热带海洋学报 ›› 2010, Vol. 29 ›› Issue (6): 34-45.doi: 10.11978/j.issn.1009-5470.2010.06.034cstr: 32234.14.j.issn.1009-5470.2010.06.034

• 海洋气象学 • 上一篇    下一篇

近50年来南海海面蒸发量的时空变化特征分析

丁张巍1, 黎伟标1, 温之平1, 罗聪2   

  1. 1. 中山大学季风与环境研究中心/大气科学系, 广东 广州 510275; 2. 广州中心气象台, 广东 广州510080
  • 收稿日期:2009-03-27 修回日期:2009-10-09 出版日期:2010-12-15 发布日期:2010-12-15
  • 通讯作者: 黎伟标。
  • 作者简介:丁张巍 (1984—), 男, 江西省景德镇人, 博士研究生, 现从事海气相互作用研究。E-mail: paton1945 @163.com
  • 基金资助:

    国家自然基金项目(40875020); 国家自然科学基金重点项目(40730951); 国家自然科学基金联合资助项目(U0733002)

Temporal and spatial characteristics of evaporation over the South China Sea from 1958 to 2006

DING Zhang-wei1, LI Wei-biao1, WEN Zhi-ping1, LUO Cong2   

  1. 1. Center for Monsoon and Environment Research/ Department of Atmospheric Sciences, Sun Yat-sen University, Guangzhou 510275, China; 2. Guangzhou Meteorological Observatory, Guangzhou 510080, China
  • Received:2009-03-27 Revised:2009-10-09 Online:2010-12-15 Published:2010-12-15
  • Contact: 黎伟标。
  • About author:丁张巍 (1984—), 男, 江西省景德镇人, 博士研究生, 现从事海气相互作用研究。E-mail: paton1945 @163.com
  • Supported by:

    国家自然基金项目(40875020); 国家自然科学基金重点项目(40730951); 国家自然科学基金联合资助项目(U0733002)

摘要:

根据最新的OAFlux洋面蒸发量资料, 使用EOF经验正交分解、谐波分析、小波变换、功率谱分析、趋势分析、M-K检验等方法, 对南海海区蒸发量的时空特征进行了分析。结果表明: 1)南海地区的蒸发量空间分布上秋冬季节最强, 其次是盛夏季节, 而春季最弱。2)南海海面蒸发量表现为全区一致变化型和南北反相变化型两个主要模态, 并可以解释总方差 60%以上的变化。3)在2—5 年周期的年际变化尺度上, 南海海面蒸发量与12—2月Niño3.4区海温距平存在较大相关。距平合成分析表明, 在强La Niña年, 南海海面蒸发表现南北蒸发反相变化型, 南海北部为正距平区, 南部为负距平区; 而在强El Niño年, 整个南海几乎全为正距平区。4)南海海面各个季节的蒸发量空间分布形态都存在高频的2—5年的年际变化和低频的10—14年的年代际变化, 这些周期振荡在南海海面蒸发量演变的不同阶段显著性不一。5)不仅从多年平均的年际变化上看南海海面蒸发量在1997年发生突变, 而且四季的蒸发量也均在1980年代后期发生过由偏弱转为偏强的突变。

关键词: 南海, 蒸发, 空间分布, EOF, 季节, 突变, 周期

Abstract:

Based on the latest Objectively Analyzed Air-Sea Heat Fluxes (OAFlux) data, the temporal and spatial variability of monthly-mean evaporation (EVP) over the South of China Sea (SCS) from 1958 to 2006 are analyzed. The EVP in winter and autumn is stronger than that in spring and summer. By the EOF analysis, the variation of the EVP of the first mode depicts an in-phase mode, while the second EOF mode describes an oscillation between northern and southern parts of the SCS. These two modes can explain over 60% of the variance. The interannual change of the EVP over the SCS is closely associated with the Niño3.4 sea-surface temperature anomaly (SSTA) during December-February. The spatial pattern of composite EVP anomalies shows that the southern SCS is out-of-phase with the northern area during La Niña years, while there is a monopole mode (with the same EVP anomaly sign) during the El Niño years. The research on the periodic variation of spatial structure of seasonal EVP reflects that there is interannual and interdecadal variability in each season. The outcome of wavelet analysis shows that the periods of 2-5 yr and 10-14 yr are the leading cycles of seasonal EVP over the SCS, and the significance of these oscillation periods is different at various stages. Finally, by Mann-Kendall and trend methods, it is considered that the EVP was gradually strengthened on the interannual and seasonal scale in the area in 1997 and after the 1980s.

Key words: South China Sea, evaporation, spatial distribution, EOF, season, abrupt change, period