Collection Nonlinear and stochastic methods in climate and geophysical fluid dynamics
Organizer(s)
Date(s)
20/04/2024
Stochastic process models for precipitation processes in dialogue with observational and climate model diagnostics
By David Neelin
Stochastic process models based on simplifications of climate model equations suggest that economical assumptions can yield simple connections between underlying physics and important aspects of observed precipitation statistics and their relationship to the water vapor-temperature environment. These include characteristic shapes of probability distributions of precipitation accumulations, time-averaged intensities and spatial clusters, and factors controlling changes in extremes. The memory associated with prognostic water vapor permits understanding of relationships between wet and dry regimes, and probability distributions across these. A dialogue between such theoretical underpinnings, observational analysis and pragmatic diagnostics forclimate models aims to help understand biases in the large numerical models and aspects of the stochastic models that should be expanded.
Joint work with: Yi-Hung Kuo, Cristian Martinez-Villalobos, Fiaz Ahmed
