Response Analysis Of Precipitation In China To ENSO Events Based On Delay Correlation Analysis

ENSO is the general term of the El Nino and Southern Oscillation, it plays anirreplaceable role in observing and studying with the change of the climate as the strongestsignal of air-sea interaction. ENSO cycle has an important impact on the global climatechange, and the abnormalities of ENSO can cause flood, droughts, typhoons extreme weatherphenomena, that threat the safety the live and property of people. China located in the EastAsia on the west coast of Pacific Ocean, the climate of China affected by the ENSO cyclesignificantly, the study of how ENSO events impact on the climate of China is a greatsignificance.This paper takes average monthly land precipitation grid date of China (the range of72°E-136°E,18°N-54°N) in January1961to December2011on as the object of the research,which includes a total of9216(72×128) sets of date. M-K test, wavelet transform analysis andEOF analysis are used to analysis the time series above, results show that: China precipitationis decrease before mid-1970s and a steady increase of small amplitude is bounded after that,so the mid-1970s is the minimum of China precipitation;2-3years period of Chinaprecipitation are significant from1961to2011, and the long period is not obvious before1995. EOF analysis showed that there was increasing tendency from northwest to southeast ofChina precipitation, and the tendency change is unification, the regional distribution isobvious.Analysis the time series of SOI, Nino3.4and Nino4, MEI, which are represented theENSO index that defined by sea surface pressure, sea surface temperature, multivariatevariable. The results showed that: SOI is continued to decrease, Nino3.4is decrease first andstable then, Nino4is decrease first and a small increase after that, MEI is a slight decreaseafter the first modest upward trend; cycle analysis found that, SOI cycle mainly for two years,Nino3.4cycle mainly for2-4years, Nino4period of five years mainly, MEI cycle mainly for3or5years, ENSO cycle of1-6years in each index scale are significant, and Nino3.4andNino4long period is not obvious.Analysis the0-12months-scale delay correlation between9216sets of monthlyprecipitation series in China and four kinds of ENSO Index, record the maximum correlationcoefficient and drawing grid date of filled back. The results show that the correlationcoefficient with precipitation series of China can be arranged as follows: Nino3.4、Nino4、MEI、SOI. All the correlation of Nino3.4and Nino4with precipitation series in China passedthe remarkable test of the0.05level. According to the time series analysis above andcombined with previous research, Nino3.4is selected as the representative ENSO index. Recorded the delayed months when the maximum delay correlation appear and plotted. Theresult shows that the delayed months can be divided into three regions as follow: southwest,central and most parts of China.Divide the sea surface temperature of ENSO events into five levels which are very week,week, moderate, strong and very strong according the Ocean Nino Index. Analyzing theChina precipitation changes that delay corresponding month of ENSO events intensity abovemoderate appeared. During warm ENSO events the China precipitation changes are separatedby Qinling-Huaihe, precipitation of north is less than usual or stable, and precipitation ofsouth is more than usual. The precipitation changes are mainly impacted by the intensity ofENSO events, followed by the outbreak of the time and event duration did not impact theprecipitation significantly. During cold ENSO events precipitation of north is less than usualor stable, and precipitation of south is disunity. Event duration impact the precipitation ofChina not obvious and outbreak of the time show a great influence. Changes in precipitationmagnitude analysis showed that the magnitude of precipitation changes in northwest regionaffected by ENSO events most, followed by the Northeast, the affect of ENSO events inNortheast China, North China, Central China and East China, Southeast and Southwestregions were less.