Analysis the Impact of Climatic Signals on Kurdistan Precipitation

To doing this research, daily precipitation data from 188 synoptic, climatology and rain gauges stations in and out of Kurdistan province during 21/3/1961 to 19/1/2011 have been used. Daily precipitation interpolated on 6*6 km pixels by Kriging spatial statistic over Kurdistan province. One matrix with dimension 18203*811 has been created that located time (days) on the rows and column were pixels. For each pixels total monthly precipitation has been calculated. Data of ten teleconnection patterns extracted from NCEP/NCAR. Linear regression has been used to detection correlation between precipitation and teleconnection patterns. The correlation tested in 95% confidence level. The results showed that correlation between precipitation and teleconnection patterns is significant in 95% confidence level. The extent and intensity of significant correlation go to head in autumn season. The impact of South Oscillation Index (SOI), North Sea Caspian Pattern (NCP) and East Atlantic and West Russia (EAWR) is high in autumn. In cold seasons, SOI has negative correlation while NCP and EAWR have positive correlation with precipitation. In warm seasons two recent indices have negative correlation with precipitation. In total, increase sea level pressure and geopotential height in 500 hPa over Western European parts and decrease over eastern Mediterranean, Caspian Sea and north Caspian result in increase precipitation in Kurdistan province during cold seasons. In contrast, increase sea level pressure and geopotential height in 500 hPa over northern part of Caspian Sea result in increase precipitation during warm seasons.