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Coarse-grained stochastic models for tropical convection and climate
Boualem Khouider1, Andrew J Majda, Markos A Katsoulakis
1Courant Institute of Mathematical Sciences and Center for Atmosphere and Ocean Sciences, New York University, New York, NY 10012, USA.
Summary
New stochastic parametrizations for tropical convection improve climate model interactions with small-scale weather. These methods enhance climate simulations by capturing unresolved fluctuations and impacting overall climate patterns.
Area of Science:
- Atmospheric Science
- Climate Modeling
- Computational Fluid Dynamics
Background:
- Tropical convection plays a critical role in global weather patterns and climate.
- Accurately representing small-scale convective processes in climate models remains a significant challenge.
- Existing parameterization schemes often struggle to capture the stochastic nature of convection.
Purpose of the Study:
- To develop and evaluate prototype coarse-grained stochastic parametrizations for tropical convection.
- To enable direct interaction between coarse-grained dynamical variables and unresolved fluctuations.
- To assess the impact of these parametrizations on idealized climate scenarios.
Main Methods:
- Systematically derived birth/death processes for stochastic parametrization.
- Coarse-graining techniques applied to dynamical variables.
- Implementation within an idealized prototype climate scenario.
Main Results:
- The developed parametrizations demonstrated low computational overhead.
- Direct interaction between coarse-grained variables and unresolved fluctuations was achieved.
- Significant impacts on idealized climatology and increased wave fluctuations were observed.
Conclusions:
- Prototype coarse-grained stochastic parametrizations offer a promising approach for representing tropical convection.
- These methods can enhance climate model realism by capturing sub-grid scale processes.
- Further research is warranted to explore their application in more complex climate models.