Abstract
State estimates of mean field bias are based on hourly rain gauge data and hourly accumulations of radar rainfall estimates. The procedures are developed for the precipitation processing system to be used with products of the Next Generation Weather Radar (NEXRAD) system. To implement the state estimation procedure parameters of the bias model must be specified. The performance of the state estimation is investigated within a Monte Carlo simulation framework. The results highlight the dependence of the state estimation problem on the parameter estimation problem. The second experiment addresses the problem of converting radar-measured reflectivity into rainfall rate. This is typically done using a Z-R relationship. The parameters of such relationship can be estimated using climatological data and nonparametric estimation framework. In the paper the effects of thresholds imposed on the observations included in the estimation are investigated. -from Authors
Original language | English (US) |
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Pages (from-to) | 181-189 |
Number of pages | 9 |
Journal | Unknown Journal |
DOIs | |
State | Published - 1995 |
All Science Journal Classification (ASJC) codes
- General Environmental Science
- General Earth and Planetary Sciences