How the representation of microphysical processes affects tropical condensate in the global storm-resolving model ICON

<p>Cloud microphysics is a prime example of processes that remain unresolved in atmospheric modeling at storm-resolving resolution. In this study, we explore how uncertainties in the representation of microphysical processes affect the tropical condensate distribution in a global storm-resolvi...

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Main Authors: A. K. Naumann, M. Esch, B. Stevens
Format: Article
Language:English
Published: Copernicus Publications 2025-06-01
Series:Atmospheric Chemistry and Physics
Online Access:https://acp.copernicus.org/articles/25/6429/2025/acp-25-6429-2025.pdf
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author A. K. Naumann
A. K. Naumann
M. Esch
B. Stevens
author_facet A. K. Naumann
A. K. Naumann
M. Esch
B. Stevens
author_sort A. K. Naumann
collection DOAJ
description <p>Cloud microphysics is a prime example of processes that remain unresolved in atmospheric modeling at storm-resolving resolution. In this study, we explore how uncertainties in the representation of microphysical processes affect the tropical condensate distribution in a global storm-resolving model. We use ICON in its global storm-resolving configuration, with a one- or two-moment microphysical scheme and perform several sensitivity runs, where, in each, we modify parameters of one hydrometeor category of the applied microphysics scheme. Differences between the one- and two-moment schemes are most prominent in partitioning frozen condensate in cloud ice and snow and can be understood in terms of the habit's definition for each scheme, which is associated with different process rates. Overall differences between the simulations are moderate and tend to be larger for individual condensate habits than for more integrated quantities, like cloud fraction or total condensate burden. Yet, the resulting spread in the tropical energy balance of several W m<span class="inline-formula"><sup>−2</sup></span> at the top of the atmosphere and at the surface is substantial. Although the modified parameters within one scheme generally affect different process rates, most of the change in the condensate amount of the modified habit and even the total condensate burden can be attributed to a single property: the change in fall speed. The tropical-mean precipitation efficiency is also well explained by changes in the relative fall speed across different habits in both schemes.</p>
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institution Kabale University
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publishDate 2025-06-01
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spelling doaj-art-8d1a8d717a00486e81769d1fe3097f2e2025-08-20T03:27:17ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242025-06-01256429644410.5194/acp-25-6429-2025How the representation of microphysical processes affects tropical condensate in the global storm-resolving model ICONA. K. Naumann0A. K. Naumann1M. Esch2B. Stevens3Max Planck Institute for Meteorology, Hamburg, GermanyMeteorological Institute, Center for Earth System Research and Sustainability, University of Hamburg, Hamburg, GermanyMax Planck Institute for Meteorology, Hamburg, GermanyMax Planck Institute for Meteorology, Hamburg, Germany<p>Cloud microphysics is a prime example of processes that remain unresolved in atmospheric modeling at storm-resolving resolution. In this study, we explore how uncertainties in the representation of microphysical processes affect the tropical condensate distribution in a global storm-resolving model. We use ICON in its global storm-resolving configuration, with a one- or two-moment microphysical scheme and perform several sensitivity runs, where, in each, we modify parameters of one hydrometeor category of the applied microphysics scheme. Differences between the one- and two-moment schemes are most prominent in partitioning frozen condensate in cloud ice and snow and can be understood in terms of the habit's definition for each scheme, which is associated with different process rates. Overall differences between the simulations are moderate and tend to be larger for individual condensate habits than for more integrated quantities, like cloud fraction or total condensate burden. Yet, the resulting spread in the tropical energy balance of several W m<span class="inline-formula"><sup>−2</sup></span> at the top of the atmosphere and at the surface is substantial. Although the modified parameters within one scheme generally affect different process rates, most of the change in the condensate amount of the modified habit and even the total condensate burden can be attributed to a single property: the change in fall speed. The tropical-mean precipitation efficiency is also well explained by changes in the relative fall speed across different habits in both schemes.</p>https://acp.copernicus.org/articles/25/6429/2025/acp-25-6429-2025.pdf
spellingShingle A. K. Naumann
A. K. Naumann
M. Esch
B. Stevens
How the representation of microphysical processes affects tropical condensate in the global storm-resolving model ICON
Atmospheric Chemistry and Physics
title How the representation of microphysical processes affects tropical condensate in the global storm-resolving model ICON
title_full How the representation of microphysical processes affects tropical condensate in the global storm-resolving model ICON
title_fullStr How the representation of microphysical processes affects tropical condensate in the global storm-resolving model ICON
title_full_unstemmed How the representation of microphysical processes affects tropical condensate in the global storm-resolving model ICON
title_short How the representation of microphysical processes affects tropical condensate in the global storm-resolving model ICON
title_sort how the representation of microphysical processes affects tropical condensate in the global storm resolving model icon
url https://acp.copernicus.org/articles/25/6429/2025/acp-25-6429-2025.pdf
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AT mesch howtherepresentationofmicrophysicalprocessesaffectstropicalcondensateintheglobalstormresolvingmodelicon
AT bstevens howtherepresentationofmicrophysicalprocessesaffectstropicalcondensateintheglobalstormresolvingmodelicon