青藏高原区域性积雪增量序列及其变化特征

利用青藏高原83个气象台站的逐日积雪观测资料,充分考虑每次降雪过程所引起的积雪变化,建立了该地区1960-2007年度的区域性积雪增量序列,并讨论了其长期变化特征.结果表明:(1)积雪增量序列具有其他积雪参数指标的代表性,又较其他积雪参数指标序列有明显的统计学优点.(2)在48个年度里,1960-1966年度青藏高原区域性积雪增量处于负位相,1967-1998年度为多雪的正位相,1999-2007年度又为少雪的负位相,其中1998年度是个具有显著性的突变点.     

由地基微波辐射计测量得到的北京地区水汽特性的初步分析

首先对比分析了三种测量水汽技术(地基微波辐射计、探空、GPS)之间的差异, 得到地基微波辐射计与探空的差值为0.281cm, GPS与探空的差值为0.728 cm, 地基微波辐射计与GPS的差值为0.322 cm。接着就地基12通道微波辐射计测量得到的水汽总量 (简称PWV), 分析了北京地区水汽在四个季节中的日变化特征。秋季日变化差为0.162 cm, 冬季日变化差为0.130 cm, 春季日变化差为0.229 cm, 夏季日变化差为0.276 cm。另外, 北京地区四个季节中水汽最大值/最小值出现频率最高的时间段呈现一定的特征。即四个季节中在北京时间00:00到00:59和23:00到23:59这两个时间段中, 水汽出现最大值/最小值的概率较其他时间段都高, 其中冬季在北京时间10:00到10:59之间出现最小值的概率最高。水汽总量PWV每小时变化率在四个季节中都存在这样的现象: 出现正的水汽总量PWV每小时变化率的百分比与出现负的水汽总量PWV每小时变化率的百分比相当, 几乎都为50%。最后就水汽与温度相关性做了分析, 分别得到四个季节中各个小时水汽与温度的相关系数, 结果显示各个小时水汽与温度的相关性在四个季节中, 除了夏季从北京时间09:00到22:00为负相关外, 其他时间段内都为正相关。而且各个小时水汽与温度的相关系数都按照秋、春、 冬、夏的顺序递减。     

121 a 梅雨序列及其时变特征分析

对2001--2005年长江中下游梅雨期进行了划分。确定的梅雨参数包括梅雨集中期、梅雨长度、梅雨量、梅雨强度、入梅日期和出梅日期等。然后对1885--2005年共121a的长江中下游5站逐年的梅雨参数进行时间演变分析。从各梅雨参数趋势变化上可估计,在未来10a里,梅雨量仍将偏多,梅雨长度将偏长,入梅日期将偏早,出梅日期也将偏早。对梅雨参数进行Morlet小波分析得出,从1980s开始,入梅日期和出梅日期都出现明显的2～3a和6a的年际振荡周期;入梅日期还出现明显的12a左右的年代周期,出梅日期出现了16a左右的年代际周期。进入1990s后,梅雨长度出现了8a的年际周期,梅雨量则出现明显的4a和8a的年际周期以及一个近16a的年代际周期。     

气候因素变化对许昌烟区的影响及适应性分析

分析了许昌烟区1971—2005年4个年代气候因素变化特点,采用隶属度函数模型和指数和法,估算了许昌各县（市）的气候适生性指数（CFI）,并对其变化原因进行了分析。结果表明：不同年代各县（市）的CFI均在0．80以上,表明各县（市）均属烤烟生产气候适宜区。从4个年代CFI的均值来看,许昌县〉长葛〉襄城〉禹州〉鄢陵;从4个年代CFI变异程度来看,禹州〉长葛〉襄城〉鄢陵〉许昌县。各县（市）不同年代的CFI均呈“低-高-高-低”变化趋势;20世纪80年代以来,许昌县、襄城、长葛、禹州的CFI值及变化趋势基本一致,均明显高于鄢陵。80年代至21世纪初鄢陵的气候适生性指数明显低于其他县（市）,与伸根期温度相对较低,旺长期和成熟期多雨、高湿有关。     

Development Processes of the Tropical Pacific Meridional Mode

Mechanisms for the spatio-temporal development of the Tropical Pacific Meridional Mode(TPMM) are investigated using a coupled ocean-atmosphere model and observations.In both observations and the model,this meridional mode displays decadal variations and is most pronounced in spring and early summer.The model simulation suggests that once SST anomalies in the subtropical northeastern Pacific are initiated,say by northeasterly trade wind variability,perturbations evolve into a merdional dipole in 2-3 months.A...     

湖北地区云地闪电时空分布特征分析

为揭示湖北地区云地闪电时空分布特征及雷电活动规律,以满足雷电灾害防护和雷击风险评估工作需要,采用湖北不同地理位置的13个雷击探测仪组成的闪电监测定位系统获取的2006年3月至2009年2月的云地闪电资料,从闪电的极性分布、日变化、月变化、强度、闪电密度、累计概率分布等方面进行统计分析。结果表明:云地闪电中负闪电占闪电总数的96.2%;正闪电占闪电总数的3.8%;闪电频次的日变化呈明显的单峰单谷型,一日中,最大值出现在15—16时,最小值在09—10时;一年中,4—8月闪电次数占全年闪电总数的95.9%,其中7—8月闪电次数最多;正、负闪电的强度主要集中在10～50 kA,大于30 kA的累积概率在50%以下,大于60 kA的累积概率8.1%,大于100 kA的累积概率1.6%;拟合出湖北地区大于某雷电流强度累积概率方程,经统计分析,实测值与计算值相关系数达0.99998。闪电密度分布呈明显的地域性差异,鄂东南的嘉鱼县、咸宁、黄石、鄂州市一带为闪电高密度区,鄂西的远安县、当阳市附近为闪电次高密度区。山区与丘陵、平原交接地带,即地表状况发生明显变化的地带,是雷电多发地带。鄂西南山区县市雷电日数较多,闪电密度不一定随之增加,其原因可能是山区县市土壤电阻率较大和山区局地小气候环境共同影响的结果。     

近48a台北市气温的小波分析

利用Morlet小波分析了1961—2008年台北市年平均气温序列的小波变化特征,揭示了气温变化的多时间尺度结构,结果表明:台北市年平均气温存在多时间尺度的周期变化特征,有3个明显的特征时间尺度,分别是4 a、6-8 a和14-16 a;除14-16 a的时间尺度在整个研究时段都很明显外,其他尺度的周期阶段性都较强;以14-16 a的特征时间尺度为主周期;台北市的气温变化还表现出突变的特点;近48 a来,台北市年平均气温的气候倾向率为0.3℃/10 a,气温升高的趋势十分明显;未来2年气温在总趋势上升的前提下将处在一个偏冷期。     

Summertime atmospheric teleconnection pattern associated with a warming over the eastern Tibetan Plateau

By using a surface air temperature index (SATI) averaged over the eastern Tibetan Plateau (TP), investigation is conducted on the short-term climate variation associated with the interannual air warming (or cooling) over the TP in each summer month. Evidence suggests that the SATI is associated with a consistent teleconnection pattern extending from the TP to central-western Asia and southeastern Europe. Associated rainfall changes include, for a warming case, a drought in northern India in May and June, and a stronger mei-yu front in June. The latter is due to an intensified upper-level northeasterly in eastern China and a wetter and warmer condition over the eastern TP. In the East Asian regions, the time-space distributions of the correlation patterns between SATI and rainfall are more complex and exhibit large differences from month to month. Some studies have revealed a close relationship between the anomalous heating over the TP and the rainfall anomaly along the Yangtze River valley appearing in the summer on a seasonal mean time-scale, whereas in the present study, this relationship only appears in June and the signal's significance becomes weaker after the long-term trend in the data was excluded. Close correlations between SATI and the convection activity and SST also occur in the western Pacific in July and August: A zonally-elongated warm tone in the SST in the northwestern Pacific seems to be a passive response of the associated circulation related to a warm SATI. The SATI-associated teleconnection pattern provides a scenario consistently linking the broad summer rainfall anomalies in Europe, central-western Asia, India, and East Asia.     

Eurasian Snow Cover Variability and Its Association with Summer Rainfall in China

This study investigates the statistical linkage between summer rainfall in China and the preceding spring Eurasian snow water equivalent (SWE), using the datasets of summer rainfall observations from 513 stations, satellite-observed snow water equivalent, and atmospheric circulation variables in the NCEP/NCAR re-analysis during the period from 1979 to 2004. The first two coupled modes are identified by using the singular value decomposition (SVD) method. The leading SVD mode of the spring SWE variability shows a coherent negative anomaly in most of Eurasia with the opposite anomaly in some small areas of the Tibetan Plateau and East Asia. The mode displays strong interannual variability, superposed on an interdecadal variation that occurred in the late 1980s, with persistent negative phases in 1979--1987 and frequent positive phases afterwards. When the leading mode is in its positive phase, it corresponds to less SWE in spring throughout most of Eurasia. Meanwhile, excessive SWE in some small areas of the Tibetan Plateau and East Asia, summer rainfall in South and Southeast China tends to be increased, whereas it would be decreased in the up-reaches of the Yellow River. In recent two decades, the decreased spring SWE in Eurasia may be one of reasons for severe droughts in North and Northeast China and much more significant rainfall events in South and Southeast China. The second SVD mode of the spring SWE variability shows opposite spatial variations in western and eastern Eurasia, while most of the Tibetan Plateau and East Asia are in phase. This mode significantly correlates with the succeeding summer rainfall in North and Northeast China, that is, less spring SWE in western Eurasia and excessive SWE in eastern Eurasia and the Tibetan Plateau tend to be associated with decreased summer rainfall in North and Northeast China.     

Global and Regional Impacts of Vegetation on the Hydrological Cycle and Energy Budget as Represented by the Community Atmosphere Model （CAM3）

The effects of vegetation and its seasonal variation on energy and the hydrological cycle were examined using a state-of-the-art Community Atmosphere Model （CAM3）. Three 15-year numerical experiments were completed： the first with realistic vegetation characteristics varying monthly （VEG run）, the second without vegetation over land （NOVEG run）, and the third with the vegetation characteristics held at their annual mean values （VEGMEAN run）. In these models, the hydrological cycle and land surface energy budget were widely affected by vegetation. Globaland annual-mean evapotranspiration significantly increased compared with the NOVEG by 11.8% in the VEG run run, while runoff decreased by 13.2% when the realistic vegetation is incorporated. Vegetation plays different roles in different regions. In tropical Asia, vegetation-induced cooling of the land surface plays a crucial role in decreasing tropical precipitation. In middle latitudes and the Amazon region, however, the vegetation-induced increase of evapotranspiration plays a more important role in increasing precipitation. The seasonal variation of vegetation also shows clear influences on the hydrological cycle and energy budget. In the boreal mid-high latitudes where vegetation shows a strong seasonal cycle, evapotranspiration and precipitation are higher in the summer in the VEG run than in the VEGMEAN run.