Analysis of changes in thermal growing season indices (tGSI) and their relations with some selected atmospheric teleconnection patterns (ATPs) over the northwest of Iran.

Abstract

The daily minimum air temperature data from 18 stations located in the northwest of Iran during the period 1986-2015 was used to analyse the inter-annual variations and trends of thermal growing season indices (tGSI) and their relations with different atmospheric teleconnection patterns (ATPs). To analyze the changes in tGSI, tGSS (thermal growing season start), tGSE (thermal growing season end), and tGSL, the time period between tGSS and tGSE were considered. Using non-parametric Mann-Kendall and Spearman tests, the existence of a significant trend for time series of the tGSI and the correlation between ATPs and tGSI was evaluated. For eliminating the effect of serial correlation on test results, the trend-free pre-whitening approach was applied. Furthermore, residual bootstrap method was used to estimate the standard deviation of the Spearman correlation coefficient between tGSI and ATPs. The climate-based results showed the maximum tGSL increase (13.3daysperdecade) for SA-C-M climate. For SH-K-W climate, the maximum significant trends for tGSS and tGSE were 9.6 (earlier start) and 10.8 (delay) days per decade, respectively. In general, in all statistically significant cases, the main cause of the extended tGSL was both earlier tGSS and delayed tGSE. In regional scale, it was found that the most effective teleconnection pattern on tGSS and tGSE are MEI (positive correlation), occurring during late winter and spring, and PDO index (negative correlation) in the summer, respectively. Moreover, the tGSL demonstrated the highest correlation (negative) with PDO with 1-month delay. The findings highlight that the inter-annual variations of tGSI in northwest of Iran can be attributed to the influence of certain atmospheric teleconnection patterns such as MEI, PDO, NAO, AO, EA, and AMO.