Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-06T00:54:52.265Z Has data issue: false hasContentIssue false

Application of GIS for processing and establishing the correlation between weather radar reflectivity and precipitation data

Published online by Cambridge University Press:  12 April 2005

Y. Gorokhovich
Affiliation:
Center for International Earth Science Information Network, Columbia University, Lamont-Doherty Earth Observatory, 61 Route 9W, PO Box 1000, Palisades, NY 10964, USA Email: [email protected]
G. Villarini
Affiliation:
IIHR-Hydroscience & Engineering, University of Iowa, Iowa City, Iowa Email: [email protected]
Get access

Abstract

Correlation between weather radar reflectivity and precipitation data collected by rain gauges allows empirical formulae to be obtained that can be used to create continuous rainfall surfaces from discrete data. Such surfaces are useful in distributed hydrologic modelling and early warning systems in flood management. Because of the spatial relationship between rain gauge locations and radar coverage area, GIS provides the basis for data analysis and manipulation. A database of 82 radar stations and more than 1500 rain gauges in continental USA was compiled and used for the continuous downloading of radar images and rain data. Image sequences corresponding to rain events were extracted for two randomly selected radar stations in South and North Carolina. Rainfall data from multiple gauges within the radar zone of 124 nautical miles (nm) (∼230 km) were extracted and combined with corresponding reflectivity values for each time interval of the selected rain event. Data were normalised to one-hour intervals and then statistical analysis was applied to study the potential correlation. Results of regression analysis showed a significant correlation between rain gauge data and radar reflectivity values and allowed derivation of empirical formulae.

Type
Research Article
Copyright
© 2005 Royal Meteorological Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)