Towards a Machine Learning Snowfall Retrieval Algorithm for GPM-IMERG-Reference-Cited by-同舟云学术

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Towards a Machine Learning Snowfall Retrieval Algorithm for GPM-IMERG

Published:2023-08-28 Issue: Volume: Page:
ISSN:
Container-title:16th International Conference on Meteorology, Climatology and Atmospheric Physics—COMECAP 2023
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Author:

Dravilas Ioannis¹^ORCID,Dafis Stavros²^ORCID,Kyros Georgios²^ORCID,Lagouvardos Konstantinos²,Koubarakis Manolis¹

Affiliation:

1. Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, University Campus, Ilissia, 15784 Athens, Greece

2. Institute of Environmental Research and Sustainable Development, National Observatory of Athens, 15236 Athens, Greece

Publisher

MDPI

Link

https://www.mdpi.com/2673-4931/26/1/103/pdf

Reference20 articles.

1. Satellite estimation of falling snow: A global precipitation measurement (GPM) core observatory perspective;Kulie;J. Appl. Meteorol. Clim.,2019

2. A Parameterization of the Probability of Snow–Rain Transition;Sims;J. Hydrometeorol.,2015

3. Sensitivity of Precipitation Phase over the Swiss Alps to Different Meteorological Variables;Froidurot;J. Hydrometeorol.,2014

4. Use of Dual-Wavelength Radar for Snow Parameter Estimates;Liao;J. Atmos. Ocean. Technol.,2005

5. (2023, May 12). NASA GPM, Available online: https://gpm.nasa.gov/resources/faq/how-do-various-forms-precipitation-map-imerg-probabilityliquidprecipitation-data.

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