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A flexible and efficient spatial interpolator for radar rainfall estimation

Author

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  • R. J. Waken
  • Joon Jin Song
  • Soohyun Kwon
  • Ki-Hong Min
  • GyuWon Lee

Abstract

A key challenge in rainfall estimation is spatio-temporal variablility. Weather radars are used to estimate precipitation with high spatial and temporal resolution. Due to the inherent errors in radar estimates, spatial interpolation has been often employed to calibrate the estimates. Kriging is a simple and popular spatial interpolation method, but the method has several shortcomings. In particular, the prediction is quite unstable and often fails to be performed when sample size is small. In this paper, we proposed a flexible and efficient spatial interpolator for radar rainfall estimation, with several advantages over kriging. The method is illustrated using a real-world data set.

Suggested Citation

  • R. J. Waken & Joon Jin Song & Soohyun Kwon & Ki-Hong Min & GyuWon Lee, 2018. "A flexible and efficient spatial interpolator for radar rainfall estimation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(5), pages 829-844, April.
    • Handle: RePEc:taf:japsta:v:45:y:2018:i:5:p:829-844
    DOI: 10.1080/02664763.2017.1317723
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