Machine learning models recover most warm-rain and ice microphysical process rates from standard ICON model outputs for accumulation intervals of 10 minutes or less using a two-step classification-regression approach with calibrated uncertainty.
and Singer, Clare E
2 Pith papers cite this work. Polarity classification is still indexing.
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physics.ao-ph 2years
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Comparison of NSSL and TEMPO microphysics in MPAS-A shows structural differences in convection but both schemes produce less organized storms and poorer rainfall matches to observations than to each other.
citing papers explorer
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PRecover 1.0: Process Rate Recovery with Machine Learning
Machine learning models recover most warm-rain and ice microphysical process rates from standard ICON model outputs for accumulation intervals of 10 minutes or less using a two-step classification-regression approach with calibrated uncertainty.
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Comparison of Two Operational Microphysics Schemes Across Various Regional-MPAS Simulations
Comparison of NSSL and TEMPO microphysics in MPAS-A shows structural differences in convection but both schemes produce less organized storms and poorer rainfall matches to observations than to each other.