Investigation of the effect of large-scale atmospheric signals at different time lags on the autumn precipitation of Iran’s watersheds

Arabian Journal of Geosciences - Tập 13 - Trang 1-24 - 2020
Jalil Helali1, Saadoun Salimi2, Mohammad Lotfi3, Seyed Asaad Hosseini4, Ali Bayat2, Mohammad Ahmadi5, Siroos Naderizarneh3
1Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
2Kharazmi University, Tehran, Iran
3Islamic Azad University, Science and Research Branch, Tehran, Iran
4Department of Physical Geography, Mohaghegh Ardabili University, Ardabil, Iran
5Kermanshah Regional Meteorological Office, Kermanshah, Iran

Tóm tắt

In recent decades, the upgrading of information of human beings about the Earth’s climate and concern about climate change in the future has led to a better understanding of the components affecting the climate. One of the factors that has received much attention as a predictor of precipitation is teleconnection patterns, which is one of the topics of interest in hydrological, meteorological, and agricultural forecasts. Therefore, the main goal of the present study is to investigate the effect of teleconnection phenomena on autumn precipitation in Iran at different spatiotemporal scales including basin and different time lags using the Pearson correlation method and synoptical analysis. For this purpose, a network of 717 synoptic and rain gauge stations and 40 teleconnection indices at 1- to 6-month lags (from April to September) were utilized during the period 1987–2015. Finally, the type of correlation and frequency of significant signals or teleconnection (FSS) correlations were analyzed at basin and sub-basin scales. According to the results in most of the basins, the highest FSS correlations occurred at 1- to 3-month lags and in the Central Plateau basin occurred at 2- to 6-month lags. Simultaneous investigation of the effect of time lags and teleconnection indices on the FSS correlations also illustrated that the time lags and type of teleconnection indices were different in each basin. Overall, the results showed that most of the FSS correlations of autumn precipitation in most basins of Iran were well correlated to 3-month lag and Sea Surface Temperature (SST), Tropical North Atlantic (TNA), and Southern Oscillation Index (SOI) indices, which can be used to predict autumn precipitation using different statistical methods. Also, synoptic analysis showed that the El Niño Southern Oscillation (ENSO) family indices have the most significant correlation with most studied basins, especially the peripheral and western basins of Iran. The pattern of FSS correlations is consistent with the country’s topography and precipitation corridors. Also, the regional indices are intermediary to measure the impact of global indices such as ENSO, Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO) on the Iranian climate. Based on the results, the interpretation of high correlation of teleconnection patterns with Iran basins precipitation is difficult and requires separate work, but it seems to have relation with Madden-Julian Oscillation (MJO) index.

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