شناخت الگوهای مکانی مخاطرات دمایی استان قزوین

جغرافیا و مخاطرات محیطی

مقاله 11، دوره 13، شماره 3 - شماره پیاپی 51، آبان 1403، صفحه 280-309   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.22067/geoeh.2023.83713.1401

نویسندگان

منصوره کوهی؛ ابراهیم اسعدی اسکویی^*

استادیار، پژوهشگاه هواشناسی و علوم جو، پژوهشکده اقلیم شناسی، مشهد، ایران

چکیده

مخاطرات اقلیمی به‌ویژه انواع دمایی آن، دارای اثرات منفی بر بخش­های مختلف فعالیت‌های بشر هستند. ازآنجایی‌که انتظار می­رود تغییرات اقلیمی منجر به تشدید فراوانی، شدت و مدت مخاطرات اقلیمی شود؛ لذا ضروری است استراتژی­هایی همچون استخراج الگوهای مخاطرات اقلیمی به‌منظور افزایش تاب­آوری مراکز جمعیتی، صنعتی و کشاورزی در برابر تغییر اقلیم و افزایش رخدادهای فرین و سازگاری با این رویدادها، مدنظر تصمیم­گیران، برنامه­ریزان و سیاست­گذاران قرار گیرد. استان قزوین با توجه به موقعیت جغرافیایی، وسعت کم، توپوگرافی خاص و شرایط اقلیمی متنوع، هرساله شاهد وقوع پدیده­های مخرب جوی در فصول مختلف می­باشد که خسارات جانی و مالی زیادی را در بخش­های مختلف همچون کشاورزی به همراه داشته است.
 در این پژوهش، داده­های شبکه­ای دمای بازتحلیل ERA5-Land با قدرت تفکیک مکانی 9 کیلومتر طی دوره 2020-1991 برای بررسی توزیع مکانی نمایه­های مرتبط با مخاطرات اقلیمی دمایی سرد و گرم شامل روزهای یخبندان (FD)، روزهای یخی (ID) ، شب­های حاره­ای  (TR)، نمایه طول دوره گرما  (WSDI)و سرما (CSDI) و روزهایی با دمای بیشینه بیش از C° 35 (TXge35) استفاده و نقشه مخاطرات چندگانه تهیه شد.
بررسی­ ها نشان داد منطقه مرکزی استان قزوین در معرض چندین نوع خطر (TXge35،CSDI،FD و TR) به­طور هم‌زمان قرار دارد که با توجه به تراکم جمعیت شهری و روستایی و تمرکز فعالیت­های اقتصادی در این ناحیه، انتظار می­رود ریسک­های اقتصادی-اجتماعی مرتبط با مخاطرات اقلیمی در این ناحیه شدت یابد.

کلیدواژه‌ها

تأثیرات تغییر اقلیم؛ ارزیابی مخاطرات اقلیمی؛ کاهش خطر بلایا؛ راهبردهای سازگاری با اقلیم؛ نقشه‌برداری چندمخاطره‌ای؛ آسیب‌پذیری اجتماعی-اقتصادی

مراجع

Alijani, B., O’Brien, J., & Yarnal, B. (2008). Spatial analysis of precipitation intensity and concentration in Iran. Theoretical and Applied climatology, 94, 107-124. [In Persian] https://doi.org/10.1007/s00704-007-0344-y

Arabi Yazdi, A., Sanaei Nejad, S. H., & Mofidi, A. (2020). Evaluation of Grid reanalysis products of the European Centre for Medium Range Weather Forecasts (ECMWF datasets) in Different Climatic Regions of Iran. Journal of Climate Research, 1398(38), 63-76. [In Persian] https://clima.irimo.ir/article_113320.html?

Arce, C., & Uribe, E. (2015). Managing Vulnerability and Boosting Productivity in Agriculture through Weather Risk Mapping, World Bank Group Report, Number 92400.

Asadi Oskouei, E., Delsouz Khaki, B., Kouzegaran, S., Navidi, M. N., Haghighatd, M., Davatgar, N., & Lopez-Baeza, E. (2022). Mapping Climate Zones of Iran Using Hybrid Interpolation Methods. Remote Sensing,14(11), 2632. https://doi.org/10.3390/rs14112632

Asadi Oskouei, E., Kouzegaran, S., Kouhi, M., Hokmabadi, H., & Eslami, M. (2023). Spatial Distribution of the Probability of Satisfying the Chill Requirements of Pistachio in Iran Using ERA5-Land Reanalysis Data. Nivar, 47(120-121), 137-152. [In Persian] https://doi.org/10.30467/NIVAR.2023.416976.1263

Azizi Mobaser, J., Rasoulzadeh, A., Rahmati, A., Shayeghi, A., & Bakhtar, A. (2021). Evaluating the Performance of Era-5 Re-Analysis Data in Estimating Daily and Monthly Precipitation, Case Study; Ardabil Province. Iranian Journal of Soil and Water Research, 51(11), 2937-2951.[In Persian] https://doi.org/10.22059/ijswr.2020.302176.668600

Azizi, G., Safarrad, T., Mohammadi, H., & Faraji Sabokbar, H. (2016). Evaluation and Comparison of Reanalysis Precipitation Data in Iran. Physical Geography Research, 48(1), 33-49. [In Persian] https://doi.org/10.22059/jphgr.2016.57026

Behyar, M. (2015). Spatial Analysis and Zoning Climatic Hazards of Threshold Rainfall Indicator in Road Network of Iran Using GIS. Nivar, 39(90-91), 37-44.[In Persian] https://doi.org/10.30467/nivar.2015.15688

Burkart, K. G., Brauer, M., Aravkin, A. Y., Godwin, W. W., Hay, S. I., He, J., ... & Stanaway, J. D. (2021). Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study. The Lancet, 398(10301), 685-697. https://doi.org/10.1016/S0140-6736(21)01700-1

Burke, M., Hsiang, S. M., & Miguel, E. (2015). Global non-linear effect of temperature on economic production. Nature, 527(7577), 235-239. https://doi.org/10.1038/nature15725

Cao, B., Gruber, S., Zheng, D., & Li, X. (2020). The ERA5-Land soil temperature bias in permafrost regions. The Cryosphere, 14(8), 2581-2595. https://doi.org/10.5194/tc-14- 2581-2020.

Caprio, J. M., & Quamme, H. A. (1999). Weather conditions associated with apple production in the Okanagan Valley of British Columbia. Canadian Journal of Plant Science, 79(1), 129-137. https://doi.org/10.4141/P98-028

Chen, Y., Sharma, S., Zhou, X., Yang, K., Li, X., Niu, X., & Khadka, N. (2021). Spatial performance of multiple reanalysis precipitation datasets on the southern slope of central Himalaya. Atmospheric Research, 250, 105365. https://doi.org/10.1016/j.atmosres.2020.10536

CRED. (2018). Natural disasters 2017, Brussels.

Crespi, A., Terzi, S., Cocuccioni, S., Zebisch, M., Berckmans, J., & Füssel, H. M. (2020). Climate-related hazard indices for Europe. European Environment Agency, European Topic Centre Climate Change Impacts, Vulnerability and Adaptation.

Easterling, D. R. (1989). Regionalization of thunderstorm rainfall in the contiguous United States. International Journal of Climatology, 9(6), 567-579. https://doi.org/10.1002/joc.3370090603

El Morjani, Z. E. A., Ebener, S., Boos, J., Abdel Ghaffar, E., & Musani, A. (2007). Modelling the spatial distribution of five natural hazards in the context of the WHO/EMRO Atlas of Disaster Risk as a step towards the reduction of the health impact related to disasters. International Journal of Health Geographics, 6, 1-28. https://doi.org/10.1186/1476-072X-6-8

Engelstädter, S. (2001). Dust storm frequencies and their relationship to land surface conditions Doctoral dissertation, Friedrich-Schiller-Universität Jena. https://hdl.handle.net/21.11116/0000-0009-D2E6-6

Etkin, D., & Brun, S. E. (1999). A note on Canada's hail climatology: 1977–1993. International Journal of Climatology: A Journal of the Royal Meteorological Society, 19(12), 1357-1373. https://doi.org/10.1002/(SICI)1097-0088(199910)19:12%3C1357::AID-JOC422%3E3.0.CO;2-B

Fathian, F., Ghadami, M., Haghighi, P., Amini, M., Naderi, S., & Ghaedi, Z. (2020). Assessment of changes in climate extremes of temperature and precipitation over Iran. Theoretical and Applied Climatology, 141, 1119-1133. https://doi.org/10.1007/s00704-020-03269-2

Ghiami-Shamami, F., Sabziparvar, A. A., & Shinoda, S. (2019). Long-term comparison of the climate extremes variability in different climate types located in coastal and inland regions of Iran. Theoretical and Applied Climatology, 136, 875-897. https://doi.org/10.1007/s00704-018-2523-4

Golian, S., Mazdiyasni, O., & AghaKouchak, A. (2015). Trends in meteorological and agricultural droughts in Iran. Theoretical and Applied Climatology, 119, 679-688. https://doi.org/10.1007/s00704-014-1139-6

Gupta, H. V., Kling, H., Yilmaz, K. K., & Martinez, G. F. (2009). Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. Journal of Hydrology, 377(1-2), 80-91. https://doi.org/10.1016/j.jhydrol.2009.08.003

Helali, J., Asadi Oskouei, E., Hosseinzaheh, T., Kouhi, M., & Mohammadi, S. M. (2023). Spatio-temporal analysis of seasonal and annual trends of dust storm days in arid climates of Iran. Iranian Journal of Soil and Water Research, 54(3), 513-531.[In Persian] https://doi.org/10.22059/ijswr.2023.355469.669454

Helali, J., Oskouei, E. A., Hosseini, S. A., Saeidi, V., & Modirian, R. (2022). Projection of changes in late spring frost based on CMIP6 models and SSP scenarios over cold regions of Iran. Theoretical and Applied Climatology, 149(3), 1405-1418. https://doi.org/10.1007/s00704-022-04124-2

Hijmans, R. J., Van Etten, J., Cheng, J., Mattiuzzi, M., Sumner, M., Greenberg, J. A., ... & Hijmans, M. R. J. (2023). Package ‘raster’. R package, 734, 473. http://www.maths.bristol.ac.uk/R/web/packages/raster/raster.pdf

Huai, B., Wang, J., Sun, W., Wang, Y., & Zhang, W. (2021). Evaluation of the near-surface climate of the recent global atmospheric reanalysis for Qilian Mountains, Qinghai-Tibet Plateau. Atmospheric Research, 250, 105401. https://doi.org/10.1016/j.atmosres.2020.105401

IPCC. (2021).Climate Change 2021-The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Intergovernmental Panel on Climate Change, Geneva Understanding the spatial patterns of temperature hazards in Qazvin province. https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_SummaryVolume.pdf

Karl, T. R., Nicholls, N., & Ghazi, A. (1999). Clivar/GCOS/WMO workshop on indices and indicators for climate extremes: workshop summary. Weather and climate extremes, Springer. https://doi.org/10.1007/978-94-015-9265-9_2

Kaur, A., & Sood, S. K. (2019). Analytical mapping of research on disaster management, types and role of ICT during 2011–2018. Environmental Hazards, 18(3), 266-285. https://doi.org/10.1080/17477891.2019.1567457

Lancet. (2021). Health in a world of extreme heat. Lancet (London, England), 398(10301), 641. https://doi.org/10.1016/s0140-6736(21)01860-2

Ma, C. C. Y., & Iqbal, M. (1984). Statistical comparison of solar radiation correlations Monthly average global and diffuse radiation on horizontal surfaces. Solar Energy, 33(2), 143-148. https://doi.org/10.1016/0038-092X(84)90231-7

Maes, M. J., Gonzales-Hishinuma, A., Haščič, I., Hoffmann, C., Banquet, A., Veneri, P., ... & Quadrelli, R. (2022). Monitoring exposure to climate-related hazards: Indicator methodology and key results, OECD. Environment Working Papers, 201, OECD Publishing, Paris. https://doi.org/10.1787/19970900

Mofidi, A., Hosseinzadeh, S., & Mohammadyarian, M. (2013). Atmospheric Hazards Zonation in the Northeastren of Iran. Journal of Geography and Environmental Hazards, 2(2), 1-16. [In Persian] https://doi.org/10.22067/geo.v0i0.23110

Mofidi, A., Zarrin, A., & Janbaz Ghobadi, G. (2008). Determining the synoptic pattern of autumn heavy and extreme precipitations on the southern coast of the Caspian Sea. Journal of the Earth and Space Physics, 33(3), 131-154. [In Persian] https://dorl.net/dor/20.1001.1.2538371.1386.33.3.10.7

Mohanty, U. C., & Mohapatra, M. (2007). Prediction of occurrence and quantity of daily summer monsoon precipitation over Orissa (India). Meteorological Applications: A journal of Forecasting, Practical Applications, Training Techniques and Modelling, 14(1), 95-103. https://doi.org/10.1002/met.9

Poméon, T., Jackisch, D., & Diekkrüger, B. (2017). Evaluating the performance of remotely sensed and reanalysed precipitation data over West Africa using HBV light. Journal of Hydrology, 547, 222-235. https://doi.org/10.1016/j.jhydrol.2017.01.055

Salahi, B., Goudarzi, M., & Hosseini, S. A. (2016). Predicting the temperature and precipitation changes during the 2050s in Urmia Lake Basin. Watershed Engineering and Management, 8(4), 425-438. [In Persian] https://doi.org/10.22092/ijwmse.2016.107179

Sam Khaniani, A., & Mohammadi, A. (2022). Comparison of ERA5-Land reanalysis data with surface observations over Iran. Iranian Journal of Geophysics, 16(1), 195-212. [In Persian] https://doi.org/10.30499/ijg.2022.313494.1376

Shi, P. (2019). Disaster risk science. Springer.

Shi, P., & Kasperson, R. (2015). World atlas of natural disaster risk. Springer.

Shokri Koochak, S., Akhond Ali, A. M., & Sharifi, M. R. (2019). Introduction and comparison of the performance of two global reanalysis databases in estimating daily maximum, minimum, and average air temperatures (case study: Helleh River basin). Iranian Journal of Geophysics, 13(3), 53-68. [In Persian] https://dor.isc.ac/dor/20.1001.1.20080336.1398.13.3.4.4

Siteva, D., & Marinova, S. (2021). Design of an Atlas of Significant Natural Disasters. In Proceedings of the ICA (Vol. 4). Göttingen, Germany: Copernicus Publications. https://doi.org/10.5194/ica-proc-4-100-2021

Soltani, A., Alaedini, F., Shamspour, N., & Ahmadi Marzaleh, M. (2021). Hazard Assessment of Iran Provinces based on the Health Ministry Tool in 2019. Iranian Red Crescent Medical Journal, 23(1), e204. https://doi.org/10.32592/ircmj.2021.23.1.204

Tarek, M., Brissette, F. P., & Arsenault, R. (2020). Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America. Hydrology and Earth System Sciences, 24(5), 2527-2544. https://doi.org/10.5194/hess-24-2527-2020

Trambauer, P., Dutra, E., Maskey, S., Werner, M., Pappenberger, F., Van Beek, L. P. H., & Uhlenbrook, S. (2014). Comparison of different evaporation estimates over the African continent. Hydrology and Earth System Sciences, 18(1), 193-212. https://doi.org/10.5194/hess-18-193-2014

UNDRR. (2020). Hazard definition & classification review: Technical report, United Nations Office for Disaster Risk Reduction, New York and Geneva. https://www.undrr.org/quick/12955

UNISDR. (2004). Living with risk: A global review of disaster reduction initiatives. United Nations Office for Disaster Risk Reduction, New York and Geneva. https://www.undrr.org/quick/10883

Vazife dost , M., & Laleh syah, M. (2013). Analysis of the spatial and temporal climatic disasters affecting the road. Journal of Transportation Research, 10(3). [In Persian] https://www.trijournal.ir/article_11499.html?

Wang, Y. R., Hessen, D. O., Samset, B. H., & Stordal, F. (2022). Evaluating global and regional land warming trends in the past decades with both MODIS and ERA5-Land land surface temperature data. Remote Sensing of Environment, 280, 113181. https://doi.org/10.1016/j.rse.2022.113181

Willmott, C. J., & Matsuura, K. (2006). On the use of dimensioned measures of error to evaluate the performance of spatial interpolators. International Journal of Geographical Information Science, 20(1), 89-102. https://doi.org/10.1080/13658810500286976

Wypych, A., Ustrnul, Z., & Henek, E. (2014). Meteorological hazards-visualization system for national protection against extreme hazards for Poland. Meteorology Hydrology and Water Management. Research and Operational Applications, 2(1), 37-42. https://doi.org/10.26491/mhwm/28306

Xue, C., Wu, H., & Jiang, X. (2019). Temporal and spatial change monitoring of drought grade based on ERA5 analysis data and BFAST method in the belt and road area during 1989–2017. Advances in Meteorology, 2019(1), 4053718. https://doi.org/10.1155/2019/4053718

Yilmaz, M. (2023). Accuracy assessment of temperature trends from ERA5 and ERA5-Land. Science of The Total Environment, 856, 159182. https://doi.org/10.1016/j.scitotenv.2022.159182