摘要
对淮河流域降水异常进行分析对于预测黄海绿潮具有重要意义。选取淮河流域10个站,长江流域15个站,通过对国家气象信息中心1951-2011年的逐月降水数据进行分析,研究淮河流域和长江流域5-6月平均降水异常。2000-2010年,淮河流域5-6月降水呈现增加趋势,与长江流域降水呈反位相变化。分别对淮河流域5-6月平均降水异常与印度洋偶极子指数(Dipole Mode Index, DMI),以及太平洋年代际振荡(the Pacific Decadal Oscillation, PDO)指数做相关性分析,结果表明:淮河流域5-6月平均降水异常与6个月前的DMI指数达到最大正相关,与20个月前的北太平洋(20°N以北)SST呈现明显的负相关,与PDO指数达到最大负相关。这表明, PDO、DMI指数对淮河流域5-6月降水异常的年代际、年际变化具有明显的指示作用。
Rainfall anomalies in the Huaihe River Valley (HRV) is one of the most important factors for green tides outbreaks. So study of the rainfall anomalies of HRV is very important for forecast of the green tides in the Yellow Sea. The monthly precipitation data from 1951 to 2011 used here was from the National Meteorological Information Center, 10 stations in HRV and 15 stations in the Changjiang River Valley (CRV). May-June (MJ) average rainfall anomalies showed an upward trend in HRV from 2000 to 2009, while a downward trend in CRV. Correlation analyses had been done between MJ average rainfall anomalies and the dipole mode index (DMI), and the Pacific decadal oscillation (PDO) index, respectively. A most significant positive correlation was found between the DMI 6 months ago and the MJ average rainfall anomalies of HRV of the year, confidence exceeding 95%. The North Pacific SST (north of 20°N) as well as the PDO index of 20 months ago, negatively correlated with MJ average precipitation anomalies in HRV of the year significantly, confidence exceeding 95%. In summary, these data indicate that DMI and PDO index demonstrate distinct indications of inter-annual and inter-decadal changes for MJ average rainfall in HRV, respectively.
出处
《海洋科学》
CAS
CSCD
北大核心
2014年第2期1-5,共5页
Marine Sciences
基金
中国科学院战略性先导科技专项(XDA1102030102)
国家海洋局公益性项目(201005006)
国家自然科学基金(41176018)
国家重点基础研究发展计划项目(2010CB950400)