مدلسازی وردایی زمانی- مکانی بارش فصلی در ایران مرکزی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد آب و هواشناسی، دانشگاه یزد، یزد ایران

2 دکتری مخاطرات آب و هوایی، دانشگاه یزد، یزد، ایران

3 دانشجوی دکتری آب وهواشناسی شهری، دانشگاه شهید بهشتی، تهران، ایران

چکیده

روابط بین بارش-ارتفاع را می توان به عنوان یک دستاورد مهم برای مطالعات بارش-رواناب و مدیریت حوضه های آبریز بخصوص در مناطق خشک و نمیه خشک که شکنندگی بالایی دارند قلمداد کرد. در پژوهش پیش رو به مدلسازی وردایی زمانی-مکانی فصلی بارش-ارتفاع در ایران مرکزی پرداخته شد. به این منظور داده های پایگاه داده-بارش آفرودیت برای یک دوره 30 ساله (1977-2007میلادی) مبتنی بر DEM با تفکیک مکانی 30 متر با استفاده از دو مدل حداقل مربعات معمولی (OLS) و رگرسیون وزن دار جغرافیایی (GWR) مورد ارزیابی قرار گرفتند. ارزیابی دو مدل حاضر نشان داده است که مدل رگرسیون وزن دار جغرافیایی (GWR) بهتر می تواند روابط بارش-ارتفاع را در ایران مرکزی توضیح دهد. همچنین مشخص گردید که افزایش ضریب  برای مدل حداقل مربعات معمولی (OLS) بخصوص در فصل بهار ناشی از همرفت و تشدید پدیده کوهبارش بوده است. کمبود بارش در ایران مرکزی را می توان در دو رسته بنیادین جای داد: 1- حاکمیت پرفشار جنب حاره در دوره گرم سال و 2- آورده های سامانه های غربی به جهت سایه بارش زاگرس سهم چندانی برای مناطق ایران مرکزی ندارد لذا فارغ از فقر بارش محتوای رطوبت هواسپهر این منطقه از ایران بسیار اندک است. بارش در ایران مرکزی دارای ساختار فضایی بوده و رفتار خوشه ای از خود نشان می دهد. همچنین مشخص گردید در ایران مرکزی بیشینه بارشی در بیشینه ارتفاعی حادث نمی شود و بیشینه و کمینه رابطه
بارش-ارتفاع در ایران مرکزی بترتیب در پیش باد و پشت باد اتفاق می افتد.

کلیدواژه‌ها


عنوان مقاله [English]

Variance modeling space-time seasonal rainfall in central Iran

نویسندگان [English]

  • Kamal Omidvar 1
  • Reza Ebrahimi 2
  • Abbasali Dadashi Roodbari 3
1 Professor of Climatology,Yazd University, Iran
2 Ph.D Student of Climatology, Yazd University, Iran
3 Ph.D Student of Climatology, Shahid Beheshti University, Iran
چکیده [English]

Detection of the relationship between rainfall and altitude can be considered as an important achievement for rainfall-runoff studies and the management of catchment areas, especially in arid and dry soils that have a high brittleness. In the present study, the rainfall-elevation time-space spatial modeling of central Iran is performed. For this purpose, the Aphrodite precipitation database was used for a 30-year period (1977-2007) based on DEM and with a spatial resolution of 30 meters. In this regard, two models were utilized; ordinary least squares (OLS) and geographic weighted regressions (GWR). The evaluation of the two models showed that the GWR model can better explain the precipitation-elevation relationships in central Iran. It was also found that the increase in the coefficient for the (OLS) model, especially in the spring, was due to the convection and exacerbation of the mountainous precipitation phenomenon. The precipitation in central Iran has a spatial structure and shows cluster behavior. It emerged that, in central Iran, the maximum rainfall does not occur at the maximum altitude, and the maximum and minimum of the rainfall-altitude relationship in central Iran occur before and behind the wind.
Keywords: .

کلیدواژه‌ها [English]

  • Seasonal precipitation
  • Spatial dependence
  • Geographic weighted regression
  • Central Iran
  1. Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P. P., Janowiak, J., & Gruber, A. (2003). The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979-present). Journal of hydrometeorology, 4(6), 1147-1167.
  2. Al-Ahmadi, K., & Al-Ahmadi, S. (2013). Rainfall-altitude relationship in Saudi Arabia. Advances in Meteorology, 2013.
  3. Alijani, B. (1995). The role of the Alborz Mountains on the altitudinal distribution of precipitation, Geographical Research Quarterly, Volume 38, Issue 3. (in Farsi).
  4. Alijani, B. (2008). Effect of the Zagros Mountains on the spatial distribution of precipitation. Journal of Mountain Science, 5(3), 218-231.
  5. Asakereh, H. (1999). Kriging interpolation method of precipitation used, Geography and Development, Issue 12 (in Farsi).
  6. Azizi, G., Faraji Sabokbar, H.A., Abbaspoor R.A., Sfrrad, T. (2010). The Model of the Spatial Variability Precipitation in the Middle Zagros. Physical geography, Volume 42, Issue 72, 35-51. (in Farsi).
  7. Basist, A., Bell, G. D., & Meentemeyer, V. (1994). Statistical relationships between topography and precipitation patterns. Journal of climate, 7(9), 1305-1315.
  8. Bostan, P. A., & Akyürek, Z. (2009). Spatio-Temporal Analysis of Precipitation and Temperature Distribution over Turkey. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38(Part II).
  9. Bostan, P. A., & Akyürek, Z. (2009). Spatio-Temporal Analysis of Precipitation and Temperature Distribution over Turkey. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38(Part II).
  10. Brunsdon, C., McClatchey, J., & Unwin, D. J. (2001). Spatial variations in the average rainfall–altitude relationship in Great Britain: an approach using geographically weighted regression. International Journal of Climatology, 21(4), 455-466.
  11. Charlton, M., Fotheringham, S., & Brunsdon, C. (2009). Geographically weighted regression. White paper. National Centre for Geocomputation. National University of Ireland Maynooth.
  12. Darand, M., Zerafat, M., Zerafat Motlagh, O.R., Samandar, R. (2015). Comparison between global and regional databases of precipitation Asfazari base station of precipitation Iran, Geographical Research Quarterly, Vol. 30, No. 2, pp. 65-84. (in Farsi).
  13. Fiener, P., & Auerswald, K. (2009). Spatial variability of rainfall on a sub‐kilometre scale. Earth Surface Processes and Landforms, 34(6), 848-859.
  14. Fotheringham, A. S., Charlton, M. E., & Brunsdon, C. (2001). Spatial variations in school performance: a local analysis using geographically weighted regression. Geographical and Environmental Modelling, 5(1), 43-66.
  15. Ghayour, H.A., Masoodian, A. (1996). Evaluating the spatial relationship between precipitation and elevation in Iran. Geographical Research, Issue 41 (in Farsi).
  16. Grayson, R., & Blöschl, G. (2001). Spatial patterns in catchment hydrology: observations and modelling. CUP Archive.
  17. Haile, A. T., Rientjes, T., Gieske, A., & Gebremichael, M. (2009). Rainfall variability over mountainous and adjacent lake areas: the case of Lake Tana basin at the source of the Blue Nile River. Journal of Applied Meteorology and Climatology, 48(8), 1696-1717.
  18. Hayward, D., & Clarke, R. T. (1996). Relationship between rainfall, altitude and distance from the sea in the Freetown Peninsula, Sierra Leone. Hydrological sciences journal, 41(3), 377-384.
  19. Hurvich, C. M., Simonoff, J. S., & Tsai, C. L. (1998). Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 60(2), 271-293.
  20. Konrad II, C. E. (1996). Relationships between precipitation event types and topography in the southern Blue Ridge Mountains of the southeastern USA. International Journal of Climatology, 16(1), 49-62.
  21. Lloyd, C. D. (2010). Multivariate interpolation of monthly precipitation amount in the United Kingdom. In geoENV VII–Geostatistics for Environmental Applications (pp. 27-39). Springer Netherlands.
  22. Manzano-Agugliaro, F., Zapata-Sierra, A., Fernández-Castañeda, C., García-Cruz, A., & Hernández-Escobedo, Q. (2014). Extreme rainfall relationship in Mexico. Journal of Maps, (ahead-of-print), 1-10.
  23. Masoodian, A. (2011), weather of Iran, Mashhad Birch Sharia Publishing, Printing 1, Mashhad (in Farsi).
  24. Masoodian, A., Keikhosravi Kayani, MS., Rayat Pisheh, F. (2014). Introduce and compare database with database Asfazari GPCC, GPCP, and CMAP, Geographical Research Quarterly, Vol. 29, No. I, pp. 73-88. (in Farsi).
  25. Mennis, J. (2006). Mapping the results of geographically weighted regression. The Cartographic Journal, 43(2), 171-179.
  26. Oettli, P., & Camberlin, P. (2005). Influence of topography on monthly rainfall distribution over East Africa. Climate Research, 28(3), 199-212.
  27. Schuurmans, J. M., & Bierkens, M. F. P. (2006). Effect of spatial distribution of daily rainfall on interior catchment response of a distributed hydrological model. Hydrology and Earth System Sciences Discussions, 3(4), 2175-2208.
  28. Scott, D., Hall, C. M., & Gössling, S. (2016). A review of the IPCC Fifth Assessment and implications for tourism sector climate resilience and decarbonization. Journal of Sustainable Tourism, 24(1), 8-30.
  29. Scott, L. M., & Janikas, M. V. (2010). Spatial statistics in ArcGIS. In Handbook of applied spatial analysis. (pp. 27-41). Springer Berlin Heidelberg.
  30. Sharma, V., Kilic, A., Kabenge, I., & Irmak, S. (2011). Application of GIS and Geographically Weighted Regression to Evaluate the Spatial Non‐Stationarity Relationships between Precipitation vs. Irrigated and Rainfed Maize and Soybean Yields.
  31. Sorooshian, S., Hsu, K. L., GAO, X., Gupta, H. V., Imam, B., & Braithwaite, D. (2000). Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bulletin of the American Meteorological Society, 81(9), 2035-2046.
  32. Staub, C. G., Stevens, F. R., & Waylen, P. R. (2014). The geography of rainfall in Mauritius: Modelling the relationship between annual and monthly rainfall and landscape characteristics on a small volcanic island. Applied Geography, 54, 222-234.
  33. Tošić, I. (2004). Spatial and temporal variability of winter and summer precipitation over Serbia and Montenegro. Theoretical and applied climatology, 77(1-2), 47-56.
  34. Xie, P., & Xiong, A. Y. (2011). A conceptual model for constructing high‐resolution gauge‐satellite merged precipitation analyses. Journal of Geophysical Research: Atmospheres, 116(D21).
  35. Xie, P., Chen, M., Yang, S., Yatagai, A., Hayasaka, T., Fukushima, Y., & Liu, C. (2007). A gauge-based analysis of daily precipitation over East Asia. Journal of Hydrometeorology, 8(3), 607-626.
  36. Zulfiqari, H. Sari Sarraf, B. (1998). The North Westof Iran study of precipitation based on cluster analysis, Faculty of Literature, Human Sciences, Mashhad, Issue 1 and 2. (in Farsi).