Rainfall estimation using raingages and radar - a Bayesian approach. I: Derivation of estimators
type: Item
instance of: scholarly article
title: Rainfall estimation using raingages and radar - a Bayesian approach. I: Derivation of estimators
zbMATH Open document ID: 0729.62109
DOI: 10.1007/BF01544175
author: N. E. Zubov
published in: Stochastic Hydrology and Hydraulics
publication date: 1991-01-01T00:00:00Z
review text: Procedures for estimating rainfall from radar and raingage observations are constructed in a Bayesian framework. Given that the number of raingage measurements is typically very small, mean and variance of gage rainfall are treated as uncertain parameters. Under the assumption that log gage rainfall and log radar rainfall are jointly multivariate normal, the estimation problem is equivalent to lognormal co-kriging with uncertain mean and variance of the gage rainfall field. The posterior distribution is obtained under the assumption that the prior for the mean and inverse of the variance of log gage rainfall is normal-gamma 2. Estimate and estimation variance do not have closed-form expressions, but can be easily numerically evaluated.
Mathematics Subject Classification ID: 62P99
Mathematics Subject Classification ID: 86A10
Mathematics Subject Classification ID: 62F15
Mathematics Subject Classification ID: 86A05
zbMATH DE Number: 4205698
zbMATH Keywords: rainfall estimation
zbMATH Keywords: parameter uncertainty
zbMATH Keywords: gage rainfall
zbMATH Keywords: log gage rainfall
zbMATH Keywords: log radar rainfall
zbMATH Keywords: lognormal co-kriging
MaRDI profile type: Publication
cites work: Q5558293
cites work: Q4497726
cites work: Q3073613
cites work: Q5659019
description: scientific article; zbMATH DE number 4205698