Abstract

The extreme temperature indices (ETI) are an essential indicator of climate change. The detection of their changes over the next years can play an essential role in the climate action plan (CAP). In this study, four temperature indices (mean of daily minimum temperature (TN), mean of daily maximum temperature (TX), cold-spell duration index (CSDI), and warm-spell duration index (WSDI)) were defined by ETCCDI and two new indices,the maximum number of consecutive frost days (CFD) and the maximum number of consecutive summer days (CSU), were used to examine ETIs in Iran under climate change conditions. We used minimum and maximum daily temperatures of five general circulation models (GCMs), including HadGEM2-ES, IPSL-CM5A-LR, GFDL-ESM2M, MIROC-ESM-CHEM, and NorESM1-M, from the set of CMIP5 bias-correction models. We investigated two representative concentration pathway (RCP) scenarios of RCP4.5 and RCP8.5 during the historical (1965–2005) and future (2021–2060 and 2061–2100) periods. The performance of each model evaluated using the Taylor diagram on a seasonal scale. Among models, GFDL-ESM2M and HadGEM2-ES showed the highest, and NorESM1-M and IPSL-CM5A-LR showed the lowest performance in Iran. Then, an ensemble model was generated using independence weighted mean (IWM) method. The results of multi-model ensembles (MME) showed a higher performance compared to individual CMIP5 models in all seasons. Also, the uncertainty value significantly reduced, and the correlation value of the MME model reached 0.95 in all seasons. Additionally, it is found that WSDI and CSU indices showed positive anomalies in future periods, and CSDI and CFD showed negative anomalies throughout Iran. Also, at the end of the twenty-first century, no cold spells are projected in almost every part of Iran. The CSU index showed that summer days are increasing sharply; according to the results of the RCP8.5 scenario in spring (MAM) and autumn (SON), the CSU will increase by 18.79 and 20.51 days, respectively, at the end of the twenty-first century. It projected that in the future, the spring and autumn seasons will be shorter and summers will be much longer than before.

Highlights

  • Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) shows that the globally averaged surface temperature of the earth and oceans has increased about 0.85°C [0.65–1.06°C] during the period 1880 to 2012

  • We examined the mean of daily minimum temperature (TN) and mean of daily maximum temperature (TX) of five models including HadGEM2-ES, IPSL-CM5A-LR, MIROC-Earth System Models (ESM)-CHEM, GFDLESM2M, and NorESM1-M from the set of CMIP5 Bias-Correction models on a seasonal scale

  • Our results showed that GFDL-ESM2M and HadGEM2-ES models have the highest and NorESM1-M and IPSL-CM5A-LR models have the lowest performances in simulating temperature in Iran

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Summary

Introduction

Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) shows that the globally averaged surface temperature of the earth and oceans has increased about 0.85°C [0.65–1.06°C] during the period 1880 to 2012. A period of consecutive days with very high and low temperatures is called a warm or cold wave (Cook et al 2013). They are one of the forms of extreme climate events, and their frequency, intensity, and duration are expected to increase under climate change in the decades. Increasing in frequency and intensity of temperature extremes is significant for detecting cold spells in the region with dry climates such as Iran, which depends on snowmelt water resources in the warm period of the year. Increasing in frequency and intensity of temperature extremes is significant for detecting cold spells in the region with dry climates such as Iran, which depends on snowmelt water resources in the warm period of the year. Donat et al (2013) showed that significant warming in all seasons is associated with more pronounced warming in cold seasons of the Earth

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