paper
2026
Hybrid physics-ML & parameterization
New model or method
Physics-informed / physics-constrainedUniversity of Oxford Other
2026-02-07
022
Feb 2026
Kang‐En Huang, Minghuai Wang, Philip Stier et al.
preprint
University of Oxford
Monotonic Mass Partition embeddings with physics-informed rate models give stable ML emulators of cloud collision-coalescence that best predict precipitation onset.
Hybrid physics-ML & parameterization
Physics-Constrained Reduced-Order Modeling of Collision-Coalescence with Advectable Embeddings: Monotonic Mass Partition Scheme
In one sentence. Monotonic Mass Partition embeddings with physics-informed rate models give stable ML emulators of cloud collision-coalescence that best predict precipitation onset.
Labels
- Topic
- Hybrid physics-ML & parameterization
- Type
- New model or method
- Method
- Physics-informed / physics-constrained
- Domain
- Local / station
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.22541/essoar.177046617.70989390/v1 OpenAlex:W7128296928
- Added
- 2026-10-22
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