Interannual variability of the southern Yellow Sea Cold Water Mass

Temperature data collected in the sections of 34°N, 35°N and 36°N in August from 1975 through 2003 were analyzed using Empirical Orthogonal Function (EOF) to investigate interannual variability of the southern Yellow Sea Cold Water Mass (YSCWM). The first mode (EOF1) reveals variations of basin-wide thermocline depth, which is mainly caused by surface heating. The second mode (EOF2) presents fluctuations of vertical circulation, resulting mainly from interannual variability of cold front intensity. In addition, it is found that the upward extent of upwelling in the cold front is basically determined by wind stress curl and the zonal position of the warm water center in the southern Yellow Sea is correlated with spatial difference of net heat flux.     

中国近百年夏季雨量场及雨带类型恢复研究

文章将气象要素场转化为秩序统计量场,用ＥＯＦ迭代方案进行气象要素场的恢复研究．利用全国４２个站点１９５１～１９９５年夏季（６～８月）雨量场资料对１９０１～１９５０年夏季雨量场进行了恢复,并在此基础上用Ｂａｙｅｓ判别法对雨带类型进行了恢复．检验表明,所恢复的资料是可靠的．     

用均生函数预测模型预报降水的若干试验

基于均生函数的处理原则,对目前常用的均生函数逐步筛选模型,主成分模型进行预报试验,提出带逐步筛选的主成分模型,并用变化幅度较大的降水序列对三种模型进行若干预测试验,结果表明,逐步筛选的主成分模型优于主成分模型,在对不同预报步长的预测试验中也表明,逐步筛选的主成分模型在预测效果以及模型的稳定性方面都是较好的。     

Spatial and Temporal Variability in a Vertical Section Across the Alaskan Stream and Subarctic Current

In the central North Pacific Subarctic Gyre, CTD hydrographic measurements were carried out yearly in late June from 1990 to 1998 at 9 stations along 180° meridian from 48°N to 51.2°N. Vertical sections of 9-year means, anomalies for each year and others of potential temperature, salinity, potential density and geostrophic velocity (referred to 3000 m) were calculated based on this data set. Empirical Orthogonal Function (EOF) analysis was adopted in the investigation of spatial characteristics and its temporal variation in vertical sections. The spatial distribution of the 1st mode EOF of velocity shows the westward Alaskan Stream and the eastward Subarctic Current. This mode explains 37.6% of the total variance. Two positive maxims appear in its amplitude in 1991 and 1997, which is similar to the variation in volume transport of the eastward Subarctic Current. These variations are closely related to the vertical movement of Ridge Domain deep water.     

1980—2016年西太平洋暖池与ENSO循环过程的相关分析

利用1980—2016年海表温度(SST)、海平面气压场（SLP）、南方涛动指数（SOI）、平均海洋尼诺指数（ONI）等资料对近37 a发生的ENSO（El Nio-Southern Oscillation）事件进行统计分析,并用经验正交函数分析法以及小波分析方法研究西太平洋暖池与ENSO循环过程之间的作用机制。研究表明：近37 a来,Nino3.4区的SST在厄尔尼诺（El Nio）现象发生时存在较大的正距平,采用Nino3.4区SSTA的大幅度突变作为指标,能够更好地反映El Nio事件的发生;El Nio事件合成分析可知其形成过程中,西太平洋有一逐渐增强东移的暖中心;西太暖池东边界变化具有明显的年际变化特征,平均3～4 a经历一次循环,并出现变化周期延长的现象;海表温度的EOF能很好地预示ENSO的发生;通过小波分析可以看出暖池东边界对ENSO的发生有较好的预报意义。     

北太平洋风应力场变异规律及其与黑潮大弯曲和El—Nino的联系

利用COADS资料,计算北太平洋(包括赤道海区)1949—1979年海表面风应力,对其距平场进行矢量场的EOF分解,得到几个主要的距平风应力模态(EOF1—3)。分析了各自的时空分布特征,分析发现,风应力距平场的EOF1和EOF2模态分别对黑潮大弯曲和E1—Nino事件有重要影响,并讨论了其影响过程,为黑潮大弯曲预报的可能性提供了依据。     

福建春季降水量场预测模型研究

利用1960—2000年福建春季(2—4月)降水量场资料，分析了经验正交函数(EOF)展开得出的特征向量，以反映降水的空间分布特征。研究了前三种分布型的时间系数与前期北半球500hPa、100hPa月高度距平场和北太平洋海温距平场之间的关系，针对不同的分布型分别找出了不同的前期预测信号，以此为预测因子，构建出福建春季降水量场短期气候预测模型。利用该模型对2001、2002年福建春季降水量场进行试预测，取得了较满意的结果。     

热带太平洋-印度洋海温联合模及其气候影响

本文基于观测资料和LICOM2.0模拟结果的分析研究,简要介绍讨论了太平洋—印度洋海温(异常)联合模(PIOAM)的存在、特征、演变及其影响等问题。热带太平洋—印度洋区域乃至全球范围的海表温度异常(SSTA)资料进行EOF分解,都清楚表明其第一分量在热带太平洋—印度洋的空间形态与太平洋—印度洋海温(异常)联合模(PIOAM)非常相似,说明PIOAM是热带太平洋—印度洋实实在在存在的一种海温异常模态。对应PIOAM的正、负位相,热带印度洋和西太平洋地区的夏季(JJA)850 hPa距平风场有近乎相反的异常流场形势;对流层低层的Walker环流支和亚洲夏季风都出现了不同特征的(近乎相反)异常;在PIOAM正(负)位相将使得100 hPa的南亚高压位置偏东(西)。对热带太平洋和印度洋温跃层曲面上的海温异常(为了方便将其称为SOTA)进行EOF分解,发现其第一模态也是一个三极子模态,即当赤道中西印度洋大部分海域与赤道中东太平洋大部分海域偏暖(偏冷)时,赤道东印度洋和赤道西太平洋大部分海域则偏冷(偏暖);它与太平洋—印度洋表层的PIOAM十分类似,也表明PIOAM在海洋次表层也是存在的。高分辨海洋环流模式LICOM2.0的模拟结果,无论是对太平洋—印度洋表层还是次表层的PIOAM的特征和演变都刻画得很好,这从另一个角度进一步说明PIOAM是热带太平洋—印度洋实际存在的一种海温变化模态。PIOAM正、负位相不仅对亚洲及西太平洋地区的天气气候有非常不一样的影响(不少地方有反向的特征),还会对南北美洲和非洲一些地区产生不同影响;而且其影响与单独的厄尔尼诺(El Ni?o)及印度洋偶极子(IOD)都不尽相同。     

江淮梅雨期降水异常分布型及其与东亚副热带高空西风急流的关系

利用1980—2010年的NCEP/NCAR再分析资料与江淮地区44个站逐日降水资料,分析了江淮地区1980—2010年梅雨期(6月16日—7月15日)降水的基本空间分布型及其与东亚副热带西风急流的关系。结果表明,江淮梅雨降水的第一分布型为"南正(负)北负(正)",该型受副热带高空西风急流位置的影响,急流位置偏南(北),则雨带位于江淮南(北)部地区;第二分布型为"中间负(正),两边正(负)",该型受副热带高空西风急流强度的影响,急流强度异常偏弱(强),则雨带位于江淮地区西北、东南部(中部)。合成分析表明,高空急流位置异常偏南时,500 h Pa副高偏弱、偏南,850 h Pa江淮南部地区为水汽、风场辐合区,高低空配置有利于降水呈"南正北负"的分布型。高空急流强度异常偏弱时,从我国江淮中东部地区至日本南部,500 h Pa上无明显垂直运动,850 h Pa上有水汽和风场的辐散区,高低空配置有利于降水呈"中间负,两边正"的分布型。     

Application of Empirical Orthogonal Function (EOF) method to detect the spatial grain-size fractionation of aeolian sediment and comparison with other methods in case studies from northwestern China

A grain-size fraction/population of sediment can reflect a specific transport process. Use of this potential grain-size fraction is more meaningful than that of a single grain-size value for analysis of grain-size fractionation over space, so identifying the potential grain-size fraction is key in analyzes of grain-size fractionation. Our aim was to test the applicability of Empirical Orthogonal Function (EOF) analysis for sediment grain-size fractionation. We performed EOF analysis on grain-size data of aeolian sediment to identify the potential grain-size fraction and detect its grain-size fractionation over space. Two other methods, the grain-size-class standard deviation (GSC-std) method and end-member analysis (EMA) were conducted for comparison. The results show that the EOF method is not only able to identify the potential grain-size fraction, but also to simultaneously determine the spatial change of the potential grain-size fraction. The GSC-std method provides the potential grain-size fraction, but fails to exhibit its spatial change at the same time. EMA end members resemble a grain-size distribution that differs from the potential grain-size fraction; thus, the EMA method fails to identify the potential grain-size fraction directly. Our results suggest that EOF analysis is suitable for detecting grain-size fractionation over space.