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Updated: Jun 27, 2026
11:03
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
Published on: December 4, 2017
Stochastic models for convective momentum transport.
Andrew J Majda1, Samuel N Stechmann
1Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute, New York University, New York, NY 10012, USA. jonjon@cims.nyu.edu
Summary
This study introduces stochastic models to improve how computer models represent tropical convection, specifically convective momentum transport (CMT). These models better capture how small-scale weather events impact large-scale forecasts and climate change predictions.
Area of Science:
- Atmospheric Science
- Climate Modeling
- Computational Physics
Background:
- Accurate parameterization of tropical convection is crucial for long-range weather forecasting and climate change studies.
- Current computer models exhibit deficiencies in representing convective momentum transport (CMT) from sub-grid scales to larger scales.
- This gap hinders the precise simulation of tropical weather phenomena and climate dynamics.
Purpose of the Study:
- To develop simple stochastic models for representing convective momentum transport (CMT).
- To address the challenge of parameterizing unresolved tropical convection in large-scale models.
- To investigate the impact of improved CMT parameterization on weather and climate simulations.
Main Methods:
- Utilized a combination of mathematical and physical reasoning to construct stochastic models.
- Employed a test column model to analyze the properties of the stochastic CMT model for large-scale variables.
- Investigated the effects of the stochastic CMT model on a large-scale convectively coupled wave in an idealized setting.
Main Results:
- The developed stochastic models effectively capture intermittent upscale transports of CMT from organized unresolved convection.
- Upscale transports from stochastic effects were found to be significant in a test column model.
- The model generated a large-scale mean flow that can interact with convectively coupled waves.
Conclusions:
- The stochastic modeling approach offers a promising method to improve the parameterization of unresolved tropical convection.
- Accurate representation of CMT is vital for enhancing the fidelity of weather and climate models.
- The findings suggest potential improvements for long-range ensemble forecasting and short-term climate change predictions.
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