بررسي تغييرات بارندگي در ايران به كمك شاخص هاي اقيانوسي-اتمسفري

چكيده انگليسي :

Investigating of Iran s Rainfall Variations Using Ocean Atmospheric Indices Rabbaneh Roghani r roghani@na iut ac ir February 28 2011 Department of Natural Resources Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Saeid Soltani ssoltani@cc iut ac ir Abstract Rainfall variability in space and time is the characterics of arid and semiarid zones Determination of factors influencing on rainfall of these regions such as Iran is important for forecasting purposes and water resource management Ocean atmospheric oscillations such as ENSO El Ni o Southern Oscillation phenomenon have been known as one of the most important factors influencing on rainfall of specific areas This study aimed to investigate the correlations between ocean atmospheric oscillations and Iran rainfall The correlations were investigated both monthly and seasonal Monthly rainfall data from 50 synoptic stations with at least 30 years of records up to the end of 2007 were used a First concurrent and lag relationships 0 3 lead time between ENSO and Iran monthly and seasonal rainfall were evaluated based on Southern Oscillation Index SOI and Indian and Pacific Sea Surface Temperature SST in Rainman software Monthly and Seasonal time series were divided to several groups by four methods Avarage SOI SOI Phases Indian SST Phases and Pacific SST Phases Significant differences between rainfall groups in each methods were assessed by the non parametric Kruskal Wallis and Kolmogorov Smirnov tests The significant relationships for rainfall forecasting was validated by Linear Error in Probability Space LEPS test b Then Pearson correlation coefficients between Iran monthly and seasonal rainfall with North Atlantic Oscillation NAO North Caspian Pattern NCP Mediterranean Oscillation Algiers Cairo MOac Mediterranean Oscillation Gibraltar Israel MOgi Western Mediterranean Oscillation WeMO Mediterranean Circulation Index MCI Mediterranean SST MSST and Persian Gulf SST PGSST were analyzed c Finally for each season the effective ocean atmospheric oscillation indices in homogenous rainfall regions were identified by stepwise multivariate regression analysis The results showed that status of ENSO during summer July September was related to autumn October December and October rainfall in the west and northwest of Iran and the west Caspian Sea coast The El Ni o Negative phase is associated with increased rainfall and the La Ni a Positive phase is associated with decreased rainfall Using average SOI is useful index for rainfall forecasting in mentioned areas According to results Indian and Pacific SST phases are not suggested for rainfall forecasting in Iran There is a significant correlation between NAO and monthly rainfall in northern and western parts of Iran Also a lag significant correlation between NAO and winter January March rainfall in north western and autumn rainfall in central and southern of Iran were identified NCP has a simultaneous and positive correlation with monthly and seasonal rainfall over north of Iran There was a weak correlations between MOac and MOgi and Iran rainfall however the correlation for MOgi was higher than MOac These indices MOgi and MOac showed a significant correlation with May rainfall in western part of Iran and spring rainfall April June in west Caspian Sea coast MCI and WeMO had simultaneous and negative correlation with monthly and seasonal rainfall over most parts of Iran these correlations were stronger during winter in seasonal timescale January March and January and February in monthly timescale The correlation between MSST and monthly rainfall was significant only for limited area of Iran especially north part however significant correlations were not found with MSST and seasonal rainfall A significant negative correlation between the PGSST and spring autumn and April rainfall in eastern half of Iran were found Inverse relationship with Iran rainfall and PGSST and MSST does not seem real The more studies

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بررسي تغييرات بارندگي در ايران به كمك شاخص هاي اقيانوسي-اتمسفري

بارش , انسو , Rainman