Analysis of rainy days in Iran based on output Aphrodite Precipitation Database | ||
| پژوهش های جغرافیای طبیعی | ||
| Article 10, Volume 49, Issue 3, October 2017, Pages 503-521 PDF (1.45 M) | ||
| Document Type: Full length article | ||
| DOI: 10.22059/jphgr.2017.207627.1006866 | ||
| Authors | ||
| Abdol Reza Kashki* 1; Abbas Ali Dadashi Roudbari2 | ||
| 1Assistant Professor of Climatology, Hakim Sabzevari University, Sabzevar, Iran | ||
| 2PH.D Student Urban Climatology, Shahid Beheshti University, Tehran, Iran | ||
| Abstract | ||
| Introduction Knowledge of the amount, spatial distribution and temporal variation of rainy days is essential to provide public information, hydrological modelling and flood forecasting, climate monitoring and climate model validation. Data Grids Database provides valuable information about the amount and frequency of rainfall. A rainy day indicates a day when all the conditions of precipitation, humidity, instability and condensation nuclei have been provided in the atmosphere. Iran is located between the vast territories of Siberia in the north, the Mediterranean Sea in the west, the African deserts in Saudi Arabia in the southwest and the Arabian Sea and India in the east. This is a factor for interacting with different atmospheric systems on Iran. Interaction deep, complex and continuous rainfall is caused by climate change and a variety of other elements in space and time. Therefore, the aim of this study is to study the number of days of Iranian rainfall using the Aphrodite precipitation database in the 56-year period (1/1/1951 to 31/12/2007). Materials and methods In the present study, data of the Middle East region (APHRO_ME) have been obtained from the latest Aphrodite database product (Yatagai et al. 2014) under the name of v1101, with a resolution of 0.25 × 0.25 °, equivalent to 25.5 x 25.5 km with the format of NC" NetCDF. Given the programming capabilities of Grads 2.0.a9 and Matlab R2013 software, the 57-year precipitation data (1951-2007) have been selected from the total precipitation database (APHRO_ME) on a daily basis.In this research, the Root Mean Square Error (RMSE) and the coefficient of determination (R2) have been used. Results and discussion The values are different in every area of rainfalls and every time. The skewness provided shows that the spatial distribution of precipitation is skewed to the right, towards the low-rainfall areas relative to the areas with high rainfall. According to the dynamic and thermodynamic systems considered as a cause for precipitation and dependent on the geographic location, these systems in dealing with local conditions can cause different precipitation regions. Therefore, the amount of precipitation can be estimated by a variety of statistical parameters. The difference in median, mean and deviation indicates that the data does not follow a normal distribution. The number of rainy days is ranged from 9 to 147 days. The average number of rainy days in Iran is 38 days, while the number of rainy days is 36.62% of the area of the country, less than 38 days. The rainy day of region in terms of the number of rainy days is located iin southwest part of the Caspian Sea (32 km south part of the Bandar Anzali West synoptic). Similarly, the lowest number of rainy days with 9 days in South East Iran has located 116 kilometers East of Khash synoptic stations. Conclusion The results have indicated that the average of rainy days is 38 days and, however, the number of rainy days is 36.62% of the area of the country. The maximum rainfall Iran with 147 days is located on the Caspian Sea in the South West. On the other hand, a minimum of 9 days of rainy days is in the South East Iran. Iran is divided into four zones of rainy days in the entire north coast, the northern part of North Khorasan, North West and West Highlands in a group. Finally, the division offered the best zone division of rainy days. The country is divided into six zones. The six zones are the Khazary zones with 126 rainy days, across the mountainous regions of West, North West and Northeast with 77 rainy days across the mountainous area, a zone between the highlands and lowlands of leeward with 38 rainy days. Finally, the relationship between the number of rainy days with latitude and elevation has been evaluated for the entire zone in Iran and the six zones. There is a correlation of 0.57 for entire Iran. This has determined the most important factor in the equation. The differences between the average and the maximum number of rainy days in Iran have been compared with other studies. The comparison has revealed accuracy of the results. | ||
| Keywords | ||
| rainy day; rainy areas; Stepwise regression; Aphrodite Database; Iran | ||
| References | ||
|
امیدوار، کمال (1380). تحلیل سینوپتیکی سیستمهای بارانزا و امکان افزایش بارش آنها بهوسیلة باروری ابرها در منطقة کرمان، پژوهشهای جغرافیایی، 40: 19-32. دارند، محمد؛ ظرافتی، محمد؛ کفایت مطلق، امیدرضا و سمندر، ریحانه (1394). مقایسة بین پایگاههای دادة جهانی و منطقهای بارش با پایگاه بارش اسفزاری و پیمونگاهی ایرانزمین، فصلنامة تحقیقات جغرافیایی، 30(2): 65-84. رضایی، عبدالمجید و سلطانی، افشین (1382). مقدمهای بر تحلیل رگرسیون کاربردی، مرکز نشر دانشگاه صنعتی اصفهان. رمضانی، بهمن و فرهی، صدیقه (1389). پهنهبندی مقدار بارش روزانه و تعداد روزهای بارندگی در حوضة تالاب انزلی، مجلة تالاب دانشگاه آزاد اسلامی واحد اهواز، 4: 11-20. صفرراد، طاهر؛ فرجی سبکبار، حسنعلی؛ عزیزی، قاسم و عباسپور، رحیمعلی (1392). تحلیل مکانی دگرگونی بارش در زاگرس میانی از طریق روشهای زمینآمار (1995-2004)، جغرافیا و توسعه، 31: 162-149. عزیزی، قاسم؛ صفرراد، طاهر؛ محمدی، حسین؛ فرجی سبکبار، حسنعلی (1395). ارزیابی و مقایسة دادههای بازکاویشدة بارش جهت استفاده در ایران، پژوهشهای جغرافیای طبیعی، 48(1): 33-49. عساکره، حسین (1387). کاربرد روش کریجینگ در میانیابی بارش، جغرافیا و توسعه، 12: 25-42. عساکره، حسین (1390). مبانی آب و هواشناسی آماری، انتشارات دانشگاه زنجان. عساکره، حسین و رزمی، رباب (1391). تحلیل دگرگونی بارش سالانة شمال غرب ایران، جغرافیا و برنامهریزی محیطی، 23(3): 147-162. عساکره، حسین و سیفیپور، زهره (1392). توصیف ساختار مکانی بارش سالانة ایران، تحقیقات جغرافیایی، 28(111): 15-30. علیجانی، بهلول (1389). آبوهوای ایران، چ 10، تهران: انتشارات دانشگاه پیام نور. غیور، حسنعلی؛ مسعودیان، سید ابوالفضل؛ آزادی، مجید و نوری، حمید (1390). تحلیل زمانی و مکانی رویدادهای بارشی سواحل جنوبی خزر، فصلنامة تحقیقات جغرافیایی، 25(100): 1-30. لشکری، اعظم؛ بنایان، محمد؛ کوچکی، علیرضا؛ علیزاده، امین؛ سای چوی، یانگ و کی پارک، سئون (1394). بررسی امکانسنجی استفاده از پایگاه دادة AgMERRA برای ساخت دادههای ناقص و گمشدة موجود در دادههای پیمونگاههای سینوپتیک (دشت مشهد)، نشریة آب و خاک، 29(6): 1758-1749. مسعودیان، سید ابوالفضل (1388). نواحی بارشی ایران، جغرافیا و توسعه، 13: 79-91. مسعودیان، سید ابوالفضل (1390). آبوهوای ایران، مشهد: شریعة توس. مسعودیان، سید ابوالفضل؛ دارند، محمد و کاشکی، عبدالرضا (1389). تحلیل روند تعداد روزهای بارانی ایران، چهارمین کنفرانس منطقهای دگرگونی آب و هوا 29 آذر الی 1 دی، تهران. مسعودیان، سید ابوالفضل؛ کیخسروی کیانی؛ محمدصادق و رعیتپیشه، فاطمه (1393). معرفی و مقایسة پایگاه دادة اسفزاری با پایگاههای دادة GPCC، GPCP ، و CMAP، فصلنامة تحقیقات جغرافیایی، 29(1): 73-88. مفیدی، عباس (1383). آب و هواشناسی سینوپتیکی بارشهای سیلزا با منشأ منطقة دریای سرخ در خاورمیانه، فصلنامة تحقیقات جغرافیایی، 75: 71-93. Alijani, B. (2010). Climate Iran, Payame Noor University, Tenth Edition, Tehran, 221 p. (In Persian).
Asakereh, H. (2008). Kriging interpolation method of precipitation used, Geography and Development, 12: 25-42.
Asakereh, H. (2011). Foundations of statistical climatology, Zanjan University Press, 548 p.
Asakereh, H. and Razmi, R. (2012).Analysis of changes in annual rainfall North West of Iran, Geography and Environmental Planning, 23(3): 147-162.
Asakereh, H. and Seifipour, Z. (2013). Describes the spatial structure of annual rainfall Iran, Geographical Research, 28(111): 15-30.
Barancourt, C.; Creutin, J.D. and Rivoirard, J. (1992). A method for delineating and estimating rainfall fields, Water Resources Research, 28(4): 1133-1144.
Barry, R.G. (1992). Mountain climatology and past and potential future climatic changes in mountain regions: a review, Mountain Research and Development, 71-86.
Berne, A.; Delrieu, G.; Creutin, J.D. and Obled, C. (2004). Temporal and spatial resolution of rainfall measurements required for urban hydrology, Journal of Hydrology, 299(3): 166-179.
Brunetti, M.; Maugeri, M. and Nanni, T. (2001). Changes in total precipitation, rainy days and extreme events in northeastern Italy, International Journal of Climatology, 21(7): 861-871.
Brunsell, N.A. (2010). A multiscale information theory approach to assess spatial–temporal variability of daily precipitation, Journal of hydrology, 385(1): 165-172.
Chappell, A.; Renzullo, L.J.; Raupach, T.H. and Haylock, M. (2013). Evaluating geostatistical methods of blending satellite and gauge data to estimate near real-time daily rainfall for Australia, Journal of Hydrology, 493: 105-114.
Chen, S.; Hong, X.; Harris, C.J. and Sharkey, P.M. (2004). Sparse modeling using orthogonal forward regression with PRESS statistic and regularization, Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 34(2): 898-911.
Cressie, N. (1993). Statistics for Spatial Data: Wiley Series in Probability and Statistics.
Cressie, N. and Wikle, C.K. (2011). Statistics for spatio-temporal data, John Wiley & Sons.
Creutin, J.D. & Obled, C. (1982). Objective analyses and mapping techniques for rainfall fields: an objective comparison, Water resources research, 18(2): 413-431.
Delhomme, J.P. (1978). Kriging in the hydrosciences, Advances in water resources, 1(5): 251-266.
Eksioglu, B.; Demirer, R. and Capar, I. (2005). Subset selection in multiple linear regression: a new mathematical programming approach, Computers & Industrial Engineering, 49(1): 155-167.
Fallah Ghalhari, G.A.; Dadashi Roudbari, A.A. and Asadi, M. (2016). Identifying the spatial and temporal distribution characteristics of precipitation in Iran, Arabian Journal of Geosciences, 9(12): 595.
Fortin, M.J. and Dale, M.R.T. (2005). Spatial analysis: a guide for ecologists, Cambridge University Press.
Ghayor, H.A.; Masoodian, S.A.; Azadi, M.; Noori, H. (2011). Analyze the spatial and temporal rainfall events the southern shores of the Caspian, Geographical Research Quarterly, 25(100): 1-30.
Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall, Journal of hydrology, 228(1): 113-129.
Grimes, D.I. and Pardo‐Igúzquiza, E. (2010). Geostatistical Analysis of Rainfall, Geographical Analysis, 42(2): 136-160.
Haining, R.P. (2003). Spatial data analysis, Cambridge: Cambridge University Press, p. 67-72.
Hofinger, S.; Mayr, G.J.; Dreiseitl, E. and Kuhn, M. (2000). Fine-scale observations of summertime precipitation in an intra-Alpine region, Meteorology and Atmospheric Physics, 72(2-4): 175-184.
Hofstra, N.; Haylock, M.; New, M.; Jones, P. and Frei, C. (2008). Comparison of six methods for the interpolation of daily, European climate data, Journal of Geophysical Research: Atmospheres, (1984-2012), 113(D21).
IPCC (2013). Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge.
Jhajharia, D.; Yadav, B.K.; Maske, S.; Chattopadhyay, S. and Kar, A.K. (2012). Identification of trends in rainfall, rainy days and 24h maximum rainfall over subtropical Assam in Northeast India, Comptes Rendus Geoscience, 344(1): 1-13.
Khan, J.A.; Van Aelst, S. and Zamar, R.H. (2007). Robust linear model selection based on least angle regression, Journal of the American Statistical Association, 102(480): 1289-1299.
Kumar, V. and Jain, S.K. (2010). Trends in seasonal and annual rainfall and rainy days in Kashmir Valley in the last century, Quaternary International, 212(1): 64-69.
Lebel, T.; Bastin, G.; Obled, C. and Creutin, J.D. (1987). On the accuracy of areal rainfall estimation: a case study, Water Resources Research, 23(11): 2123-2134.
Masoodian, S.A. (2009). Iran Precipitation zones, Geography and Development, 13: 79-91.
Masoodian, S.A. (2011). Climate Iran, Mashhad Toos Sharia Publishing, Printing 1, Mashhad, 288 p.
Masoodian, S .A.; Darand, M.and Kashki, A. (2010). Analyzing the number of rainy days in Iran, The fourth regional conference on climate change 29 November to 1 December, Tehran.
Mofidi, A. (2004). Synoptic Climatology rains causing floods originated from the Red Sea to the Middle East, Geographical Research Quarterly, 75: 71-93.
Odekunle, T.O. (2006). Determining rainy season onset and retreat over Nigeria from precipitation amount and number of rainy days, Theoretical and applied climatology, 83(1-4): 193-201.
Oki, T.; Musiake, K. and Koike, T. (1991). Spatial rainfall distribution at a storm event in mountainous regions, estimated by orography and wind direction, Water resources research, 27(3): 359-369.
Omidvar, K. (2001). Synoptic analysis systems, rain and the possibility of increasing rainfall by cloud seeding in the region of Kerman, Geographical Research, 40: 19-32.
Phillips, D.L.; Dolph, J. and Marks, D. (1992). A comparison of geostatistical procedures for spatial analysis of precipitation in mountainous terrain, Agricultural and Forest Meteorology, 58(1): 119-141.
Ramezani, B. and Farhi, S. (2010). Zoning amount of daily rainfall and number of days of rain in the Anzali basin, wetlands, Journal of Islamic Azad University, Ahvaz, 4: 11-20.
Rezaei, A.M. and Sultan, A. (2003). Introduction to Applied Regression Analysis, Center Isfahan University Press, 294 p.
SafarRad, T.; Faraji Sabokbar, H.A.; Azezim, Q. and Abbaspoor, Ra. (2013). Analyze the spatial variation of precipitation in the central Zagros through geostatistics methods (1995-2004), Geography and Development, 31: 162-149.
Sotillo, M.G.; Ramis, C.; Romero, R.; Alonso Oroza, S. and Homar, V. (2003). Role of orography in the spatial distribution of precipitation over the Spanish Mediterranean zone, Climate Research, 23: 247-261.
Sturman, A. and Wanner, H. (2001). A comparative review of the weather and climate of the Southern Alps of New Zealand and the European Alps, Mountain Research and Development, 21(4): 359-369.
Wang, X.X.; Chen, S.; Lowe, D. and Harris, C.J. (2006). Sparse support vector regression based on orthogonal forward selection for the generalised kernel model, Neurocomputing, 70(1): 462-474.
Yatagai, A.; Kamiguchi, K.; Arakawa, O.; Hamada, A.; Yasutomi, N. and Kitoh, A. (2012). APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges, Bulletin of the American Meteorological Society, 93(9): 1401-1415. | ||
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