研究的迅速发展,观测约束成为政府间气候变化专门委员会（IPCC）第一工作组（WGI）第六次评估报告（AR6）提升对未来预估约束的证据链中的重要一环。IPCC第一工作组第六次评估报告首次利用包括根据历史模拟温度升高幅度得到的观测约束、多模式预估以及第六次评估报告中更新的气候敏感度在内的多条证据链来约束全球地表温度未来变化的预估,减小了多模式预估的不确定性。文中回顾并介绍了IPCC第一工作组第六次评估报告中涉及的几种主要观测约束方法（多模式加权方法、基于归因结论的约束方法（ASK方法）、萌现约束方法）及其应用情况。在IPCC第一工作组第六次评估报告以及很多针对不同区域不同变量的预估研究中,观测约束方法均显示出了订正模式误差、改善模式预估的潜力。相比而言,目前中国在观测约束预估方面的研究还不多,亟待加强观测约束方法研究以及在中国区域气候变化预估中的应用,为中国应对气候变化的政策制定和适应规划提供更丰富、不确定性更小的未来气候信息。      

A comprehensive classification of anomalous circulation patterns responsible for persistent precipitation extremes in South China

Based on observational precipitation at 63 stations in South China and NCEP NCAR reanalysis data during 1951 2010,a cluster analysis is performed to classify large-scale circulation patterns responsible for persistent precipitation extremes(PPEs) that are independent of the influence of tropical cyclones(TCs).Conceptual schematics depicting configurations among planetary-scale systems at different levels are established for each type.The PPEs free from TCs account for 38.6%of total events,and they tend to occur during April August and October,with the highest frequency observed in June.Corresponding circulation patterns during June August can be mainly categorized into two types,i.e.,summer-Ⅰ type and summer-Ⅱtype.In summer-Ⅰ type,the South Asian high takes the form of a zonal-belt type.The axis of upstream westerly jets is northwest-oriented.At the middle level,the westerly jets at midlatitudes extend zonally.Along the southern edge of the westerly jet,synoptic eddies steer cold air to penetrate southward;the Bay of Bengal(BOB) trough is located to the north;a shallow trough resides over coastal areas of western South China;and an intensified western Pacific subtropical high(WPSH) extends westward.The anomalous moisture is mainly contributed by horizontal advection via southwesterlies around 20°N and southeasterlies from the southern flange of the WPSH.Moisture convergence maximizes in coastal regions of eastern South China,which is the very place recording extreme precipitation.In summer-Ⅱ type,the South Asian high behaves as a western-center type.The BOB trough is much deeper,accompanied by a cyclone to its north;and a lower-level trough appears in northwestern parts of South China.Different to summer-Ⅰ type,moisture transport via southwesterlies is mostly responsible for the anomalous moisture in this type.The moisture convergence zones cover Guangdong,Guangxi,and Hainan,matching well with the areas of flooding.It is these set combinations among different systems at different levels that trigger PPEs in South China.     

“75·8”持续性强降水事件及其大尺度水汽输送特征

首先研究了河南"75·8"强降水事件的极端异常特征,然后从水汽通量的角度定性分析这次事件的水汽输送特征,最后采用了Hysplit模型定量分析了不同源地的水汽来源对河南"75·8"强降水的贡献率。研究表明,1975年8月5-8日在河南省发生的是一次大范围持续性极端降水过程,事件发生期间区域平均降水程度超过其气候平均值3倍标准差。强降水事件是在中高纬度环流异常和台风共同作用下发生的,贝加尔湖以东阻塞高压和副热带高压合并阻挡了7503号台风北上。定量计算结果进一步表明,河南"75·8"强降水的水汽来源与7503号台风具有十分密切的联系。     

中国1961—2016年夏季持续和非持续性极端降水的变化特征

基于国家气象信息中心提供的1961—2016年2400多站逐日降水观测资料,根据百分位法确定极端降水,对中国夏季持续（持续2 d及以上）和非持续性（持续1 d）极端降水事件的变化特征进行了研究。结果表明：在气候变暖背景下,以江淮流域为代表,中国大部分地区极端降水量趋于增多,但华北、西南及西部部分地区趋于减少;除内蒙古中部、四川等地以外,中国大部极端降水对总降水的贡献呈增多趋势。进一步对华北、江淮、华南、西南4个代表区域进行分析,发现华北、西南地区的持续和非持续性极端降水量都呈减少趋势,持续性极端降水量的减少更突出,极端降水更多以非持续性形式出现;江淮、华南一带,两类极端降水量都呈增多趋势,持续性极端降水量的增加更明显,极端降水更多以持续性形式出现。     

长江流域旱涝典型年大气水汽输送

利用我国125个探空站一日两次自地面至100hpa共11个层次上的观测资料,对长江流域典型夏涝年(1980年)和夏旱年(1985年)我国大气中水汽总输送场、涡动输送场及散度场进行了计算分析。结果表明:当水汽总输送场从西北、西南和东南三支气流携带的水汽交汇于长江流域,且整个水汽输送场稳定持久,则在水汽辐合带附近导致大量降水,形成洪涝;反之,当三支气流微弱不稳定,不能形成水汽辐合带条件,则形成干旱。涡动输送亦反映出类似的特征。稳定且强盛的西南气流水汽输送是形成降水的主要条件和原因。     

厄尔尼诺对长江中下游地区夏季持续性降水结构的影响及其可能机理

根据中国国家气象信息中心提供的1961-2016年2400多站的逐日降水观测数据,分析了厄尔尼诺对长江中下游地区夏季持续性降水结构的影响。发现长江中下游地区的降水主要以5 d及以内的降水事件为主,其强度主要分布在4-24 mm/d;5 d以上降水所占比例相对较小,而其强度主要分布在12-24 mm/d。其中,长江中下游地区夏季大于5 d的降水事件（长持续性降水事件）所占比例和强度在长江以南地区要大于长江以北地区。同时,在厄尔尼诺的影响下,长江以南地区的降水结构从2-5 d持续性降水事件（短持续性降水事件）和1 d的降水事件（非持续性降水事件）向长持续性降水事件转变,且其强度增加。而长江以北地区,以湖北为主,降水结构存在从非持续性向短持续性降水事件转变的现象,短持续性降水事件的强度也略有增强。因此,厄尔尼诺使得长江中下游地区的降水事件更多地以持续性降水为主,不同持续性降水事件的强度加强。进一步分析发现厄尔尼诺次年西太平洋副热带高压西伸加强,与其相关的东南季风所输送的水汽也有所加强。同时,中高纬度阻塞高压环流形势稳定维持。受这些因子的共同作用,最终导致长江中下游地区夏季降水持续性延长和降水强度加强。而这将给长江中下游地区的农作物种植和经济发展等带来较严重的影响,使防洪、防涝工作面临严峻的挑战。      

A GENERALIZED CANONICAL MIXED REGRESSION MODEL FOR ENSO PREDICTION WITH ITS EXPELMENT

A scheme is proposed for predicting NINO-region SST in terms of a generalized canonical mixedregression model based on principal component canonical correlation analysis(PC-CCA). and into the scheme are introduced such techniques as EEOF, PRESS criterion and consensus prediction. By optimizing physicalfactors and selecting optimal model parameters, experiments were made successful in predicting the LINO SST index for 1 to 4 seasons to follow. The scheme is shown to be stable in operation and its total technical level compares well with that of the model published in NOAA/NWS/NCEP CPC Climate Diagnostics Bulletin. butthe number of factors needed in our scheme is much fewer than that for the CPC's model in dealing with the sameproblems. This makes it possible to establish an operational ENSO monitoring system in China.