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.
Aggregation of Ice Crystals in Cirrus
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A simple ice cloud model is shown to behave as a nonlinear oscillator with two Hopf bifurcations, scaling laws, and good agreement with measurements.
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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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Ice clouds as nonlinear oscillators
A simple ice cloud model is shown to behave as a nonlinear oscillator with two Hopf bifurcations, scaling laws, and good agreement with measurements.