Articles | Volume 18, issue 12
https://doi.org/10.5194/gmd-18-3559-2025
https://doi.org/10.5194/gmd-18-3559-2025
Model evaluation paper
 | 
18 Jun 2025
Model evaluation paper |  | 18 Jun 2025

Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data

Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee

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Cited articles

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Bang, W. and Kim, K.: Plot program for MRR data of ICE-POP 2018, Zenodo [code], https://doi.org/10.5281/zenodo.14352684, 2024. 
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Short summary
Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
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