2004年夏季经向型雨带及其与印度洋偶极模异常海温的关系

针对2004年夏季降水为南北向雨带分布的异常特点，利用NCEP／NCAR再分析资料对可能造成2004年准经向降水分布的海温场、高度场及水汽输送特征进行了分析，并与夏季降水呈纬向分布的2003年进行了比对。分析结果表明，2004年夏季西太平洋副热带高压偏北、偏东，中国大陆中纬度地区东部为异常偏东水汽输送，西部为异常偏西的水汽输送，东、西风在110°E形成南北向交界，有利于形成南北经向型的水汽辐合和降水分布。而在2003年夏季，西太平洋副热带高压偏南、偏西，在长江以南形成稳定的带状副高，有利于雨带长时间稳定在副高北侧的淮河流域，同时中国大陆35°N以南地区为异常偏西水汽输送，以北地区为异常偏东的水汽输送，正、负异常纬向风形成东西向交界，有利于形成东西纬向型的水汽辐合和带状降水分布。对海温状况的分析发现，虽然2003年和2004年太平洋异常海温信号较弱，但印度洋和中国大陆近海海温却有明显的差异，2004年夏季西北太平洋异常海温北高南低，西印度洋海温异常偏冷，赤道热带印度洋海温呈东暖西冷的偶极模负相位特征。而在2003年淮河强降水发生同期，西北太平洋异常海温南高北低，西印度洋海温异常偏暖，赤道热带印度洋海温呈东冷西暖的偶极模正相位特征。因此，印度洋异常海温偶极模的不同相位可能是造成2003、2004年中国夏季降水不同雨带分布型的重要原因。利用中国160个代表站1950-1999的降水资料，进一步分析了印度洋偶极模不同相位异常海温对中国夏季降水的影响，结果发现，印度洋偶极模正相位有利于中国南方降水的西移和北方降水的东进，趋向于形成东西纬向型降水分布；而印度洋偶极模负相位有利于中国南方降水的东退和北方降水的西移，趋向于形成南北经向型降水分布。

南印度洋副热带偶极模在ENSO事件中的作用

南印度洋副热带偶极模(Subtropical Dipole Pattern,SDP)是印度洋存在的另一种很明显的偶极型海温差异现象,在年际和年代际尺度上均有十分明显的表现.而目前有关印度洋海气相互作用的研究主要集中在赤道印度洋地区,针对南印度洋地区的工作还比较少,特别是有关南印度洋海温与ENSO(EI Nino-Southern Oscillation)事件关系的研究.本文初步探讨了年际尺度上南印度洋副热带偶极型海温变化差异与ENSO事件的关系,发现SDP与ENSO事件有密切的联系,SDP事件就像连接正负ENSO位相转换的一个中间环节,SDP事件前后期ENSO的位相刚好完全相反.进一步,本文通过分析SDP事件前后期海温、高低层风、低层辐合辐散、高空云量和辐射等的变化特征研究了南印度洋偶极型海温异常在ENSO事件中的作用,结果表明:SDP在ENSO事件中的作用不仅涉及海气相互作用的正负反馈过程,还与热带和副热带大气环流之间的相互作用有关,特别是与东南印度洋海温变化所引起的异常纬向风由赤道印度洋向赤道太平洋传播的过程等有十分直接的关系;同时,SDP对ENSO事件的影响在很大程度上还依赖于大尺度平均气流随季节的变换.

Southern high latitude climate anomalies associated with the Indian Ocean dipole mode

Using a 23-year database consisting of sea level pressure, surface air temperature and sea surface temperature, the authors studied southern high latitude climate anomalies associated with IOD (Indian Ocean Dipole). Correlation analysis of the spatial variability regarding monthly sea level pressure, surface air tempera- ture, and sea surface temperature anomalies with IOD index suggests that IOD signal exists in southern high latitudes. The correlation fields exhibit a wavenumber-3 pattern around the circumpolar Southern Ocean. Lead-lag correlation analysis on the strongest correlation areas with IOD index shows that IOD in the tropical Indian Ocean responses to the southern high latitude climate almost instantaneously. It is proposed in the present paper that this connection is realized through atmospheric propagation rather than through oceanic one.

RELATIONSHIPS BETWEEN AUTUMN INDIAN OCEAN DIPOLE MODE AND THE STRENGTH OF SCS SUMMER MONSOON

Based on 1948 - 2004 monthly Reynolds Sea Surface Temperature （SST） and NCEP/NCAR atmospheric reanalysis data, the relationships between autumn Indian Ocean Dipole Mode （IODM） and the strength of South China Sea （SCS） Summer Monsoon are investigated through the EOF and smooth correlation methods. The results are as the following. （1） There are two dominant modes of autumn SSTA over the tropical Indian Ocean. They are the uniformly signed basin-wide mode （USBM） and Indian Ocean dipole mode （IODM）, respectively. The SSTA associated with USBM are prevailing deeadal to interdecadal variability characterized by a unanimous pattern, while the IODM mainly represents interannual variability of SSTA. （2） When positive （negative） IODM exists over the tropical Indian Ocean during the preceding fall, the SCS summer monsoon will be weak （strong）. The negative correlation between the interannual variability of IODM and that of SCS summer monsoon is significant during the warm phase of long-term trend but insignificant during the cool phase. （3） When the SCS summer monsoon is strong （weak）, the IODM will be in its positive （negative） phase during the following fall season. The positive correlation between the interannual variability of SCS summer monsoon and that of IODM is significant during both the warm and cool phase of the long-term trend, but insignificant during the transition between the two phases.

North Indian Ocean tropical cyclone activities influenced by the Indian Ocean Dipole mode

Using Joint Typhoon Warning Center tropical cyclone(TC)track data over the North Indian Ocean(NIO),National Centers for Environmental Prediction monthly reanalysis wind and outgoing long-wave radiation data,and National Oceanic and Atmospheric Administration sea surface temperature data from 1981 to 2010,spatiotemporal distributions of NIO TC activity and relationships with local sea surface temperature(SST)were studied with statistical diagnosis methods.Results of empirical orthogonal function(EOF)analysis of NIO TC occurrence frequency show that the EOF1 mode,which accounts for 16%of total variance,consistently represents variations of TC occurrence frequency over the whole NIO basin.However,spatial dis- tributions of EOF1 mode are not uniform,mainly indicating variations of westward-moving TCs in the Bay of Bengal.The prevailing TC activity variation mode oscillates significantly on a quasi-5 year interannual time scale.NIO TC activity is notably influenced by the Indian Ocean dipole(IOD)mode.When the Indian Ocean is in a positive(negative)phase of the IOD, NIO SST anomalies are warm in the west(east)and cold in the east(west),which can weaken(strengthen)convection over the Bay of Bengal and eastern Arabian Sea,and cause anticyclonic(cyclonic)atmospheric circulation anomalies at low levels. This results in less(more)TC genesis and reduced(increased)opportunities for TC occurrence in the NIO.In addition,positive(negative)IOD events may strengthen(weaken)westerly steering flow over the Bay of Bengal,which further leads to fewer(more)westward-moving TCs which appear in regions west of 90°E in that bay.

Representation of global precipitation anomalies using four major climate patterns

This study aims at finding the dominant climate patterns that influence the precipitation anomalies for different regions over the world. To this end, a multiple linear regression model is employed to represent the impact of four major climate patterns(El Ni?o-Southern Oscillation(ENSO), Indian Ocean Dipole(IOD), Arctic Oscillation(AO) and Antarctic Oscillation(AAO)) on the global precipitation anomalies. The normalized climate pattern indexes and normalized precipitation anomalies are used in the regression model. For the Northern Hemisphere, the three predictors used are the normalized NINO3.4 index(representing ENSO), normalized DMI(representing IOD) and normalized AO index; for the Southern Hemisphere, also three indexes are used as three predictors, and the normalized AO index is replaced by the normalized AAO index. The influences brought by each climate pattern can be represented by the magnitude of the corresponding regression coefficients, and the dominant climate patterns are those with the largest magnitude. The study results show that the precipitation anomalies in the northern part of South America and the northwestern part of Southeast Asia are mainly influenced by ENSO. The precipitation anomalies in East Africa and the southwestern part of Southeast Asia are mainly influenced by IOD. The precipitation anomalies in Europe and west coast of North America are mainly influenced by AO; the precipitation anomalies in the eastern part and southern part of South America, southern part of Africa, and the northeastern Australia are mainly influenced by AAO. These findings are consistent with the general understanding on the teleconnection features of the four climate patterns. Further, the regression model can be used for predicting precipitation anomalies through use of these major climate patterns.