Impacts of large-scale teleconnections on climate variability over Southwest Asia

Abstract

The atmospheric low frequency variability at a regional or global scale is represented by teleconnection. Using monthly dataset of the Climatic Research Unit (CRU) for the period 1971–2016, the impacts of four large-scale teleconnection patterns on the climate variability over Southwest Asia are investigated. The large-scale features include the El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) and the East Atlantic (EA) teleconnection patterns, as well as western tropical Indian Ocean (WTIO) sea surface temperature anomaly index. Results indicate that ENSO and EA are the first leading modes that explain variation of Southwest Asian precipitation, with positive (negative) anomalies during El Niño (La Niña) and the negative (positive) phase of EA. Variation of Southwest Asian near-surface temperature is most strongly related to WTIO index, with above-average (below-average) temperature during the positive (negative) phase of WTIO index, although the negative (positive) phase of NAO also favours the above-average (below-average) temperature. On the other hand, temperature (precipitation) over Southwest Asia shows the least response to ENSO (WTIO). ENSO and EA individually explain 13 percent annual variance of precipitation, while WTIO index explains 36 percent annual variance of near-surface temperature over Southwest Asia. Analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis Interim (ERA-Interim) data indicated establishments of negative (positive) geopotential height anomalies in the middle troposphere over Southwest Asia during El Niño (La Niña) or the negative (positive) phase of NAO, EA and WTIO. The response of precipitation variability over Southwest Asia to NAO is opposite to that expected from the geopotential height anomalies, but the correlation between precipitation and NAO is not statistically significant. Due to predictability of large-scale teleconnections, results of this study are encouraging for improvement of the state-of-the-art seasonal prediction of the climate over Southwest Asia.