Articles | Volume 17, issue 11
https://doi.org/10.5194/amt-17-3377-2024
https://doi.org/10.5194/amt-17-3377-2024
Research article
 | 
03 Jun 2024
Research article |  | 03 Jun 2024

Dual adaptive differential threshold method for automated detection of faint and strong echo features in radar observations of winter storms

Laura M. Tomkins, Sandra E. Yuter, and Matthew A. Miller

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Cited articles

Ansari, S., Greco, S. D., Kearns, E., Brown, O., Wilkins, S., Ramamurthy, M., Weber, J., May, R., Sundwall, J., Layton, J., Gold, A., Pasch, A., and Lakshmanan, V.: Unlocking the Potential of NEXRAD Data through NOAA's Big Data Partnership, B. Am. Meteorol. Soc., 99, 189–204, https://doi.org/10.1175/BAMS-D-16-0021.1, 2018. a
Arkin, P. A. and Meisner, B. N.: The Relationship between Large-Scale Convective Rainfall and Cold Cloud over the Western Hemisphere during 1982–84, Mon. Weather Rev., 115, 51–74, https://doi.org/10.1175/1520-0493(1987)115<0051:TRBLSC>2.0.CO;2, 1987. a
Amazon Web Services (AWS): Next Generation Weather Radar (NEXRAD), https://registry.opendata.aws/noaa-nexrad, last access: 7 November 2023. a
Baxter, M. A. and Schumacher, P. N.: Distribution of Single-Banded Snowfall in Central U. S. Cyclones, Weather Forecast., 32, 533–554, https://doi.org/10.1175/WAF-D-16-0154.1, 2017. a, b, c
Bullock, R. G., Brown, B. G., and Fowler, T. L.: Method for Object-Based Diagnostic Evaluation, NCAR Technical Note, https://doi.org/10.5065/D61V5CBS, 2016. a
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Short summary
We have created a new method to better identify enhanced features in radar data from winter storms. Unlike the clear-cut features seen in warm-season storms, features in winter storms are often fuzzier with softer edges. Our technique is unique because it uses two adaptive thresholds that change based on the background radar values. It can identify both strong and subtle features in the radar data and takes into account uncertainties in the detection process.