1750-2010年强火山喷发事件的时空分布特征(英文)

Using the dataset provided by the Smithsonian Institution's Global Volcanism Program, we have extracted the large volcanic eruptions(volcanic explosivity index ≥ 4) from the period 1750–2010 and have then analyzed the main characteristics of large volcanic eruptions since 1750 according to their geographic latitudes, their elevations, and the years and months in which they occurred. The results show that most large volcanic eruptions were located around the margins of the Pacific Ocean and the islands of Sumatra and Java, especially in the equatorial regions(10°N–10°S). Large volcanic eruptions were concentrated at 1000–2000 m elevations and in the months of January and April. There were more eruptions in the summer half-year(from April to September) than in the winter half-year(from October to the next March). Large volcanic eruptions have interdecadal fluctuations, including cycles of 15–25 years and 35–50 years, which were detected by Morlet wavelet analysis, with the fluctuations being more frequent after 1870 than before. During the periods 1750–1760, 1776–1795, 1811–1830, 1871–1890, 1911–1920 and 1981–1995, there were relatively many large volcanic eruptions.     

Spatial and temporal distribution of large volcanic eruptions from 1750 to 2010

Using the dataset provided by the Smithsonian Institution＇s Global Volcanism Program, we have extracted the large volcanic eruptions（volcanic explosivity index ≥ 4） from the period 1750–2010 and have then analyzed the main characteristics of large volcanic eruptions since 1750 according to their geographic latitudes, their elevations, and the years and months in which they occurred. The results show that most large volcanic eruptions were located around the margins of the Pacific Ocean and the islands of Sumatra and Java, especially in the equatorial regions（10°N–10°S）. Large volcanic eruptions were concentrated at 1000–2000 m elevations and in the months of January and April. There were more eruptions in the summer half-year（from April to September） than in the winter half-year（from October to the next March）. Large volcanic eruptions have interdecadal fluctuations, including cycles of 15–25 years and 35–50 years, which were detected by Morlet wavelet analysis, with the fluctuations being more frequent after 1870 than before. During the periods 1750–1760, 1776–1795, 1811–1830, 1871–1890, 1911–1920 and 1981–1995, there were relatively many large volcanic eruptions.     

INTERRELATION BETWEEN EAST-ASIAN WINTER MONSOON AND INDIAN/PACIFIC SST WITH THE INTERDECADAL VARIATION*

Investigated statistically is the interrelation between East Asian winter monsoon (EAWM) and SST over sensitive areas of the Indian and Pacific Oceans.with focus on the relation of EAWM to strong ENSO signal area.i.e.,the equatorial eastern Pacific (EEP) SST.Evidence suggests that the EAWM variation is intimately associated not only with the EEP SST but with the equatorial western Pacific "warm pool" and equatorial Indian/northwestern Pacific Kuroshio SST as well:the EAWM and ENSO interact strongly with each other on the interannual time scales,exhibiting pronounced interdecadal variation mainly under the joint effect of the monsoon QBO and the monsoon/SST background field features on an interdecadal basis-when both fields are in the same phase(anti-phase).strong EAWM contributes to EEP SST rise(drop)in the following winter,corresponding to a warm(cold)ENSO cycle;the EAWM QBO causes ENSO cycle to be strong phase-locked with seasonal variation,making the EEP SST rise lasting from April-May to May-June of the next year,which plays an important role in maintaining a warm ENSO phase.     

拉萨近半个世纪降水的变化特征

利用拉萨1952-2005年逐月降水量,≥0.1 mm、1.0 mm、5.0 mm和10.0 mm年降水日数,分析了近半个世纪拉萨年、季降水量及年降水日数的年际和年代际变化.结果发现:近半个世纪以来,拉萨年降水量表现为前30年呈不显著的减少趋势,减幅为17.8 mm/10 a;季降水量除夏季呈不显著的减少趋势外,其它各季均表现为增加趋势,以秋季增幅最大;≥0.1 mm、≥1.0 mm和≥5.0 mm年降水日数表现为不同程度的增加趋势.近25年≥10.0 mm的年降水日数呈极显著的增加趋势.20世纪50年代至80年代夏季降水量表现为逐年代减少趋势,秋季降水量则呈逐年代增加趋势,而冬季降水量为负距平.各等级年降水日数20世纪80年代偏少,90年代偏多.年降水量异常偏旱年主要出现在20世纪80年代,50年代和60年代的初期各出现一次异常偏涝年,70年代从未出现过异常年份.14年振荡周期可能是影响年降水量的主导周期.     

Flooding 1990s along the Yangtze River, has it concern of global warming?

1 IntroductionFloods occurring along the Yangtze River (Changjiang River) valley make up about 35.8 % of the floods over China[1]. Most noteworthily, a series of severe floods happened along the middle to lower Yangtze River and caused great damages during the past decade. The flood of 1991 afflicted 0.98 million hectares of farmland and resulted in 1,200 loss of life. Severe flood occurred again over this region in 1996. An extremely destructive flood emerged during the summer of 1998, wh…     

冬季北半球风暴轴的协同变化及其与大气环流的相互作用

基于1971—2016年NCEP/NCAR的逐日、逐月再分析资料,研究冬季北半球西伯利亚风暴轴(Siberian Storm Track,SIST)、北太平洋风暴轴(Pacific Storm Track,PST)和北大西洋风暴轴(Atlantic Storm Track,AST)的协同变化特征及其与大气环流的关系。结果表明:(1)三大风暴轴不仅各自的位置与强度变化存在显著相关性,风暴轴之间也存在一定的协同变化且年代际尺度上比年际尺度上更紧密。年际尺度上,SIST与AST的经度变化呈显著负相关,而PST和AST的协同性较差;年代际尺度上,SIST与PST的经、纬度变化均呈弱的负相关,SIST与AST的经度和强度变化均呈显著正相关,PST与AST的经、纬度变化均呈显著负相关。(2)由联合EOF分析得到北半球风暴轴的协同变化时空特征:在年际尺度上,第一模态主要表现为SIST偏弱(强),PST主体偏弱(强)、东南偏强(弱),AST略偏北(南)偏强(弱)但不显著的协同变化。PC1为正位相时,对应的大气环流异常为:500 hPa高度场上为太平洋北美(Pacific North America,PNA)型和欧亚(Eurasian,EU)型的正位相,东亚急流偏强且偏南;第二模态主要表现为SIST偏强(弱)且偏东(西),PST中东部偏南(北)、西部强度偏强(弱),AST偏强(弱)的协同变化。PC2为正位相时,对应的大气环流异常为:500 hPa高度场上为PNA型和大西洋东部(East Atlantic,EA)型的正位相,北美急流减弱;在年代际尺度上,第一模态主要表现为SIST偏西(东)且偏弱(强),PST偏东(西)且偏弱(强),AST偏西(东)且偏弱(强)的协同变化。PC1为正位相时,对应的大气环流异常为:500 hPa高度场上为西大西洋(West Atlantic,WA)型和EU型的正位相。第二模态主要表现为SIST偏强(弱)且偏北(南),PST偏南(北)且偏弱(强),AST北抬(南压)的协同变化。PC2为正位相时,对应的大气环流异常为:500 hPa高度场上为EU型和WA型的正位相,东亚急流强度加强且偏南,北美急流强度减弱。     

Interdecadal Change of the Relationship Between the Tropical Indian Ocean Dipole Mode and the Summer Climate Anomaly in China

The interdecadal change of the relationship between the tropical Indian Ocean dipole(IOD) mode and the summer climate anomaly in China is investigated by using monthly precipitation and temperature records at 210 stations in China and the NCEP/NCAR reanalysis data for 1957-2005.The results indicate that along with the interdecadal shift in the large-scale general circulation around the late 1970s,the relationship between the IOD mode and the summer climate anomaly in some regions of China has significantly changed.Before the late 1970s,a developing IOD event is associated with an enhanced East Asian summer monsoon,which tends to decrease summer precipitation and increase summer temperature in South China;while after the late 1970s,it is associated with a weakened East Asian summer monsoon,which tends to increase(decrease) precipitation and decrease(increase) temperature in the south(north) of the Yangtze River.During the next summer,following a positive IOD event,precipitation is increased in most of China before the late 1970s,while it is decreased(increased) south(north) of the Yangtze River after the late 1970s.There is no significant correlation between the IOD and surface air temperature anomaly in most of China in the next summer before the late 1970s;however,the IOD tends to increase the next summer temperature south of the Yellow River after the late 1970s.     

南亚高压的年际和年代际变化

利用1958～1998年NCEP/NCAR再分析月平均100 hPa高度场和风场资料， 依据大气环流观测事实及天气学原理，较客观地定义了描述南亚高压活动的特征参数， 然后对南亚高压的年际及年代际变化特征进行了系统的诊断分析。发现北半球中低纬 100 hPa环流异常具有空间整体性和时间持续性，即北半球中低纬100 hPa环流同时加 强或同时减弱，并且其整体异常具有明显的年代际变化。南亚高压面积和强度的变化 存在3.8年的振荡周期，与ENSO的循环周期一致。南亚高压的中心和脊线在夏季较为稳 定，较大的年际差异出现在春季。高压面积和强度的年际变化最明显，并且面积大、 强度强的年份往往与El Niao年相对应。南亚高压的位置和强度还存 在明显的年代际变化，自1978年以后，冬半年南亚高压脊线南移，中心东移，面积增大， 强度增强，夏半年南亚高压的位置变化不很明显，但是面积和强度也增大增强。这种年代 际异常与低层大气系统及赤道太平洋海温的年代际异常一致。南亚高压强度距平与热带 海洋SSTA密切相关，与印度洋海区的同期相关最好。南亚高压强度异常对印度洋SSTA的 响应时间为0～5个月，对赤道中东太平洋SSTA的响应时间为4～6个月。南亚高压明显的 年际和年代际变化特征表明，可将南亚高压看作气候系统中大气子系统异常的强信号， 通过分析南亚高压的年际及年代际异常可以更直接地研究和预测区域气候异常。     

近50a华北地区冬季气温的时空变化特征

利用我国160站1951－2000年的月平均气温资料，在分析华北地区气温变化的季节－－年际变化特征的基础上，重点分析了冬季的年际、年代际变化的时空特征。发现：冬季气温在50、60年代较低，70年代开始升高，80年代变化较为平缓，90年代增暖程度加大，50a来有显著的增暖趋势，达0.27℃／（10a)。华北地区冬季气温的升高趋势与中国大部分地区是一致的，且是升高最明显的地区之一。     

华北盛夏降水年代际变化与南半球环流异常的关系

利用NCEP/NCAR再分析资料和中国160个台站降水资料,分析了华北盛夏降水与南半球马斯克林高压、澳大利亚高压的年际关系。结果表明,华北盛夏降水和马高、澳高在年际变化尺度上都有着显著的负相关关系,且这种关系存在年代际变化,并重点分析了与华北盛夏降水年代际变化相对应的南半球环流异常型的特征。