Articles | Volume 15, issue 18
https://doi.org/10.5194/amt-15-5515-2022
https://doi.org/10.5194/amt-15-5515-2022
Research article
 | 
28 Sep 2022
Research article |  | 28 Sep 2022

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

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

Related authors

Objective identification of pressure wave events from networks of 1 Hz, high-precision sensors
Luke R. Allen, Sandra E. Yuter, Matthew A. Miller, and Laura M. Tomkins
Atmos. Meas. Tech., 17, 113–134, https://doi.org/10.5194/amt-17-113-2024,https://doi.org/10.5194/amt-17-113-2024, 2024
Short summary
Detecting wave features in Doppler radial velocity radar observations
Matthew A. Miller, Sandra E. Yuter, Nicole P. Hoban, Laura M. Tomkins, and Brian A. Colle
Atmos. Meas. Tech., 15, 1689–1702, https://doi.org/10.5194/amt-15-1689-2022,https://doi.org/10.5194/amt-15-1689-2022, 2022
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
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
Atmos. Meas. Tech., 17, 3377–3399, https://doi.org/10.5194/amt-17-3377-2024,https://doi.org/10.5194/amt-17-3377-2024, 2024
Short summary
Noise filtering options for conically scanning Doppler lidar measurements with low pulse accumulation
Eileen Päschke and Carola Detring
Atmos. Meas. Tech., 17, 3187–3217, https://doi.org/10.5194/amt-17-3187-2024,https://doi.org/10.5194/amt-17-3187-2024, 2024
Short summary
Measuring rainfall using microwave links: the influence of temporal sampling
Luuk D. van der Valk, Miriam Coenders-Gerrits, Rolf W. Hut, Aart Overeem, Bas Walraven, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 2811–2832, https://doi.org/10.5194/amt-17-2811-2024,https://doi.org/10.5194/amt-17-2811-2024, 2024
Short summary
Drone-based photogrammetry combined with deep learning to estimate hail size distributions and melting of hail on the ground
Martin Lainer, Killian P. Brennan, Alessandro Hering, Jérôme Kopp, Samuel Monhart, Daniel Wolfensberger, and Urs Germann
Atmos. Meas. Tech., 17, 2539–2557, https://doi.org/10.5194/amt-17-2539-2024,https://doi.org/10.5194/amt-17-2539-2024, 2024
Short summary
The High lAtitude sNowfall Detection and Estimation aLgorithm for ATMS (HANDEL-ATMS): a new algorithm for snowfall retrieval at high latitudes
Andrea Camplani, Daniele Casella, Paolo Sanò, and Giulia Panegrossi
Atmos. Meas. Tech., 17, 2195–2217, https://doi.org/10.5194/amt-17-2195-2024,https://doi.org/10.5194/amt-17-2195-2024, 2024
Short summary

Cited articles

Alku, L., Moisseev, D., Aittomäki, T., and Chandrasekar, V.: Identification and Suppression of Nonmeteorological Echoes Using Spectral Polarimetric Processing, IEEE T. Geosci. Remote, 53, 3628–3638, https://doi.org/10.1109/TGRS.2014.2380476, 2015. a
Ansari, S., Del Greco, S., 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
Battan, L. J.: Radar observation of the atmosphere, University of Chicago Press, Chicago, ISBN-10: 1878907271, ISBN-13: 978-1878907271, 1973. a
Bringi, V. and Chandrasekar, V.: Polarimetric Doppler Weather Radar: Principles and Applications, Cambridge University Press, ISBN-13: 978-0521623841, ISBN-10: 0521623847, 2001. a, b
Calvo, L., Christel, I., Terrado, M., Cucchietti, F., and Pérez-Montoro, M.: Users' Cognitive Load: A Key Aspect to Successfully Communicate Visual Climate Information, B. Am. Meteorol. Soc., 103, E1–E16, 2021. a
Download
Short summary
Locally higher radar reflectivity values in winter storms can mean more snowfall or a transition from snow to mixtures of snow, partially melted snow, and/or rain. We use the correlation coefficient to de-emphasize regions of mixed precipitation. Visual muting is valuable for analyzing and monitoring evolving weather conditions during winter storm events.