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Disaggregating radar-derived rainfall measurements in East Azarbaijan, Iran, using a spatial random-cascade model

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Abstract

The availability of spatial, high-resolution rainfall data is one of the most essential needs in the study of water resources. These data are extremely valuable in providing flood awareness for dense urban and industrial areas. The first part of this paper applies an optimization-based method to the calibration of radar data based on ground rainfall gauges. Then, the climatological Z-R relationship for the Sahand radar, located in the East Azarbaijan province of Iran, with the help of three adjacent rainfall stations, is obtained. The new climatological Z-R relationship with a power-law form shows acceptable statistical performance, making it suitable for radar-rainfall estimation by the Sahand radar outputs. The second part of the study develops a new heterogeneous random-cascade model for spatially disaggregating the rainfall data resulting from the power-law model. This model is applied to the radar-rainfall image data to disaggregate rainfall data with coverage area of 512 × 512 km2 to a resolution of 32 × 32 km2. Results show that the proposed model has a good ability to disaggregate rainfall data, which may lead to improvement in precipitation forecasting, and ultimately better water-resources management in this arid region, including Urmia Lake.

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References

  • Ashouri H, Hsu K, Sorooshian S, Braithwaite DR, Knapp K, Cecil LD, Nelson BR, Prat O (2015) Daily precipitation climate data record from multisatellite observation for hydrological and climate studies. Am Meteorol Soc 96:69–83

    Article  Google Scholar 

  • Chumchean S (2004). Improved estimation of radar rainfall for use in hydrological modelling, Ph.D. Thesis, University of New South Wales

  • Deidda R, Benzi R, Siccardi F (1999) Multifractal modeling of anomalous scaling laws in rainfall. Water Resour Res 35(6):1853–1867

    Article  Google Scholar 

  • Fields G, Seed A, Yu B, Malone T (2004) Calibration of weather radar in South East Queensland, Sixth international symposium on hydrological applications of weather radar. Melbourne, Australia

    Google Scholar 

  • Fouladi Osgouei H, Zarghami M (2014) The study and modeling of rainfall spatial and temporal changes in East Azarbaijan, Iran, 21st Century Challenges in Regional Climate Modelling Workshop, 16–19 June 2014. Lund, Sweden

    Google Scholar 

  • Frisch U, Parisi G (1985), On the singularity structure of fully developed turbulence, In: Ghil, R. Benzi, and G. Parisi (Eds.), Turbulence and predictability in geophysical fluid dynamics and climate dynamics, North-Holland, N Y, 84-88

  • Groppelli B, Bocchiola D, Rosso R (2010) Precipitation downscaling using random cascades: a case study in Italy. Adv Geosci 26:39–44

    Article  Google Scholar 

  • Hassanzadeh E, Zarghami M, Hassanzadeh Y (2012) Determining the main factors in declining the Urmia Lake level by using system dynamics modeling. Water Resour Manag 26(1):129–145

    Article  Google Scholar 

  • Hsu K, Gao X, Sorooshian S, Gupta HV (1997) Precipitation estimation from remotely sensed information using artificial neural networks. J Appl Meteorol Climatol 36:1176–1190

    Article  Google Scholar 

  • Joyce RJ, Janowiak JE, Arkin PA, Xie P (2004) CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J Hydrometeorol 5:487–503

    Article  Google Scholar 

  • Kang B, Ramirez JA (2010) A coupled stochastic space-time intermittent random cascade model for rainfall downscaling. Water Resour Res 46:1–17

    Article  Google Scholar 

  • Licznar P, Łomotowski J, Rupp DE (2011) Random cascade driven rainfall disaggregation for urban hydrology: an evaluation of six models and a new generator. Atmos Res 99(3–4):563–578

    Article  Google Scholar 

  • Mandelbrot BB (1982) The Fractal Geometry of Nature. . W. H. Freeman & Company, New York 480 pp

    Google Scholar 

  • Mapiam PP, Sriwongsitanon N (2008) Climatological Z-R relationship for radar rainfall estimation in the upper ping river basin. Sci Asia 34:215–222

    Article  Google Scholar 

  • Marshall JS, Palmer WM (1948) The distribution of raindrops with size. J Meteorol 5:165–166

    Article  Google Scholar 

  • Mouhous N, Gaume E, Andrieu H (2001) Influence of the highest values on the choice of log-poisson random cascade model parameters. Phys Chem Earth Part B: Hydrol, Oceans Atmos 26(9):701–704

    Article  Google Scholar 

  • Olsson J (1998) Evaluation of a scaling cascade model for temporal disaggregation model. Hydrol Earth Syst Sci 2(1):145–164

    Article  Google Scholar 

  • Over TM, Gupta VK (1996) A space-time theory of mesoscale rainfall using random cascades. J Geophys Res 101(26):319–331

    Google Scholar 

  • Pathirana A, Herath S (2002) Multifractal modeling and simulation of rain fields exhibiting spatial heterogeneity. Hydrol Earth Syst Sci 6:695–708

    Article  Google Scholar 

  • Pedersen L, Jensen NE, Madsen H (2010) Calibration of local area weather radar-identifying significant factors affecting the calibration. Atmos Res 97:129–143

    Article  Google Scholar 

  • Pui A, Sharma A, Mehrotra R, Sivakumar B, Jeremiah E (2012) A comparison of alternatives for daily to sub-daily rainfall disaggregation. J Hydrol 470-471:138–157

    Article  Google Scholar 

  • Sharma D, Das Gupta A, Babel MS (2007) Spatial disaggregation of bias-corrected GCM precipitation for improved hydrologic simulation: Ping River Basin, Thailand. Hydrol Earth Syst Sci Discuss Copernicus Publ 11(4):1373–1390

    Article  Google Scholar 

  • Sivakumar B, Sharma A (2008) A cascade approach to continuous rainfall data generation at point locations. Stoch Env Res Risk A 22:451–459

    Article  Google Scholar 

  • Sorooshian S, Hsu KL, Gao X, Gupta HV, Imam B, Braithwaite D (2000) Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bull Am Meteorol Soc 81:2035–2046

    Article  Google Scholar 

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Acknowledgments

The authors would like to thank the Meteorological Department of East Azarbaijan, Iran, for providing gauge and radar-rainfall data and the East Azarbaijan Regional Water Company for funding the research. We would also like to acknowledge Prof. Vahid Nourani (University of Tabriz), Jory Hecht (Tufts University), Javad Fouladi (University of Tabriz), and Corrie Thies (University of California at Irvine) for their useful suggestions to improve the quality of the research presented in this manuscript.

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Authors and Affiliations

  1. Faculty of Civil Engineering, University of Tabriz, Tabriz, 51666, Iran

    Hojjatollah Fouladi Osgouei & Mahdi Zarghami

  2. East Azarbaijan Regional Water Company, Tabriz, 51569, Iran

    Hojjatollah Fouladi Osgouei

  3. Department of Civil and Environmental Eng., Tufts University, Medford, MA, 02155, USA

    Mahdi Zarghami

  4. Sociotechnical Systems Research Center, Massachusetts Institute of Technology, Cambridge, MA, 02142, USA

    Mahdi Zarghami

  5. Department of Civil and Environmental Engineering, University of California, Irvine, CA, 92697, USA

    Hamed Ashouri

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  1. Hojjatollah Fouladi Osgouei
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  2. Mahdi Zarghami
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  3. Hamed Ashouri
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Correspondence to Mahdi Zarghami.

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Fouladi Osgouei, H., Zarghami, M. & Ashouri, H. Disaggregating radar-derived rainfall measurements in East Azarbaijan, Iran, using a spatial random-cascade model. Theor Appl Climatol 129, 427–435 (2017). https://doi.org/10.1007/s00704-016-1784-z

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  • DOI: https://doi.org/10.1007/s00704-016-1784-z

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