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Optimal merging of multi-satellite precipitation data in urban areas

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Abstract

This paper develops and applies algorithms for optimally merging satellite precipitation products with rain-gauge precipitation for accurate rainfall estimation. The satellite-based precipitation products (SBPs) PERSIANN-CDR, TMPA-3B42, GPM-IMERG, and GSMaP MKV are combined and evaluated to generate accurate rainfall estimates. Daily satellite precipitation data are compared with corresponding station data to calculate the bias for the period 2014–2019. Three different algorithms are proposed whose adjustable parameters are optimally determined by solving constrained optimization algorithms to produce combinations of satellite-based precipitation products. The optimal combination is named optimally merged satellite-based precipitation (OMSBP). The root mean square error (RMSE), coefficient correlation (CC), and the Nash–Sutcliffe error (NSE) are employed to test the proposed method with precipitation data for the Tehran urban region, Iran. The spatially resolved results over the studied urban area establish that TMPA-3B42, with an average value MAE, MBE, and RMSE equal to 0.68 mm, − 0.31 mm, and 2.94 mm, leads to better estimates of precipitation than those of PERSIANN-CDR, IMERG, and GSMaP MKV. Moreover, algorithms alg7 and alg8 yielded better results with respect to the MAE and MBE, respectively. Lastly, algorithm alg3 produced better results than alg7 and alg8 based on the RMSE, NSE, and CC corresponding to precipitation predictions.

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Acknowledgements

The authors thank Iran’s National Science Foundation (INSF) for its support of this research.

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Authors and Affiliations

  1. Department of Irrigation & Reclamation Engineering, College of Agriculture & Natural Resources, University of Tehran, Tehran, Iran

    Arman Oliazadeh & Omid Bozorg-Haddad

  2. Disasters and Climate Change Group, Climatological Research Institute (CRI), Atmospheric Science and Meteorological Research Center (ASMERC), Mashhad, Iran

    Morteza Pakdaman

  3. Department of Agriculture and Biological Engineering, Mississippi State University, Starkville, MS, 39762, USA

    Ramin Baghbani

  4. Department of Geography, University of California, Santa Barbara, CA, 93016-4060, USA

    Hugo A. Loáiciga

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  1. Arman Oliazadeh
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  2. Omid Bozorg-Haddad
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  3. Morteza Pakdaman
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  4. Ramin Baghbani
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  5. Hugo A. Loáiciga
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Contributions

Arman Oliazadeh: software, formal analysis, writing — original draft.

Omid Bozorg-Haddad: conceptualization, supervision, project administration.

Morteza Pakdaman: software, formal analysis, writing — original draft.

Ramin Baghbani: software, formal analysis, writing — original draft.

Hugo A. Loáiciga: validation, writing, equations — review and editing.

Corresponding author

Correspondence to Omid Bozorg-Haddad.

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Oliazadeh, A., Bozorg-Haddad, O., Pakdaman, M. et al. Optimal merging of multi-satellite precipitation data in urban areas. Theor Appl Climatol 147, 1697–1712 (2022). https://doi.org/10.1007/s00704-021-03895-4

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