تحلیل آنتروپی شدت صدکی امواج گرمایی تابستانه با استفاده از توابع پارامتریک در ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

پژوهشگاه هواشناسی و علوم جو، تهران، ایران.

چکیده

گرمایش زمین، سبب افزایش شدت و فراوانی پدیده‌های حدی از جمله امواج گرمایی شده است. میزان تأثیرات امواج گرمایی وابسته به پارامترهای تداوم، فراوانی، شدت و وسعت منطقه درگیر پدیده است. در این پژوهش شاخص شدت موج گرمایی با استفاده از مفهوم آنتروپی، متناسب با انحراف از آستانه دمایی و احتمال وقوع آن در هر منطقه از ایران تعریف شد. برای محاسبه این شاخص، از توابع پارامتریک توزیع احتمال دمای متوسط روزانه، در ماهای گرم سال متناسب با هر منطقه استفاده شد. از یک شبکه منظم برای متوسط دمای طی دوره 2011-2021 استفاده شد. توابع توزیع احتمال مختلفی مورد آزمون قرار گرفت و نتایج نشان داد در اغلب مناطق ایران تابع توزیع احتمال ویبول مناسب است. احتمال وقوع این پدیده در اغلب مناطق ایران یکبار در سال است. به غیر از مناطق جنوب‌شرقی ایران، بیشترین فراوانی و گسترده‌ترین امواج گرمایی در ماه جولای رخ داده است. به غیر از یک ناحیه مرکزی، در اکثر نواحی ایران میانگین تداوم امواج گرمایی حداکثر 4 روز است. میانگین هندسی اندازه شدت موج گرمایی نشان داد، مقدار شدت در مناطق مختلف کشور متفاوت و بیشترین مقادیر آن در سواحل جنوبی به بیش از 80 درصد می­رسد. وسعت مناطق درگیر رخداد پدیده موج گرمایی در سال­های اخیر علاوه‌بر افزایش، با شدت بزرگ‌تری همراه بوده است. بیشترین وسعت مناطق در برگیرنده پدیده­های امواج گرمایی، اکثرا مناطق مرکزی و نوار شرقی کشور را در برمی‌گیرند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Entropy-Based Analysis of Summer Heatwave Intensity Percentiles Using Parametric Functions across Iran

نویسندگان [English]

  • Mojtaba Shokouhi
  • Mehdi Mesrizadeh
  • Ebrahim Asadi Oskouei
Research Institute of Meteorology and Atmospheric Science (RIMAS), Tehran, Iran.
چکیده [English]

Global warming has contributed to an increase in both the intensity and frequency of extreme climatic events, including heat waves. The impacts of heatwaves are influenced by various parameters such as duration, frequency, intensity, magnitude and the spatial extent of the affected area. In this study, a nonlinear index was developed to quantify heatwave intensity, based on the probability distribution of daily temperatures in each region. The proposed Heatwave Intensity Index (HII) is derived using the concept of entropy and is proportional to the deviation from a temperature threshold. This threshold is determined from a parametric probability distribution function fitted to daily average temperature data for each region of Iran during the period 2011–2021. The index was evaluated in terms of intensity, duration, and spatial extent.
Daily average temperature data at a 2-meter height were employed over the entire area of Iran, with each grid cell treated as an individual study unit. A heatwave event was defined as a period of at least three consecutive days with daily average temperatures exceeding the 95th percentile of the warm-season (June–September) temperature distribution. The 95th percentile threshold for each region was derived from the best-fitting continuous parametric probability distribution function. Four distribution types were tested: normal, log-normal, Weibull, and gamma, and the one that best represented the observed data in each selected region.
The Weibull distribution provided the best fit for more than 85% of Iran’s territory. In contrast, less than 10% of the areas, primarily along the northern and southern coasts, as well as Ardabil and large parts of East Azerbaijan provinces, were best described by normal or log-normal distributions. The highest temperature thresholds, exceeding 43°C, were observed in southwestern Iran, particularly in Khuzestan, southern Ilam, and central regions of the Lut Desert. Given the geographical diversity and varying climatic conditions across Iran, applying a single, fixed temperature threshold for the entire country is not appropriate. Instead, region-specific thresholds should be used to accurately identify heatwave events. In areas with historically low heatwave frequency, return periods are estimated to range from 4 to 5 years, whereas regions with higher frequencies may experience heatwaves at least three times every two years. Except for southeastern Iran, the highest frequency and broadest spatial extent of heatwaves were observed in July. Except for one central region, the average heatwave duration in most areas did not exceed four days. In the years 2019 and 2021, the intensity and frequency of heatwave events were higher compared to other years. The results show that during the heatwave days in 2021, the heatwaves were more intense, and a larger area was affected by it than that in 2019. It can be said that, given the rising temperature trend in the later years of the study period, the magnitude of heatwave intensity has also increased. The geometric mean of the HII varied significantly across Iran, with the highest values exceeding 80 units recorded along the southern coastline. In recent years, both the spatial extent and the intensity of heatwave events have increased. The most expansive heatwaves primarily affected the central and eastern border regions of the country.

کلیدواژه‌ها [English]

  • Geometric mean
  • Global warming
  • Heatwave Intensity Index
  • Weibull distribution function
بهاروندی، ن.؛ مجرد، ف. و معصوم پور، ج. (1399). شناسایی امواج گرمایی و تحلیل تغییرات زمانی-مکانی آنها در ایران. نشریه تحقیقات کاربردی علوم جغرافیایی، 20(59)، 39- 58.
دارند، م. (1393). شناسایی و تحلیل زمانی- مکانی امواج‌ گرمایی ایران زمین. مجله جغرافیا و توسعه، 12(35)، 167–180.
دوستان، ر.؛ اعتمادیان، ا. و زرین، آ. (1399). نواحی امواج گرمایی ایران. پژوهش‌های اقلیم‌شناسی، 11(42)،17–30.
Akaike, H. (2011). Akaike’s Information Criterion. BT-International Encyclopedia of Statistical Science (p. 25). https://doi.org/10.1007/978-3-642-04898-2_110.
Asadi Oskouei, E., Pakdaman, M., Falamarzi, Y., & Javanshiri, Z. (2024). A hybrid approach for generating daily 2m temperature of 1km spatial resolution over Iran. Theoretical and Applied Climatology, 155(8), 7109–7119. https://doi.org/10.1007/s00704-024-05042-1
Awasthi, A., Vishwakarma, K., & Pattnayak, K. C. (2022). Retrospection of heatwave and heat index. Theoretical and Applied Climatology, 147(1), 589–604.
Błażejczyk, K., Jendritzky, G., Bröde, P., Fiala, D., Havenith, G., Epstein, Y., Psikuta, A., & Kampmann, B. (2013). An introduction to the universal thermal climate index (UTCI). Geographia Polonica, 86(1), 5–10.
Díaz-Poso, A., Lorenzo, N., & Royé, D. (2023). Spatio-temporal evolution of heat waves severity and expansion across the Iberian Peninsula and Balearic islands. Environmental Research, 217, 114864.
García-León, D., Casanueva, A., Standardi, G., Burgstall, A., Flouris, A. D., & Nybo, L. (2021). Current and projected regional economic impacts of heatwaves in Europe. Nature Communications, 12(1), 5807. https://doi.org/https://doi.org/10.1038/s41467-021-26050-z
Huang, H., Jie, P., Yang, Y., & Mi, S. (2022). Spatial and temporal characteristics of high-temperature heat wave disasters in Chongqing. Atmosphere, 13(9), 1396.
IPCC, I. P. on C. C. (2023). Climate Change 2022 – Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. https://doi.org/DOI: 10.1017/9781009325844
Lee, H., Calvin, K., Dasgupta, D., Krinmer, G., Mukherji, A., Thorne, P., Trisos, C., Romero, J., Aldunce, P., & Barret, K. (2023). Synthesis report of the IPCC Sixth Assessment Report (AR6), Longer report. IPCC.
Liss, A., Wu, R., Chui, K. K. H., & Naumova, E. N. (2017). Heat-related hospitalizations in older adults: An amplified effect of the first seasonal heatwave. Scientific Reports, 7(1), 39581.
Martinez-Villalobos, C., Fu, D., Loikith, P. C., & Neelin, J. D. (2025). Accelerating increase in the duration of heatwaves under global warming. Nature Geoscience, 18(8), 716–723.
Massey Jr, F. J. (1951). The Kolmogorov-Smirnov test for goodness of fit. Journal of the American Statistical Association, 46(253), 68–78.
Mazdiyasni, O., Sadegh, M., Chiang, F., & AghaKouchak, A. (2019). Heat wave intensity duration frequency curve: A multivariate approach for hazard and attribution analysis. Scientific Reports, 9(1), 14117.
Mohammad, P., & Weng, Q. (2024). Comparing existing heat wave indices in identifying dangerous heat wave outdoor conditions. Nexus, 1(3), 100027.
Pan, J.-X., Fang, K.-T., Pan, J.-X., & Fang, K.-T. (2002). Maximum likelihood estimation. Growth Curve Models and Statistical Diagnostics, 77–158.
Radinović, D., & Ćurić, M. (2012). Criteria for heat and cold wave duration indexes. Theoretical and Applied Climatology, 107, 505–510.
Raei, E., Nikoo, M. R., AghaKouchak, A., Mazdiyasni, O., & Sadegh, M. (2018). GHWR, a multi-method global heatwave and warm-spell record and toolbox. Scientific Data, 5(1), 1–15.
Roshan, G., Ghanghermeh, A., & Kong, Q. (2018). Spatial and temporal analysis of outdoor human thermal comfort during heat and cold waves in Iran. Weather and Climate Extremes, 19, 58–67.
Royé, D., Codesido, R., Tobías, A., & Taracido, M. (2020). Heat wave intensity and daily mortality in four of the largest cities of Spain. Environmental Research, 182, 109027.
Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal, 27(3), 379–423.
Skinner, C. B., Touma, D., Barlow, M., Singh, D., & King, T. (2025). The spatial extent of heat waves has changed over the past four decades. Communications Earth & Environment, 6(1), 662.
Spangler, K. R., Liang, S., & Wellenius, G. A. (2022). Wet-bulb globe temperature, universal thermal climate index, and other heat metrics for US Counties, 2000–2020. Scientific Data, 9(1), 326.
Sridevi, C., Routray, A., Ramarao, M. V. S., Dutta, S., Prasad, K. H., Colón, E., Gibbs, A., Pondeca, M., & Prasad, V. S. (2024). Study of Heat Wave Using High‐Resolution Real Time Meso‐Scale Analysis Over India. Geophysical Research Letters, 51(17), e2024GL109310.
World Health Organization. (2023). Climate change and health: Heat and health. https://www.who.int/news-room/fact-sheets/detail/climate-change-heat-and-health
Xu, Z., FitzGerald, G., Guo, Y., Jalaludin, B., & Tong, S. (2016). Impact of heatwave on mortality under different heatwave definitions: a systematic review and meta-analysis. Environment International, 89, 193–203.