Investigating Precipitation Return Period and its Probability of Occurrence in Iran based on Multi-Source Weighted-Ensemble Precipitation (MSWEP)

جغرافیا و مخاطرات محیطی

Article 11, Volume 10, Issue 4 - Serial Number 40, February 2022, Pages 209-227   

Document Type: Research Article

DOI: 10.22067/geoeh.2021.71102.1079

Authors

Azar Zarrin^* ; AbbasAli Dadashi Roudbari

Department of Geography, Ferdowsi University of Mashhad, Mashhad, Iran

Abstract

Return periods and the probability of the occurrence of precipitation are two important indicators in studies related to flooding and precipitation, and a correct understanding of the indicators can play an important role in climate risk studies. This study aimed to investigate the performance of the Multi-Source Weighted-Ensemble Precipitation (MSWEP) and to use it in determining the return periods and the probability of annual precipitation in Iran. For this purpose, the generalized extreme value (GEV) method was used. Four statistics of RMSE, MBE, PBIAS, and R² in Köppen-Geiger climate classification in Iran were used to evaluate the MSWEP data. The results showed that this data has the best performance in arid and semi-arid regions of the country with a PBIAS of 0.40 and 0.32. In contrast, this data showed the least performance in two rainy (Cfa) and mountainous areas (Dsb), so that the maximum PBIAS between the climate zones of the country is seen between -2.45 and -0.09% in the above-mentioned zones, respectively. The results showed that the maximum probable precipitation occurs in periods of 1 to 15 years in the northern coasts and its maximum intensity occurs in the southern coasts of Iran. The probability of occurrence of precipitation in Iran fluctuates between 2.03 to 32.02%. Decreasing latitude from north to south and decreasing height from west to east are associated with a decrease in the probability of occurrence of precipitation in Iran. Maximum uncertainty is seen in the mountainous regions of Iran with a high probability of occurrence of precipitation.

Keywords

Generalized Extreme Value (GEV); Iran; MSWEP; Precipitation Return Period; Precipitation

References

ذوالفقاری، حسن؛ هاشمی، رضا؛ فشی، مهدی؛ 1388. بررسی نسبت حداکثر بارش­های روزانه به بارش­های سالانه در ایران. تحقیقات جغرافیایی. شماره 24. صص 165-188.

رحیم­زاده، فاطمه؛ نسجای­زواره، مجتبی؛ 1393. روند و تغییرپذیری دما در ایران در دوره 2010-1960 پس از تعدیل ناهمگنی­های غیرطبیعی موجود در داده­ها. تحقیقات جغرافیایی. شماره 29. صص 181-196.

رضیئی، طیب؛ 1396. منطقه‌بندی اقلیمی ایران به روش کوپن-گایگر و بررسی جابه‌جایی مناطق اقلیمی کشور در سدۀ بیستم. فیزیک زمین و فضا. شماره 43. صص 419-439.

رضیئی، طیب؛ ستوده، فاطمه؛ 1396. بررسی دقت مرکز اروپایی پیش‌بینی‌های میان‌مدت جوی (ECMWF) در پیش‌بینی بارش مناطق گوناگون اقلیمی ایران. فیزیک زمین و فضا. شماره 43. صص 133-147.

عساکره، حسین؛ 1391. تغییر توزیع فراوانی بارش‌های فرین شهر زنجان. جغرافیا و برنامه‌ریزی محیطی. شماره 23. صص 51-66.

گرجی زاده، علی؛ آخوندعلی، علی‌محمد؛ شهبازی، علی؛ مریدی، علی؛ 1398. مقایسه و ارزیابی بارش برآورد شده توسط مدل‌های ERA-Interim، PERSIANN-CDR و CHIRPS در بالادست سد مارون. تحقیقات منابع آب ایران. شماره 15. صص 267-279.

مظفری، غلامعلی؛ مزیدی، احمد؛ شفیعی، شهاب؛ 1396. واکاوی روابط فضایی بارش‌های فرین غرب ایران. جغرافیا و توسعه. شماره 46. صص 169-183.

میری، مرتضی؛ رضیئی، طیب؛ رحیمی، مجتبی؛ 1395. ارزیابی و مقایسه آماری داده‌های بارش TRMM و GPCC با داده‌های مشاهده‌ای در ایران. فیزیک زمین و فضا. شماره 42. صص 657-672.

 

Acero, F. J., García, J. A., & Gallego, M. C., 2011. Peaks-over-threshold study of trends in extreme rainfall over the Iberian Peninsula. Journal of Climate, 24: 1089-1105.

AghaKouchak, A., Behrangi, A., Sorooshian, S., Hsu, K., & Amitai, E., 2011. Evaluation of satellite‐retrieved extreme precipitation rates across the central United States. Journal of Geophysical Research: Atmospheres, 116(D2).

Alexandersson, H., 1986. A homogeneity test applied to precipitation data. Journal of climatology, 6: 661-675.

Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. G., Van Dijk, A. I., ... & Adler, R. F., 2019. MSWEP V2 global 3-hourly 0.1 precipitation: methodology and quantitative assessment. Bulletin of the American Meteorological Society, 100: 473-500.

Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., & Wood, E. F., 2018. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Scientific data, 5: 1-12.

Bishop, C. H., & Abramowitz, G., 2013. Climate model dependence and the replicate Earth paradigm. Climate dynamics, 41: 885-900.

Bosilovich, M. G., Chen, J., Robertson, F. R., & Adler, R. F., 2008. Evaluation of global precipitation in reanalyses. Journal of applied meteorology and climatology, 47: 2279-2299.

Coles, S., Bawa, J., Trenner, L., & Dorazio, P., 2001. An introduction to statistical modeling of extreme values (Vol. 208, p. 208). London: Springer.

De Paola, F., Giugni, M., Pugliese, F., Annis, A., & Nardi, F., 2018. GEV parameter estimation and stationery vs. non-stationary analysis of extreme rainfall in African test cities. Hydrology, 5: 28.

DeGaetano, A. T., 2009. Time-dependent changes in extreme-precipitation return-period amounts in the continental United States. Journal of Applied Meteorology and Climatology, 48: 2086-2099.

Fang, J., Yang, W., Luan, Y., Du, J., Lin, A., & Zhao, L., 2019. Evaluation of the TRMM 3B42 and GPM IMERG products for extreme precipitation analysis over China. Atmospheric Research, 223: 24-38.

Gao, M., Mo, D., & Wu, X., 2016. Nonstationary modeling of extreme precipitation in China. Atmospheric Research, 182: 1-9.

Groisman, P. Y., Knight, R. W., Easterling, D. R., Karl, T. R., Hegerl, G. C., & Razuvaev, V. N., 2005. Trends in intense precipitation in the climate record. Journal of climate, 18: 1326-1350.

Hirpa, F. A., Salamon, P., Alfieri, L., Pozo, J. T. D., Zsoter, E., & Pappenberger, F., 2016. The effect of reference climatology on global flood forecasting. Journal of Hydrometeorology, 17: 1131-1145.

Katz, R. W., Parlange, M. B., & Naveau, P., 2002. Statistics of extremes in hydrology. Advances in water resources, 25: 1287-1304.

Khaliq, M. N., Ouarda, T. B., Ondo, J. C., Gachon, P., & Bobée, B., 2006. Frequency analysis of a sequence of dependent and/or non-stationary hydro-meteorological observations: A review. Journal of hydrology, 329: 534-552.

Kharin, V. V., Zwiers, F. W., Zhang, X., & Wehner, M., 2013. Changes in temperature and precipitation extremes in the CMIP5 ensemble. Climatic change, 119: 345-357.

Kim, Y. H., Min, S. K., Zhang, X., Sillmann, J., & Sandstad, M., 2020. Evaluation of the CMIP6 multi-model ensemble for climate extreme indices. Weather and Climate Extremes, 29: 100269.

Mika, J., 2013. Changes in weather and climate extremes: phenomenology and empirical approaches. Climatic Change, 121: 15-26.

Milly, P. C. D., Betancourt, J., Falkenmark, M., Hirsch, R. M., Kundzewicz, Z. W., Lettenmaier, D. P., & Stouffer, R. J., 2008. Stationarity is dead: Whither water management? Earth, 4: 20.

Monier, E., & Gao, X., 2015. Climate change impacts on extreme events in the United States: an uncertainty analysis. Climatic Change, 131: 67-81.

Myhre, G., Alterskjær, K., Stjern, C. W., Hodnebrog, Ø., Marelle, L., Samset, B. H., ... & Stohl, A., 2019. Frequency of extreme precipitation increases extensively with event rareness under global warming. Scientific reports, 9: 1-10.

Prein, A. F., & Gobiet, A., 2017. Impacts of uncertainties in European gridded precipitation observations on regional climate analysis. International Journal of Climatology, 37: 305-327.

Rulfová, Z., Buishand, A., Roth, M., & Kyselý, J., 2016. A two-component generalized extreme value distribution for precipitation frequency analysis. Journal of hydrology, 534: 659-668.

Salas, J. D., & Obeysekera, J., 2014. Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. Journal of Hydrologic Engineering, 19: 554-568.

Soukissian, T. H., & Tsalis, C., 2015. The effect of the generalized extreme value distribution parameter estimation methods in extreme wind speed prediction. Natural Hazards, 78: 1777-1809.

Stedinger, J. R., Vogel, R. M., Foufoula-Georgiou, E., & Maidment, D. R., 1993. Handbook of hydrology. McGraw-Hill, Inc., New York, USA.

Sun, Q., Miao, C., Duan, Q., Ashouri, H., Sorooshian, S., & Hsu, K. L., 2018. A review of global precipitation data sets: Data sources, estimation, and intercomparisons. Reviews of Geophysics, 56: 79-107.

Sun, Q., Zhang, X., Zwiers, F., Westra, S., & Alexander, L. V., 2021. A global, continental, and regional analysis of changes in extreme precipitation. Journal of Climate, 34: 243-258.

Tabari, H., 2020. Climate change impact on flood and extreme precipitation increases with water availability. Scientific reports, 10: 1-10.

Vaghefi, S. A., Keykhai, M., Jahanbakhshi, F., Sheikholeslami, J., Ahmadi, A., Yang, H., & Abbaspour, K. C., 2019. The future of extreme climate in Iran. Scientific reports, 9: 1-11.

Vu, T. M., & Mishra, A. K., 2019. Nonstationary frequency analysis of the recent extreme precipitation events in the United States. Journal of Hydrology, 575: 999-1010.

Wahl, T., Jain, S., Bender, J., Meyers, S. D., & Luther, M. E., 2015. Increasing risk of compound flooding from storm surge and rainfall for major US cities. Nature Climate Change, 5: 1093-1097.

Wehner, M., Gleckler, P., & Lee, J., 2020. Characterization of long period return values of extreme daily temperature and precipitation in the CMIP6 models: Part 1, model evaluation. Weather and Climate Extremes, 30: 100283.

Xavier, A. C. F., Rudke, A. P., Fujita, T., Blain, G. C., de Morais, M. V. B., de Almeida, D. S., ... & Martins, J. A., 2020. Stationary and non‐stationary detection of extreme precipitation events and trends of average precipitation from 1980 to 2010 in the Paraná River basin, Brazil. International Journal of Climatology, 40: 1197-1212.

Yan, H., Sun, N., Wigmosta, M., Skaggs, R., Hou, Z., & Leung, L. R., 2019. Next-generation intensity–duration–frequency curves to reduce errors in peak flood design. Journal of Hydrologic Engineering, 24: 04019020.

Yozgatlıgil, C., & Türkeş, M., 2018. Extreme value analysis and forecasting of maximum precipitation amounts in the western Black Sea subregion of Turkey. International Journal of Climatology, 38: 5447-5458.

Zolina, O., Simmer, C., Kapala, A., & Gulev, S., 2005. On the robustness of the estimates of centennial‐scale variability in heavy precipitation from station data over Europe. Geophysical Research Letters, 32(14).