Trend Analysis of Climate Compound Extreme Indices in Iran

Document Type : Research Article

Authors

• Hossain Esmaiili ¹
• Ahmad Roshani ¹
• Alireza Shakiba ²
• Fatemeh Parak ¹

¹ University of Kharazmi

² University of Shahid Beheshti

10.22067/geo.v0i0.67984

Abstract

Introduction

Although climate change is a global challenge, its effects occur locally and differ from  region to region (Filho et al., 2016; Leonard et al., 2014). Over the past few years, the large positive departures of temperatures from their mean values have become commonplace in many parts of the world. Surface temperature over land regions have warmed at a faster rate than over the oceans in both hemispheres (IPCC, 2007). Each of the last three decades has been successively warmer at the Earth’s surface than any preceding decades since 1850. The warmth of the period from 1983 to 2012 is very likely higher than any 30-year period in last 1,400 years in the Northern Hemisphere. The globally averaged temperature that results from combined land and ocean surface data shows a warming of 0.85 °C during the period 1880 to 2012, (IPCC, 2013). Indices for climate variability and extremes have been used for a long time, often by assessing daily temperature or precipitation observation above or below specific thresholds (Zhang et al., 2011). The dependence and thermodynamic relations between the precipitation and temperature have been addressed in numerous studies (Liu et al., 2012). Changes in extreme weather and climate events have significant impacts and are among the most serious challenges to society in coping with a changing climate (CCSP, 2008). The warming global climate has increased the concurrent climatic extremes and the intensity of extreme weather events over different regions of the Earth, such as drought, heat waves, tropical cyclones, floods, and fires (AghaKouchak et al., 2014; Alexander et al., 2005; Leonard et al., 2014). The projections of extreme weather phenomena on the basis of temperature and precipitation indices in AR5 show a probable increase in the number and intensity of dry and hot periods in the summer time (Filho et al., 2016; Hao et al., 2013). Many practical problems require the knowledge of the behavior of extreme values. In particular, the infrastructures we depend upon for food, water, energy, shelter and transportation are sensitive to the high or low values of meteorological variables (WMO, 2009). The impact of these events can be due to a single variable in an extreme state, but more often it is the result of a combination of variables which are not all necessarily extreme (Leonard et al., 2014). The combination of variables leading to an extreme impact is referred to a compound event (Beniston, 2011). Recent studies of joint quantities of precipitation and temperature are often described in terms of warm/wet, warm/dry, cool/wet and cool/dry climate combinations (e.g., Arsenovic et al., 2013; Beniston et al., 2009; Estralla & Menzel, 2012; Hao et al., 2013; Lopez-Moreno et al., 2011) and/or based on copula theory (see Miao et al., 2016). The combination of warm/wet, warm/dry, cool/wet and cool/dry modes reveals a systematic change at all the locations investigated with significant declines in the frequency of occurrence of the cool modes and a sharp rise in that of the warm modes. This article investigates the trends of combined temperature, precipitation, humidity, wind speed and sunshine statistic in spatial domain in Iran. Our investigation aims to use the joint quantities of temperature and precipitation and other variables of weather to offer some insights into the behavior of particular modes of heat and moisture which cannot be achieved by the analysis of the statistics of each individual variable. Over the last years, several extreme precipitation and temperature indices have been explained and analyzed in the literature (e.g., Parak et al., 2015; Rahimzadeh et al., 2009; Tabari et al., 2011); however,  the climate change has not been concerned with the use of joint extremes indices.

Materials and Methods

The study area in Iran lies approximately between 25oN and 40oN in latitude and between44oE and 64oE in longitude (see Fig. 1). Based on the Koppen climate classification, most parts of Iran are categorized under arid (BW) and semi-arid (BS) climates. Alborz and Zagros are the important mountains of Iran which play an important role in non-uniform spatiotemporal distribution of temperature and precipitation in Iran (Dinpashoh, 2006).
The examination of climate changes needs long and high quality records of climatic variables. In the present study, the dataset of daily maximum, the minimum and mean air temperatures and precipitation (P) for the period 1981-2015 from 47 synoptic stations from different geographic locations of Iran (Fig. 1) were collected from the Islamic Republic of Iran Meteorological Organization (IRIMO) and were then analyzed. The homogeneity of the dataset was also assessed and approved by IRIMO. Most of the regions were covered by the corresponding data and the geographical location of the stations.

Results and Discussion

One solution for the better detection of climate change is the use of compound indices; therefore, a set of compound indices derived using daily resolution climatic time series data with a major focus on extreme events were computed and analyzed to assess climate changes in Iran. The compound indices consisted of cool/dry, cool/wet, warm/dry, warm/wet, TCI and UTCI which were examined for a 47 synoptic meteorological stations during 1981-2015. The main results of the research showed a substantial change in the behavior of the joint extremes of temperature and precipitation quantities associated with warming has occurred in the past three decades. More than 80 percent of Iran has experienced a decrease in the annual occurrence of the cold modes and an increase in the annual occurrence of the warm modes. Universal thermal climate index (UTCI) change showed a widespread and significant increase in the annual occurrence of the strong heat stress (32–38 °C) and a significant decrease in the annual occurrence of the no thermal stress class (9-26 °C); in fact, the changes are also spatially coherent as compared with joint extremes of temperature and precipitation changes. Trends in tourism climatic index (TCI), including the number of days with TCI≥60, and the number of days with TCI≥80 showed similar changes but with weak spatial coherence. The results of this study also allow researchers to preview the condition that may occur with greater frequency in the future throughout Iran.

Conclusion

This paper attempts to present a suite of compound extreme indices with a primary focus on extreme events. These indices were calculated and analyzed for a number of sites between the years of 1981-2015 to provide a general overview of climate change in Iran. The results from non-parametric test showed statistically significant and spatially coherent trends in the compound extreme indices. It was found that in more than 80 percent of Iran the frequency of the warm modes has increased, while the frequency of cold modes has decreased but with smaller magnitudes. More than 97% of the country exhibited a positive trend for the annual WD index. The significant increasing trends of the annual WD varied from (+) 3.7 to (+) 14.5 days per decade respectively in Chabahar and Kish Island stations. Based on the results of the analysis, apart from a few stations and more specifically in Shahrekord station, joint quantities of temperature and precipitation indicates almost the same trend and responding to these differences definitely requires further investigation. At the same time, the occurrence of TCI and UTCI in the range strong heat stress (32-38 °C) events has increased almost over the whole country, which is consistent with the increase of the frequency of warm modes. The distribution of the annual compound indices trends indicated that the negative and positive significant trends have mainly occurred in the northwest of Iran. The results also suggested the need for further investigation on local factors intervention in the environment, which could be one of the major causes of climate change.

Keywords

• Climate change
• Compound indices
• Trend
• Iran

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