A flexible and efficient spatial interpolator for radar rainfall estimation |
| |
| Authors: | R. J. Waken Soohyun Kwon Ki-Hong Min GyuWon Lee |
| |
| Affiliation: | 1. Department of Statistical Science, Baylor University, Waco, TX, USA;2. Department of Astronomy and Atmospheric Sciences, Kyungpook National University, Daegu, Republic of Korea;3. Research and Training Team for Future Creative Astrophysicists and Cosmologist, Kyungpook National University, Daegu, Republic of Korea |
| |
| 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. |
| |
| Keywords: | Radar rainfall estimation spatial prediction spatial-temporal deterministic spatial interpolation uncertainty quantification |
|
|
