JSM 2005 - Toronto

Abstract #304276

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 403
Type: Contributed
Date/Time: Wednesday, August 10, 2005 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract - #304276
Title: Calibration of Texas Radar Rainfall Estimates by Rain Gauge Data
Author(s): Bo Li*+ and Michael Sherman and Raymond J. Carroll and Marian Eriksson and Raghavan Srinivasan
Companies: Texas A&M University and Texas A&M University and Texas A&M University and Texas A&M University and Texas A&M University
Address: 309 Ball Street Apt1032, College Station, TX, 77840, United States
Keywords: calibration ; rain gauge ; WSR-88D ; threshold ; geostatistics
Abstract:

Rainfall is one of the most important hydrologic model inputs and recognized as a random process in time and space. Rain gauges generally provide good quality data, however they are usually too sparse to capture the spatial variability. Radar estimates provide the better spatial representation of rainfall patterns, but they are subject to substantial biases. The calibration of radar estimates using gauge data take season, rainfall type, and rainfall amount into account. It is accomplished through a combination of estimating threshold for NexRad data, removing bias in NexRad data by linear regression, and modeling the linear regression residuals using geostatistical procedures. Different methods in threshold estimation, linear regression, and variogram estimation are employed and the results are compared. The methods are illustrated using Texas rainfall data in 2003, which includes WSR-88D radar-reflectivity data and the corresponding rain gauge measurements. Simulation also is used to verify the accuracy of the methods.

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Revised March 2005