Affiliation:
1. a Atmospheric Observations Research Group, University of Queensland, Saint Lucia, Queensland, Australia
2. b Science and Innovation Group, Australian Bureau of Meteorology, Docklands, Victoria, Australia
Abstract
Abstract
Observations made by weather radars play a central role in many aspects of meteorological research and forecasting. These applications commonly require that radar data be supplied on a Cartesian grid, necessitating a coordinate transformation and interpolation from the radar’s native spherical geometry using a process known as gridding. In this study, we introduce a variational gridding method and, through a series of theoretical and real data experiments, show that it outperforms existing methods in terms of data resolution, noise filtering, spatial continuity, and more. Known problems with existing gridding methods (Cressman weighted average and nearest neighbor/linear interpolation) are also underscored, suggesting the potential for substantial improvements in many applications involving gridded radar data, including operational forecasting, hydrological retrievals, and three-dimensional wind retrievals.
Funder
Guy Carpenter & Company Pty Ltd
Publisher
American Meteorological Society
Subject
Atmospheric Science,Ocean Engineering
Cited by
6 articles.
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