Articles | Volume 25, issue 7
Hydrol. Earth Syst. Sci., 25, 3819–3835, 2021
https://doi.org/10.5194/hess-25-3819-2021
Hydrol. Earth Syst. Sci., 25, 3819–3835, 2021
https://doi.org/10.5194/hess-25-3819-2021

Research article 02 Jul 2021

Research article | 02 Jul 2021

Conditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic process

Jieru Yan et al.

Data sets

Supplementary material for the paper "Conditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic process" J. Yan https://doi.org/10.6084/m9.figshare.14864910.v1

Download
Short summary
Accurate spatial precipitation estimates are important in various fields. An approach to simulate spatial rainfall fields conditioned on radar and rain gauge data is proposed. Unlike the commonly used Kriging methods, which provide a Kriged mean field, the output of the proposed approach is an ensemble of estimates that represents the estimation uncertainty. The approach is robust to nonlinear error in radar estimates and is shown to have some advantages, especially when estimating the extremes.