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Project

Development and evaluation of moist physics parameterizations in climate models over the tropics

Over the past decades, climate simulations have benefitted from ever increasing spatial resolution, allowing for a better representation of moist convection and cloud organisation. However, many moist processes are far from being resolved by the primitive equations, and will require advanced parameterizations for many decades to come. Reliability of climate simulations is inherently intertwined with our capability to represent these processes, ranging from microphysics to grey-zone convection. This project is aimed at evaluating current microphysics and grey-zone convection parameterizations for the tropics in the ALARO regional climate model. To this end, state-of-the art observations from the US Department of Energy Atmospheric Radiation Measurement supersites in Darwin, Manaus and Oklahoma will be exploited to advance the existing integrated grey-zone convection and microphysics pacakge in the ALARO model, leading to improved and more reliable simulations for tropical climate.

Date:1 Dec 2022 →  Today
Keywords:Extreme precipitation, Climate modeling, machine learning and remote sensing
Disciplines:Atmospheric physics