Forty Years of Air Temperature Change over Iran Reveals Linear and Nonlinear Warming

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  • Spatiotemporal analysis of long-term changes in air temperature is of prime importance for climate change research and the development of effective mitigation and adaptation strategies. Although there are considerable studies on air temperature change across the globe, most of them have been on linear trends and time series analysis of nonlinear trends have not received enough attention. Here, spatiotemporal patterns of monthly and annual mean (Tmean), maximum (Tmax), and minimum (Tmin) air temperature at 47 synoptic stations across climate zones in Iran for a 40-yr period (1978–2017) are analyzed. A polynomial fitting scheme (Polytrend) is used to both monthly and annual air temperature data to detect trends and classify them into linear and nonlinear (quadratic and cubic) categories. The significant (non-significant) trends in Tmean, Tmax, and Tmin across all climate zones are 41.1% (58.9%), 34.1% (65.9%), and 46% (54%), respectively. The highest magnitude of increasing trends is observed in the annual Tmin (0.47°C decade−1) and the lowest magnitude is for the annual Tmax (0.4°C decade−1). Across the country, increasing trends (\bar x = 37.2%) have higher spatial coverage than the decreasing trends (\bar x = 3.2%). Warming trends in Tmean (65.3%) and Tmin (73.1%) are mainly observed in humid climate zone while warming trends in Tmax are in semi-arid (43.9%) and arid (34.1%) climates. Linear change with a positive trend is predominant in all Tmean (56.7%), Tmax (67.8%), and Tmin (71.2%) and for both monthly and annual data. Further, the linear trends have the highest warming rate in annual Tmin (0.83°C decade−1) and Tmean (0.46°C decade−1) whereas the nonlinear trends have the highest warming rate in annual Tmax (0.52°C decade−1). The linear trend type is predominant across the country especially in humid climate zones whereas the nonlinear trends (quadratic and cubic) are mainly observed in the arid climate zones. This study highlights nonlinear changes and spatiotemporal trends in air temperature in Iran and contributes to a growing body of climate change literature that is necessary for the development of effective mitigation and adaptation strategies in the Middle East.
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