秋季层状云中高值过冷水区的微物理特征

利用１１架次的机载“ＰＭＳ”资料,分析了山东秋季层状云中高值（大于０．１ｇ·ｍ~(－３)）过冷水区的微物理特征：最大过冷水含量为０．３６１ｇ·ｍ~(－３),８４．０％的过冷水含量在０．１～０．２ｇ·ｍ~(－３)间,过冷水连续出现的宽度８６．１％小于３．０ｋｍ。雪晶形状以霰粒和小雪粒为主。２阶(函数可以很好地拟合云滴尺度谱,质量谱适合用对数正态函数拟合。     

近百年中国、北半球和南半球气温内在结构比较(Ⅱ)

气温序列的变化不仅包含月、季、年、百年等不同的时间尺度,而且具有一定的局域性,全球、南半球、北半球和中国的气温变化各不相同．文中利用子波变换极大值线表征的突变点来构造一维映射动力系统的基本原理,研究中国、北半球和南半球气温的异同,从而映证了气候变化的局域性     

国家气象中心新一代业务中期预报模式T213L31的主要特点

T2 1 3中期数值预报系统于 2 0 0 2年 9月 1日起在国家气象中心正式业务化。作为此系统核心的T2 1 3L31全球模式与原业务模式T1 0 6L1 9相比 ,采用了一些新的数值技术 ,包括半拉格朗日时间积分方案的引入 ,采用规约格点 ,分布内存与共享内存并行相结合 ,从而在目前有限的计算机资源条件下 ,能积分高分辨率的模式。更重要的是 ,模式采用了一些更新、具有更真实物理概念的物理过程参数化方案 ,对于辐射方案、次网格尺度地形参数化、积云对流方案、云方案、陆面过程方案都作了很大改进 ,从而克服了许多T1 0 6L1 9模式中存在的问题 ,明显提高了T2 1 3L31模式的预报技巧。     

广东省夏半年降水敏感区域分析

利用广东省25个台站1980年至2012年4-9月份的降水量资料,采用小波分析、EOF和REOF方法对夏半年降水量的周期振荡、空间异常特征以及时间变化规律进行诊断分析研究。结果表明：广东省夏半年降水总量存在显著的4a、7a和13a周期振荡,且4a周期振荡信号最强,为第一主周期,7a和13a分别为第二、第三主周期。其主要异常模态表现为一致偏少或一致偏多、沿海与内陆反向型。广东省夏半年降水量的异常敏感区域为粤西北区、粤西南区和粤东北区。三个区域近几年夏半年降水量均表现为减少趋势,其中粤东北区降水量减少幅度较大。     

小麦生育关键期对降水的需求

利用驻马店市1981-2007年的气象观测资料、冬小麦生长季内墒情观测资料和作物观测资料,分析了驻马店市冬小麦在不同生育期和不同土壤湿度条件下所需降水量,结果表明:播种期内,土壤重量含水率＞16%(＜6%)时,10月降水量＞15 mm(＞45 mm)即可保证小麦顺利播种和一播全苗;10月土壤重量含水率＞17%(＜10%)时,11月降水量＞10 mm(＞45 mm),可满足越冬需要;正常年份不必浇灌返青水,2月上旬降水量＜5 mm,需浇返青水;拔节-孕穗期,土壤重量含水率13%-15%(＜13%)时,3月下旬至4月上旬降水量＞45 mm(＞70 mm),可保证小麦孕穗需要;开花灌浆期,土壤重量含水率以15%-20%为宜,降水不宜＞25 mm.     

汉江流域极端水文事件时空分布特征

利用1960-2012年汉江流域15个气象站点的日降雨资料和3个水文站同时期日径流资料,分析了9个极端降雨指数的空间分布规律,运用广义极值分布（GEV）、Gamma分布两种极值统计模型对各站点的最大1 d降雨、最大3 d降雨极值样本进行拟合,遴选描述降雨极值分布规律最优概率模型,进而推算给定重现期下的降雨设计值,并分析其空间分布规律;选用Gumbel、Clayton和Frank这3种Copula函数建立降雨-洪量极值联合分布模型,优选最合适的Copula函数,由此计算给定重现期下的洪量设计值。结果表明：GEV分布模型能更好地模拟降雨极值序列,不同重现期下的降雨极值在空间上均呈西低东高的特征;3种Copula函数中,Frank Copula函数能更好地拟合降雨-洪量相关关系,由此推求的洪量设计值大于单变量拟合设计值。     

Advances in understanding the “Perfect Monsoon-influenced Typhoon”: Summary from International Conference on Typhoon Morakot (2009)

Typhoon Morakot (2009) produced 2855 mm of rain and was the deadliest typhoon to impact Taiwan with 619 deaths and 76 missing persons, including a landslide that wiped out an entire village. While Morakot did not exceed the heaviest 24-h rain record, the combination of heavy rain and long duration that led to the record accumulation is attributed to the southwest summer monsoon influence on the typhoon. Thus, a special combination of factors was involved in the Morakot disaster: (i) Strong southwesterly monsoon winds; (ii) Convergence between the typhoon circulation and monsoon flow to form an east-west oriented convective band over the Taiwan Strait that was quasi-stationary and long-lasting; (iii) A typhoon in a specific location relative to the Central Mountain Range and moving slowly; and (iv) Steep topography that provided rapid lifting of the moist air stream. The contributions of each of these four factors in leading to the Morakot disaster are reviewed primarily based on new research presented at the International Conference on Typhoon Morakot (2009). Historical data sets, new Doppler radar observations, and numerical modeling have advanced the understanding of the special conditions of monsoon-influenced typhoons such as Morakot. This research is also leading to modifications of existing and development of new forecasting tools. Gaps in scientific understanding, limits to the predictability, and requirements for advanced forecast guidance tools are described that are challenges to improved warnings of these extreme precipitation and flooding events in monsoon-influenced typhoons.     

长江上游流域秋季连阴雨时空变化特征

利用长江上游259个气象站逐日降水资料,采用线性趋势分析方法,分析了近1961—2012年来长江上游流域秋季连阴雨的时空变化特征。结果表明,长江上游流域秋季连阴雨过程平均出现1.54次/a,其中9月出现次数最多,10月次之,11月出现较少。秋季连阴雨日数、累积降水量分别以2.3 d/(10 a)、13.7 mm/(10 a)的速率显著减少,连阴雨开始和结束日期平均为9月9日和9月30日均表现出推迟趋势。进入21世纪后,5—9 d、10 d以上连阴雨过程的次数、80.0 mm以上连阴雨过程的次数均表现出减少趋势。金沙江下游和四川盆地东部为秋季连阴雨累计雨量及其变化速率的大值中心,四川盆地西南部为连阴雨日数及其变化速率的大值中心。9月的降水中心、雨日分布情况与秋季总体情况基本一致,10月降水中心、阴雨日数的中心出现了明显东撤,11月东撤更为明显。     

闽东干旱概况及夏季人工增雨作业天气形势分析

对闽东干旱的成因和干旱的环流形势进行了探讨,着重分析了夏旱期间人工增雨作业的天气形势以及不同形势、不同云型下的降水情况。结果表明:闽东干旱的形成与大型环流形势、地理因素、土壤植被等有关,平均而言,沿海干旱明显多于内陆山区;夏季发生干旱的机率最大而且强度级别高,西太平洋副热带高压是致旱的主要天气系统;在夏季,台风型(T)、弱流场型(R)是进行人工增雨作业的优势天气型,Cb、Cu、Sc云是开展人工增雨作业比较适合的作业云。这些结果为夏旱期间开展人工增雨作业提供了理论依据。     

Vertical tilt structure of East Asian trough and its interannual variation mechanism in boreal winter

Vertical tilt structure of the East Asian trough (EAT) and its interannual variation mechanism in boreal winter are studied using NCEP/NCAR, ERA40, and NCEP/DOE reanalyses. A vertical tilt index (VTI) is defined as the mean slope of vertical trough line on the longitude-height cross section to describe the tilting extent of the EAT, with high index indicating a more west-tilted trough and vice versa. The VTI series derived from the three reanalysis datasets are highly correlated with each other during the corresponding periods. A significant positive correlation is found between the VTI and the zonal range of the vertical trough line. Based on the close relation, a possible physical mechanism is proposed to explain the interannual variation of VTI. It demonstrates that positive (negative) temperature anomalies within the mean zonal range of the EAT result in expansion (contraction) of the zonal range and lead to high (low) VTI years. The composite analyses based on the three reanalysis datasets well support the proposed mechanism. Furthermore, the general relationship between the VTI and the zonal temperature gradient is discussed based on the proposed mechanism. It is revealed that the asymmetric change of temperature gradient on the western and eastern sides of the EAT plays an important role in the variation of VTI, which suggests that the tilting extent of the EAT is strongly affected by the two-order zonal change of temperature instead of the zonal temperature gradient (i.e., one-order change). Climate variability not only in the simultaneous winter but also in the following spring and summer over East Asia is closely related to the variation of the VTI. This study on the vertical tilting of the EAT may enrich knowledge of the East Asian winter monsoon and the climate variability over East Asia and may be helpful in improving the regional climate prediction in East Asia.