Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction

<p>Aerosol–cloud interaction (ACI) significantly influences global and regional weather and is a critical focus in numerical weather prediction (NWP), but subgrid-scale ACI effects are often overlooked. Here, a subgrid-scale ACI mechanism is implemented by explicitly treating cloud microphysic...

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Main Authors: W. Zhang, H. Wang, X. Zhang, Y. Peng, Z. Liu, D. Wang, D. Zhang, C. Han, Y. Zhao, J. Zhong, W. Jia, H. Ning, H. Che
Format: Article
Language:English
Published: Copernicus Publications 2025-08-01
Series:Atmospheric Chemistry and Physics
Online Access:https://acp.copernicus.org/articles/25/9005/2025/acp-25-9005-2025.pdf
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author W. Zhang
H. Wang
X. Zhang
Y. Peng
Z. Liu
D. Wang
D. Zhang
C. Han
Y. Zhao
J. Zhong
W. Jia
H. Ning
H. Che
author_facet W. Zhang
H. Wang
X. Zhang
Y. Peng
Z. Liu
D. Wang
D. Zhang
C. Han
Y. Zhao
J. Zhong
W. Jia
H. Ning
H. Che
author_sort W. Zhang
collection DOAJ
description <p>Aerosol–cloud interaction (ACI) significantly influences global and regional weather and is a critical focus in numerical weather prediction (NWP), but subgrid-scale ACI effects are often overlooked. Here, a subgrid-scale ACI mechanism is implemented by explicitly treating cloud microphysics in the KFeta convective scheme with real-time size-resolved hygroscopic aerosol activation and introducing subgrid-scale cloud radiation feedback in an atmospheric chemistry model, CMA_Meso5.1/CUACE. With a focus on summer over central and eastern China, the performance evaluation shows that this developed model with subgrid-scale cloud microphysics and radiation feedback refines cloud representation, even in some grid-scale unsaturated areas, and subsequently leads to attenuated surface downward shortwave radiation (<span class="inline-formula">∼</span> 18.5 W m<span class="inline-formula"><sup>−2</sup></span>) that is more realistic. The increased cloud radiative forcing results in lower temperature (<span class="inline-formula">∼</span> 0.35 °C) and higher relative humidity (<span class="inline-formula">∼</span> 2.5 %) at 2 m, with regional mean bias (MB) decreasing by <span class="inline-formula">∼</span> 40 % and <span class="inline-formula">∼</span> 18.1 %. Temperature vertical structure and relative humidity below <span class="inline-formula">∼</span> 900 hPa are improved accordingly due to cooling and humidifying. The underestimated precipitation is enhanced, especially at the grid scale, thus reducing regional MB by <span class="inline-formula">∼</span> 34.4 % (<span class="inline-formula">∼</span> 1.1 mm). The performance differences between various subregions are related to convective conditions and model local errors. Additionally, compared to simulations with anthropogenic emissions turned off, subgrid-scale actual aerosol inhibits cumulative precipitation during a typical heavy rainfall event by <span class="inline-formula">∼</span> 4.6 mm, aligning it with observations, associated with lower autoconversion at the subgrid scale and less available water vapor for grid-scale condensation, suggesting competition between subgrid- and grid-scale cloud. This study contributes to the understanding of the impact of subgrid-scale ACI on NWP.</p>
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spelling doaj-art-901eaae68dc94cc4bfbe5e8a34b7ea632025-08-20T03:44:09ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242025-08-01259005903010.5194/acp-25-9005-2025Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology predictionW. Zhang0H. Wang1X. Zhang2Y. Peng3Z. Liu4D. Wang5D. Zhang6C. Han7Y. Zhao8J. Zhong9W. Jia10H. Ning11H. Che12State Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaEarth System Modeling and Prediction Centre, China Meteorological Administration, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaInstitute of Energy, Environment and Economy, Tsinghua University, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, ChinaState Key Laboratory of Severe Weather Meteorological Science and Technology, CAMS, Beijing, China<p>Aerosol–cloud interaction (ACI) significantly influences global and regional weather and is a critical focus in numerical weather prediction (NWP), but subgrid-scale ACI effects are often overlooked. Here, a subgrid-scale ACI mechanism is implemented by explicitly treating cloud microphysics in the KFeta convective scheme with real-time size-resolved hygroscopic aerosol activation and introducing subgrid-scale cloud radiation feedback in an atmospheric chemistry model, CMA_Meso5.1/CUACE. With a focus on summer over central and eastern China, the performance evaluation shows that this developed model with subgrid-scale cloud microphysics and radiation feedback refines cloud representation, even in some grid-scale unsaturated areas, and subsequently leads to attenuated surface downward shortwave radiation (<span class="inline-formula">∼</span> 18.5 W m<span class="inline-formula"><sup>−2</sup></span>) that is more realistic. The increased cloud radiative forcing results in lower temperature (<span class="inline-formula">∼</span> 0.35 °C) and higher relative humidity (<span class="inline-formula">∼</span> 2.5 %) at 2 m, with regional mean bias (MB) decreasing by <span class="inline-formula">∼</span> 40 % and <span class="inline-formula">∼</span> 18.1 %. Temperature vertical structure and relative humidity below <span class="inline-formula">∼</span> 900 hPa are improved accordingly due to cooling and humidifying. The underestimated precipitation is enhanced, especially at the grid scale, thus reducing regional MB by <span class="inline-formula">∼</span> 34.4 % (<span class="inline-formula">∼</span> 1.1 mm). The performance differences between various subregions are related to convective conditions and model local errors. Additionally, compared to simulations with anthropogenic emissions turned off, subgrid-scale actual aerosol inhibits cumulative precipitation during a typical heavy rainfall event by <span class="inline-formula">∼</span> 4.6 mm, aligning it with observations, associated with lower autoconversion at the subgrid scale and less available water vapor for grid-scale condensation, suggesting competition between subgrid- and grid-scale cloud. This study contributes to the understanding of the impact of subgrid-scale ACI on NWP.</p>https://acp.copernicus.org/articles/25/9005/2025/acp-25-9005-2025.pdf
spellingShingle W. Zhang
H. Wang
X. Zhang
Y. Peng
Z. Liu
D. Wang
D. Zhang
C. Han
Y. Zhao
J. Zhong
W. Jia
H. Ning
H. Che
Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction
Atmospheric Chemistry and Physics
title Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction
title_full Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction
title_fullStr Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction
title_full_unstemmed Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction
title_short Subgrid-scale aerosol–cloud interaction in the atmospheric chemistry model CMA_Meso5.1/CUACE and its impacts on mesoscale meteorology prediction
title_sort subgrid scale aerosol cloud interaction in the atmospheric chemistry model cma meso5 1 cuace and its impacts on mesoscale meteorology prediction
url https://acp.copernicus.org/articles/25/9005/2025/acp-25-9005-2025.pdf
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