A new approach in evaluation impacts of teleconnection indices on temperature and precipitation in Iran

In many parts of the world, teleconnection patterns are one of the climate phenomena that significantly change the causative climate anomalies, especially temperature and precipitation. Thus, statistical analysis and modeling of their effects are of great importance in order to understand the fluctuations and climate variability in a region. In this study, 52 teleconnection indices were utilized to perform statistical analysis and conceptual modeling as well as simulation of temperature and precipitation fluctuations in Iran. For this purpose, temperature and precipitation data of 36 synoptic stations in Iran and 52 teleconnection indices for the period 1951–2019 were used. For the analysis, the relevant data were classified into four groups of global (GLB), regional (RGN), El Niño–Southern Oscillation (ENSO), and all indices (ALL). Then, the correlation of the aforementioned indices with temperature and precipitation was calculated using the teleconnectional–statistical model (TSM). Afterward, 5 years with the highest correlation coefficient was selected and considered as the forecasting parameters. The results revealed that the local temperature forecasting using RGN indices and the precipitation forecasting using GLB and ALL indices were more accurate than those using other indices. Our findings highlighted the prominent role of the indices with broader geographical regions that mainly were evolved across the oceans. Moreover, the effect of ENSO teleconnection on Iran climate was explained by the dynamic mechanism of the atmospheric bridge. Comparing TSM outputs and the Climate Forecast System Version 2 (CFSV2), TSM outperformed CFSV2 in the conducting experiment. Overall, the findings of this study emphasized on the existence of coincided synergy in the fluctuation or trend within almost all indices and atmospheric parameters, and most of the fluctuations in the indices occurred simultaneously or right after the ENSO events, including specific super El Niño in 1997–1998 (turning point). Also, the dramatic effect of sunspots on the average temperature of Iran is shown in inverse harmony, which is not easily revealed by correlation analysis. Also, the influence of global warming and especially synchronization with El Niño event on climatic change was briefly discussed in the Middle East. In this work, for the first time in the Middle East, physical mechanisms of how linkages affect Iran’s climate and rainfall were proposed in a synoptic conceptual model.