Determining the Temperature Threshold of the Heat Wave during the Warm Period of the Year Based on Global Index in Different Regions of the Country

جغرافیا و مخاطرات محیطی

Article 7, Volume 7, Issue 2 - Serial Number 26, January 2019, Pages 115-132   

Document Type: Research Article

DOI: 10.22067/geo.v7i3.64584

Authors

Fereshteh Rezaie^* ; Mahmoud Ahmadi; Alireza Shakiba

Shahid Beheshti University

Abstract

Introduction

Heat waves as a climatic extreme phenomenon had more occurrence in recent years in which case it is an evidence of the earth climate change. The heat wave is generally defined as a period of consecutive days with unusual high temperatures which has become a common risk in the world due to its effects on the nature and human beings, including health, hygiene, water resources, and agriculture. The identification of these effects requires recognizing the heat wave and determining its thresholds. Due to the climate change, heat waves can occur more intensely with higher frequency  longer than before (Esmailnejad, 2013; Jinghong et al., 2015; Keggenhoff et al., 2015; Rusticucci et al., 2015).

Materials and Methods

The research attempts to determine the temperature threshold of the heat wave in different regions of the country during the warm period of the year. To meet this purpose of the study, the statistics of daily maximum temperature of the 90 synoptic stations during the statistical period of 1986-2015 from April to September was collected through the country's meteorological organization. After the primary processing of raw data, the temperature threshold of the heat wave during the warm period of the year was then determined based on three global indexes (Percentile 95, Baldy, World Meteorological Organization).
Baldy indicator: Tmax daily ≥ Tmean max daily + 1.5 sdmax daily
To determine the temperature threshold necessary for extracting the heat waves according to Baldy indicator, first the mean and standard deviation of daily maximum temperature of each station were calculated. Next, the relation of Tmean max daily + 1.5 sdmax dail was calculated as a dot for each station and it gained one threshold as such. Finally, the days which their maximum temperature of each station is   ≥ p 95 and at least continue for a few consecutive days are named as heat wave.
Percentile 95 index: when the daily maximum temperature is equal or larger than percentile 95 and continues at least for 2 days, it is known as a heat wave.
 
World Meteorological Organization (WMO) index: when daily maximum temperature is 5°c more than a long term mean for 5 consecutive days, it is defined as a heat wave.
 
Fomyaki index (NTD): when the temperature is +2 standard deviation from mean (NTD) and continues at least for 2 days, it is defined as a heat wave.

Results and Discussion

The purpose of using different indexes was to select the appropriate index and finally to determine the threshold according to that index. To determine which index is more appropriate to define the threshold, first it was necessary to measure the ability of these indexes to extract the heat waves. But after using the indexes in question and extracting the heat waves by these methods, it was found that these indexes have the ability to detect heat waves. Although it may differ in terms of the characteristic of heat waves such as continuity, intensity, and extent, the main problem is that these indexes do not show an equal threshold. Therefore, although the results of each of these indexes according to the basis of scientific and statistical rules are valid, it is not possible to select an index as a arbitrarily better and more appropriate index and determine the temperature threshold based on it. Consequently, the smallest threshold was considered among the different thresholds for each station in order to determine the final threshold. In addition, the days which were equal or larger than this threshold was selected as a hot and wave day. It is important to note that because the output of Fomyaki index (NTD) is a coefficient, the index was not used to determine the final threshold; it was only used as a confirmative index to investigate the heat wave occurrence. Then in ArcGIS environment using a hybrid method of IDW and regression, the temperature threshold was interpolated for the whole country, considering the latitude and altitude (as the two important and effective factors in the amount of the temperature threshold of the heat wave).The results showed that the temperature thresholds in the country's different times and places are not the same in the warm period of the year, and they have different ranges.

Conclusions

 The temperature threshold ranged between 15 - 40 Celsius in April, between 21-46 Celsius in May, between Celsius 25-50 in June, between 29- 49 Celsius in July, between 32- 52 Celsius in August, and between 27- 47 Celsius in September. In the months of April, May, and September, the temperature threshold is higher from the local differences, while in the months of June and July and August it has almost the relative uniformity, which is due to the presence of Azores subtropical high pressure which dominates all parts of Iran from the south of Alborz Mountains. On the other hand, this phenomenon decreases the effect of local factors such as altitude and latitude on the value of temperature threshold in these months leading relative integration in temperature threshold. Also, the results show that the highest temperature threshold of the heat wave in the warm period of the year is related to Khozestan Province and the lowest temperature threshold of the heat wave is related to the parts of the north and north west of the country. The results of this research indicate this scientific fact that in order to obtain accurate temperature threshold for different regions of the country, different indices should be used because these indicators complete each other, and we cannot achieve the accurate results in this field by using just one index.

Keywords

Keywords: Heat wave; Temperature threshold parameters; Latitude; Altitude; Iran

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