Image muting of mixed precipitation to improve identification of regions of heavy snow in radar data

Autor: Laura M. Tomkins, Sandra E. Yuter, Matthew A. Miller, Luke R. Allen
Rok vydání: 2022
Předmět:
Zdroj: Atmospheric Measurement Techniques. 15:5515-5525
ISSN: 1867-8548
DOI: 10.5194/amt-15-5515-2022
Popis: In winter storms, enhanced radar reflectivity is often associated with heavy snow; however, some higher reflectivities are the result of melting and mixed precipitation. The correlation coefficient (a dual-polarization radar variable) can identify regions of and mixed precipitation, but this information is usually presented separately from reflectivity. Especially under time pressure, even experienced meteorologists can mistake regions of mixed precipitation for heavy snow because of the high cognitive load associated with comparing data in two fields while simultaneously attempting to discount a portion of the high reflectivity values. We developed an image muting method for regional radar maps that visually deemphasizes the high reflectivity values associated with mixed precipitation. These image muted depictions of winter storm precipitation structures are useful for monitoring real-time weather conditions and for analyzing storms.
Databáze: OpenAIRE
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