Abstract
Optimal assimilation of meteorological radar data into numerical models requires knowledge of the observation error covariance matrix, i.e., the error variance magnitude at each data point and its correlation to adjacent data points. We use knowledge of basic reflectivity, radial velocity and spectrum width measurements obtainable from most weather radars to determine the instrumentation error component of the complete observation error covariance matrix. Specifically, the technique will be used to ingest radar data into mesoscale numerical weather prediction models. We perform an experimental validation of the predicted errors from the Memphis, Tennessee NEXRAD (WSR-88D) data.
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