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برزو, فرزانه, عزیزی, قاسم. (1394). پیشنهاد معیاری ساده برای برآورد بارش سنگین در مناطق مختلف ایران. , 47(3), 347-365. doi: 10.22059/jphgr.2015.55335
فرزانه برزو; قاسم عزیزی. "پیشنهاد معیاری ساده برای برآورد بارش سنگین در مناطق مختلف ایران". , 47, 3, 1394, 347-365. doi: 10.22059/jphgr.2015.55335
برزو, فرزانه, عزیزی, قاسم. (1394). 'پیشنهاد معیاری ساده برای برآورد بارش سنگین در مناطق مختلف ایران', , 47(3), pp. 347-365. doi: 10.22059/jphgr.2015.55335
برزو, فرزانه, عزیزی, قاسم. پیشنهاد معیاری ساده برای برآورد بارش سنگین در مناطق مختلف ایران. , 1394; 47(3): 347-365. doi: 10.22059/jphgr.2015.55335

پیشنهاد معیاری ساده برای برآورد بارش سنگین در مناطق مختلف ایران

پژوهش های جغرافیای طبیعی
مقاله 3، دوره 47، شماره 3، مهر 1394، صفحه 347-365    اصل مقاله (897.7 K)
نوع مقاله: مقاله کامل
شناسه دیجیتال (DOI): 10.22059/jphgr.2015.55335
نویسندگان
فرزانه برزو1؛ قاسم عزیزی* 2
1دانشجوی دکتری اقلیم‌شناسی، دانشگاه رازی کرمانشاه
2دانشیار دانشکدة جغرافیا، دانشگاه تهران
چکیده
هدف این پژوهش به‌دست دادن رابطه‌ای ساده و صحیح برای محاسبة بارش سنگین است که در همة مناطق ایران، حتی مکان‌های با فقر داده‌ای کاربرد داشته باشد. به‌دلیل دشواری دسترسی به آمارهای روزانه، این روش متکی بر شاخص‌های ماهانه است. برای تعیین بارش‌های سنگین از آمار روزانة بارش پنجاه سال اخیر (1961 تا 2011) چهل ایستگاه سینوپتیکی استفاده شد. مقدار بارش سنگین با استفاده از داده‌های روزانه، ماهانه و سالانه محاسبه و با یکدیگر مقایسه شد. از داده‌های سالانه برای تعیین شاخص بارش سنگین ایران و از بارشی که احتمال وقوع آن، میان بارش‌های ثبت‌شده پنج درصد بود، به‌مثابة معیار اولیه استفاده شد. با استفاده از روش خوشه‌بندی، مؤلفه‌های مؤثر بر بارش سنگین ایران شناسایی شد. در تحلیل عاملی از یازده مؤلفة بارشی، دو مؤلفة میانگین مجموع بارش سالانه و تعداد روزهای بارشی یک میلی‌متر، درمجموع 86 درصد اثر را پوشش می‌دهد. رابطة نهایی از نسبت میانگین مجموع بارش سالانه به میانگین تعداد روزهای بارشی یک میلی‌متر و بیشتر همراه یک ضریب عددی تشکیل‌ شد. برای تعیین ضریب عددی، ایران به هفت گروه تقسیم شد و برای هر گروه، ضریب جداگانه به‌دست آمد. بارش سنگین محاسبه‌شده با معیار اولیه همبستگی زیادی (997/0) نشان‌ داد. درنهایت، نقشة پهنه‌بندی ضریب عددی و بارش سنگین برای محاسبة مقدار بارش سنگین هر نقطة ایران با نرم‌افزار  GISرسم شد.
کلیدواژه‌ها
احتمال وقوع؛ ایران؛ بارش سنگین؛ شاخص
عنوان مقاله [English]
Suggesting a Simple Criterion to Estimate Heavy Rainfall in Iran
نویسندگان [English]
Farzaneh Borzoi1؛ Ghasem Azizi2
1PhD Candidate in Climatology, Department of Geography, Faculty of Literature and Humanities, Razi University Kermanshah, Iran
2Associate Professor, Faculty of Geography, University of Tehran, Iran
چکیده [English]
Introduction
Selection of the clear and transparent index for the precipitation using long-term homogeneous data is an important point for the researchers. Several investigations have led to different indices for heavy rainfall. In some cases the specific amount of precipitation was used for heavy rainfall (Rahimzadeh, 2005; Masoodian, 2008; Kamiguchi et al., 2006), e.g. Alijani (2002) has suggested the precipitation more than 30 millimeter. Some investigators have used the percentage of daily precipitation as a heavy rainfall index (Mohammadi and Masoodian, 2010), e.g. Easterling et al. (2003) used the greatest annual 5-days total precipitation amount and the percentage of annual precipitation, due to all 24-h rainfall totals exceeding the 95th percentile of daily amounts. A series of international workshops have introduced a set of indicators to show the effect of climate change on extreme events (Folland et al., 1999; Nicholla and Murray, 1999; Manton et al., 2001). Some researchers used several indicators as an index for heavy rainfall (Seibert et al., 2005; Haylock et al., 2006; Haylock and Nicholis, 2000; Osborn and Hulme, 2002; Simonov et al., 2007; Vaidya and Kulkarni, 2007; Campins et al., 2006; Paddock et al., 2008; Kysely and Picek, 2007; Bukantis et al., 2010; Schmidli et al., 2002). For example, Hänsel and Matcshullat (2009) to study monthly trends of daily heavy precipitation indicators used 22 heavy precipitation indicators (HPI) that may be classified into the four groups “A”, “I”, “F” and “M”. “A” stands for average precipitation indicators like monthly precipitation totals and number of wet days. “I” comprises indicators measuring the precipitation intensity, like the SDPI (Simple Daily Precipitation Index) or the percentage of precipitation above the 95th percentile. The frequency of heavy precipitation events is studied by indicators in class “F”, while category “M” includes indicators of heavy precipitation events magnitude. Zhang et al. (2001) proved that annual and seasonal time series of heavy event frequency are obtained by counting the number of exceedances per year. Characteristics of the intensity of heavy precipitation events are investigated by examining the 90th percentiles of daily precipitation, the annual maximum daily value, and the 20-yr return values. Based on the results, uses of percentile indicators are more common compared with threshold indicators and in some studies both the indicators have been used. It seems that the use of heavy rainfall partly depends on the geographical characteristics of the rainfall region. The natural ecosystems adapt themselves with the annual precipitation and extreme events in every region over time. Thus, the amount of precipitation shows the heavy rainfall in a dry station and in a humid station it can be recognized as normal. This study tries to find a simple method to indicate the heavy rainfall with regard to monthly trends based on daily data.
Methodology
To determine an index for heavy precipitation, data of daily precipitation for 40 stations with synchronized meteorological data are distributed homogeneously throughout the country in periods 1961-2011. The probability (1, 5, 10, 20 and 50%) for the entire period of rainy days was calculated using the Weibul equation. A very high percentage of daily precipitation values were obtained with the test 1 percentage, so the occurrence of five percent of daily precipitation was used as an index. The relationship between the ratio of the total mean annual precipitation (mm) and number of days with precipitation equal to or greater than one millimeter with a numerical coefficient may provide the best indicator for the heavy rainfall. Factor analysis of these two components can be selected from among the eleven factors of rainfall data including a total of 86 percent. Finally, the isohyet map was plotted using the numerical index by GIS so the heavy rainfall could be calculated for each part of Iran.
Results and Discussion
To determine the appropriate numerical factor in Iran, all the stations are classified into seven groups using K means cluster analyses, because of the different geographical characteristics and rainfall patterns. The average total annual rainfall was used to classify the groups. Then, the numerical coefficient was separately calculated for each group.
Conclusion
According to the proposed heavy rainfall index, the isohyet map was plotted. The isoline map of numerical coefficient was calculated for each station or related area in order to estimate heavy rainfall. The average error between the proposed index and the five percent probability of daily precipitation is 0.07. Only in Ardabil, Urumia, Dezful and Chabahar Port the error is more than one millimeter. There is no error in Ahvaz and Isfahan, i.e. the proposed index is equal to the five percent probability of daily precipitation. The comparison between the heavy rainfall isohyet map and the total average annual precipitation and the number of days with precipitation equal to or greater than one millimeter in Iran shows the same distribution.
کلیدواژه‌ها [English]
heavy rainfall, indicator, Iran, probability
مراجع
  1. رحیم‌زاده، ف. (1384). «بررسی مقادیر حدی بارش در ایران». نیوار. ش58 و 59، ص7-20.
  2. علیجانی، ب. (1381). آب‌وهوای ایران. چ5. تهران: انتشارات دانشگاه پیام نور. ص118-120.
  3. ــــــــــ (1390). «تحلیل فضایی دماها و بارش‌های بحرانی روزانه در ایران». نشریة تحقیقات کاربردی علوم جغرافیایی. ج17. ش20. ص9-30.
  4. محمدی، ب. (1392). «تحلیل روند سالانة آستانة بارش‌های سنگین ایران». تحقیقات جغرافیایی. س28. ش1. پیاپی 108. ص163-176.
  5. محمدی، ب. و مسعودیان، ا. (1389). «تحلیل فشار تراز دریا در زمان رخداد بارش‌های فوق‌سنگین و فراگیر ایران». چهاردهمین کنفرانس ژئوفیزیک ایران. تهران:مؤسسة ژئوفیزیک.فیزیک فضا. ص230-233.
  6. مسعودیان، ا. و محمدی، ب. (1389). «تحلیل فراوانی تابع همگرایی شار رطوبت در زمان رخداد بارش‌های ابرسنگین ایران». چهارمین کنگرة بین‌المللی جغرافیدانان جهان اسلام. زاهدان.
  7. مسعودیان، ا. (1378). «شناسایی شرایط همدید همراه با بارش‌های ابرسنگین ایران». سومین کنفرانس مدیریت منابع آب ایران. تبریز.
  8. منتظری، م. (1388). «تحلیل زمانی- مکانی بارش‌های فرین روزانه در ایران». جغرافیا و برنامه‌ریزی محیطی. س20. ش2. پیاپی 34. ص125-140.
    1. Alexander, L.V., Zhang, X., Peterson, T.C., Caesar, J., Gleason, B., Klein Tank, A.M.G., Haylock, M., Collins, D., Trewin, B., Rahimzadeh, F., Tagipour, A., Ambenje, P., Rupa Kumar, K., Revadekar, J.and Griffiths, G., (2006). "Global observed changes in daily climate extremes of temperature and precipitation". J. Geophys. Res. 111 (D05109). doi: 10.1029/2005JD006290.
    2. Alijani, B. (2002). Iran's climate. 5th Printing. Tehran: University of Payame Noor Publishing. (In Persian).
    3. ــــــــــ (2011). "Spatial analysis of the critical temperatures and daily precipitation in Iran". Journal of Geographical Sciences and Applied Research. Vol. 17. No. 20. Pp. 9-30. (In Persian).
    4. Montazeri, M. (2009). "Tempo-spatial analysis of extreme 24 hour precipitations in Iran". Journal of Geography and Environmental Planning. Y. 20. No. 34. No. 2. Pp.125-140. (In Persian).
    5. Banivaheb, A. (2007). "A Survey on Synoptic Patterns of Heavy Summer Rain happening in the northern areas of Khorasan". Geographical Journal of Territory. No. 13. Pp. 41-53.
    6. Bukantis, A., Rimkus, E. and Kažys, J. (2010). "Heavy Precipitation Events in Lithuania, EMS annual meeting". 10th European Conference on Applications of Meteorology (ECAM). Vol. 7. P. 100.
    7. Campins, J., Jans`a,A. and Genov´es, A. (2006). "Heavy rain and strong wind events and cyclones in the Balearics". Advances in Geosciences. No. 7. Pp. 73–77.
    8. Easterling, D. R., Alexander, L.V., Mokssit, A. and Detemmermen, V. (2003). "CC1/CLIVAR Workshop to develop priority climate indices". American Meteorological Society. DOI: 10.1175/BAMS-84-10-1403.
    9. Folland, C.K., Horton, E.B. and Scholefield, P. (eds.) (1999). "Report of WMO Working Group on Climate Change.Detection Task Group on Climate Change Indices". Bracknell. 1 September 1998. WMO TD 930.
    10. Frich, P., Alexander, L.V., Della-Marta, P., Gleason, B., Haylock, M., Klein Tank, A.M.G. and Peterson, T. (2002)." Observed coherent changes in climatic extremes during the second half of the twentieth century". Climate Research. No. 19. Pp. 193-212.
    11. Haylock, M. and Nicholls, N. (2000) "Trends in extreme rainfall indices for an updated high quality data set for Australia 1910–1998".International Journal of Climatology. No. 20. Pp. 1533-1541.
    12. Hänsel, S. and Matschullat, J. (2009). "Monthly trends of daily heavy precipitation indicators from lowland to mountainous regions in Saxony, Germany, Poster, 7th Biomet Conf". Stará Lesná. Slovakia. October 5-8.
    13. Kamiguchi, K., Kitoh, A., Uchiyama, T., Mizuta, R., and Noda, A. (2006). "Changes in Precipitation-based Extremes Indices Due to Global Warming Projected by a Global 20-km-mesh Atmospheric Model". SOLA. No. 2. Pp. 64-67. doi:10.2151/sola.2006-017.
    14. Karl, T. R., Knight, R. W., Easterling, D. R. and Quayle, R.G. (1996). "Indices of climate change for the United States". Bull. Amer.Meteor. Soc. No. 77. Pp. 279–292.
    15. Kysely, J. and Picek, J. (2007). "Probability estimates of heavy precipitation events in a flood-prone central-European region with enhanced influence of Mediterranean cyclones". Advances in Geosciences. No. 12. Pp. 43–50.
    16. Manton, M.J., Della-Marta, P.M., Haylock, M.R., Hennessy, K.J. and 23 others. (2001). "Trends in extreme daily rainfall and temperature in southeast Asia and the South Pacific: 1961 –1998". Int. J. Climatology. No. 21. Pp. 269-284.
    17. Masoodian, A. and Mohammadi, B. (2010). "The analysis of frontogenesis frequency effected on super heavy rainfall in Iran". Forth International Congress of the Islamic World Geographers. Zahedan. (In Persian).
    18. Masoodian, A. (1999). "Identification of synoptic conditions with heavy rainfalls Iran". Third Iranian Water Resources Management Conference. Tabriz. (In Persian).
    19. Mekis, E. and Hogg, W.D.,(1999). "Rehabilitation and analysis of a Canadian daily precipitation time series". Atmos.–Ocean. No. 37. Pp. 53–85.
    20. Mohamadi, B. (2013). "The annual trend analysis of heavy precipitation thresholds Iran".Gegraphic research. year 28. No. 1 (108).Pp. 163-176. (In Persian).
    21. Mohamadi, B. and Masoodian, A. (2010). "Analysis of sea level pressure and widespread heavy rainfall event in Iran, Forth Geophysics Conference of Iran". Tehran. Institute of Geophysics. Journal of Earth Space. Pp. 230-233.
    22. Nicholls, N. and Murray, W. (1999). "Workshop on Indices and Indicators for Climate Extremes, Breakout Group B: Precipitation". Climatic Change. 42/1. Pp. 23-29.
    23. Osborn, T.J., and Hulme, M. (2002). "Evidence for trends in heavy rainfall events over the UK". The Royal Society. 10. 1098/rsta. 1002.
    24. Paddock, M., Graves, CH.E. and Martinelli, J.T. (2008). "Examining preconnective heavy rainfall environments utilizing observational and model analysis proximity soundings". 23rd Conf. on Weather Analysis and Forecasting. Omaha. NE. Amer. Meteor. Soc. JP3. 10.
    25. Peterson, T.C., Folland, C., Gruza, G., Hogg, W., Moskssit, A., and Plummer, N. (2001). "Report on The Activities of The Working Group on Climate Change Detection and Related Rapporteurs". World Meteorological Organization, Document. No. 1071. Geneva. Pp. 146.
    26. Rahimzadeh, F. (2005). "Study of Variation of Extreme Precipitations over Iran". Nivar. No. 58,59. Pp. 7-20. (In Persian).
    27. Sa´nchez, E., Gallardo, C., Gaertner, M.A., Arribas, A. and Castro, M. (2004). "Future climate extreme events in the Mediterranean simulated by a regional climate model: a first approach". Global and Planetary Change. No. 44. Pp. 163–180.
    28. Seibert, P., Frank, A. and Formayer, H. (2005). "Synoptic and regional patterns of heavy precipitation in Austria". Submitted to Theoretical and applied climatology. Vol. 87. No. 1. Pp. 139-153.
    29. Schmidli, J. and Frei, C. (2005). "trends of heavy precipitation and wet and dry spells in Switzerland during the 20th century". Int. J. climatology. No. 25. Pp. 771-773.
    30. Schmidli, J., Schmutz, C., Frei, C., Wanner, H. and Schär, C. (2002). "Mesoscale precipitation variability in the region of the European Alps during the 20th century". Int. J. Climatology. No. 22. Pp. 1049–1074.
    31. Vaidya, S.S. and Kulkarni, J.R. (2007). "Simulation of heavy precipitation over Santa Cruz Mumbai on 26 july 2005 (using mesoscale)". Meteor. Atmos. Phys. DOI10.1007/s00703-006-4,WWW.Noaa.com.
    32. Zhang, X., Aguilar, E., Sensoy, S., Melkonyan, H., Tagiyeva, U., Ahmed, N., Kutaladze, N., Rahimzadeh, F., Taghipour, A., Hantosh, T.H., Albert, P., Semawi, M., Karem Ali, M., Halal Said Al-Shabibi, A., Al-Oulan, Z., Zatari, T., Al Dean Khelet, I., Hammond, S., Demircan, M., Eken, M., Adiguzel, M., Alexander, L., Peterson, T.C. and Wallis, T. (2005). "Trends in Middle East Climate Extremes Indices during 1930-2003". J. Geophys. Res. 110. D22104. doi: 10.1029/2005JD006181.
    33. Zhang, X., Hoggs, W.D. and Mekis, E. (2001). "Spatial and Temporal Characteristics of Heavy Precipitation Events over Canada, American Meteorological Society". Journal of climate. Vol. 14. Pp. 1923-1936.
آمار
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