Assessment of Teleconnection Patterns Affecting Rainfall Extreme Indices(Case Study: Sistan-Baluchestan Province)

Generally, Climatic extreme events, like the heavy rainfalls and sudden changes cause the greatest range of damages to water resources, agricultural and even human daily life. Therefore, correction and regular monitoring reduces their negative effects. Climatic signals represent changes of between temperature and pressure in ocean that they are one of the most influential parameters on climatic patterns. This study evaluates the effects of large – scale climate factors on rainfall extreme indices in Sistan-Baluchestan province as symbol of arid land in Iran that it has sever climatic oscillations. In order to at first step we use data of daily rainfall 6 synoptic stations at 1987-2014 period from meteorological organization and 19 Teleconnection indices from NCEP/NCAR. Then we calculated extreme indices. In continue correlation of extreme indices and teleconnection calculated. In next step we analyzed affecting teleconnection by regression model. The result of the correlation between teleconnection indices and extreme rainfall indices showed that TSI, TNI, AO, WP, WHWP, TNA, NINO1, EA, NINO4, PDO, PNAو NAO have correlation with rainfall extreme indices but this effects are different in station to another as in Khash station the most correlation occur with R50 and in Chabahar station occur with R10. So determined that teleconnection identify about 30 percent of changes.