2022 journal article
Image muting of mixed precipitation to improve identification of regions of heavy snow in radar data
ATMOSPHERIC MEASUREMENT TECHNIQUES, 15(18), 5515–5525.
TL;DR:
This work developed an image muting method for regional radar maps that visually de-emphasizes the high reflectivity values associated with mixed precipitation in regions of heavy snow and monitoring real-time weather conditions.
(via Semantic Scholar)
open access via amt.copernicus.org (publisher PDF)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science; OpenAlex)
Source: Web Of Science
Added: October 11, 2022
Abstract. In winter storms, enhanced radar reflectivity is often associated with heavy snow. However, some higher reflectivities are the result of mixed precipitation including melting snow. The correlation coefficient (a dual-polarization radar variable) can identify regions of mixed precipitation, but this information is usually presented separately from reflectivity. Especially under time pressure, radar data users 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 de-emphasizes the high reflectivity values associated with mixed precipitation. These image muted depictions of winter storm precipitation structures are useful for analyzing regions of heavy snow and monitoring real-time weather conditions.