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- Title
Improvements on Phase Classification Using Atmospheric Melting and Refreezing Energy Based on Soundings.
- Authors
Shi, Shangyong; Liu, Guosheng
- Abstract
Determining precipitation as solid (snow) or liquid (rain) phase is crucial for remote sensing of precipitation. Most phase classification methods rely on near‐surface temperatures. Further attempts to incorporate atmospheric information aloft only achieved mixed level of success, particularly for precipitation with temperature inversion. In our study, we developed a phase classification scheme based on the upper‐level melting energy (ME) and refreezing energy (RE), which is proportional to the area enclosed by the temperature profile and the 0°C isotherm. We performed least squares fitting and linear discriminant analysis to derive phase separation functions using observed surface and sounding data in North America. We provided separation functions for snow conditional probabilities ranging from 30% to 80% for various applications. Compared to a previously published (Probsnow) method, our energy method achieved comparable performance for Type 1 soundings with one near‐surface melting layer, and significantly improves the phase classification scores for Type 2 soundings with an aloft melting layer and a near‐surface refreezing layer. We innovatively combined surface ice‐bulb temperature with the ratio between the ME and RE to represent Type 2 profiles. For Type 2 soundings, our energy method improves the Heidke skill score (HSS) from 0.25 to 0.47 and reduces false alarm rate (FAR) by 0.47 compared to the Probsnow method for 50% threshold. By applying the physically based method, we improved accuracy and HSS, and reduced FAR for more than two thirds of the evaluation stations across the North America. Finally, we tested the application of the new method in satellite snowfall retrievals. Plain Language Summary: In this study, we developed a method to determine whether precipitation is in the form of snow or rain, which is important for weather forecast, modeling, and snowfall measurements with radar. We used atmospheric melting and refreezing energy to represent the physical process that falling precipitation undergoes. Two types of atmosphere structures were considered: melting near the surface (Type 1), and melting‐refreezing profiles (Type 2). Compared to a previous method, we achieved comparable performance for the Type 1 soundings, and achieved major improvements for the Type 2 soundings, where the process of melting and refreezing was not well‐represented by previous methods. Our new method was tested in North America and showed improvements in most stations. The improvements in phase prediction for Type 2 soundings contribute significantly to the overall phase classification for most stations in the North America. Finally, we tested our method for satellite snowfall retrievals. For future applications, we offer different separation functions for various thresholds of the conditional probability of snow to meet different prediction needs. Key Points: We developed a physically based phase classification scheme for two typical types of soundings by incorporating the atmospheric energyWe greatly improved phase prediction for Type 2 sounding, which features a melt‐and‐refreeze process poorly represented by prior methodsWe evaluated the phase classification with a 50% snow probability threshold for North America stations and observed prominent improvements
- Subjects
NORTH America; FISHER discriminant analysis; SOUND energy; TEMPERATURE inversions; MELTING; PHASE separation
- Publication
Journal of Geophysical Research. Atmospheres, 2024, Vol 129, Issue 10, p1
- ISSN
2169-897X
- Publication type
Article
- DOI
10.1029/2023JD040030