Comparison of Global Mesoscale Convective System Simulations in a Global Storm-Resolving Model and a High-Resolution General Circulation Model

Abstract This study compares the characteristics of global mesoscale convective systems (MCSs) simulated in a global storm-resolving model (GSRM) and a high-resolution (∼25-km) general circulation model (GCM), both developed at the Geophysical Fluid Dynamics Laboratory. By comparing with two satellite datasets, we examine the spatial distribution, seasonal/diurnal cycles, and event-based features such as duration, size, intensity, and propagation of MCSs across six global hotspots. MCS-related precipitation features and their contribution to the total precipitation are also analyzed. Our results show that both models effectively capture the observed spatial patterns and seasonal cycles of MCSs, although notable differences exist in absolute values, particularly in the GCM. Both models not only simulate event-based statistics but also show large geographical variations with an overall tendency to produce longer-lasting and larger MCSs. The GSRM performs better in simulating MCS diurnal cycle and MCS intensity. While both models replicate spatial patterns of MCS-related precipitation, they struggle with accurately capturing intensity, and their contributions to total precipitation vary. This comparison highlights strengths and limitations of these two types of models, calling for further process-level investigation of model deficiencies and a detailed evaluation of observations due to dataset discrepancies. Significance Statement Mesoscale convective systems (MCSs) are organized deep convective systems that play a significant role in total precipitation, particularly in tropical and midlatitude regions. Due to their larger spatial coverage and longer lifespan compared to individual thunderstorms, MCSs can cause extreme weather events like flooding, gusty winds, hail, and tornadoes. Accurately simulating MCSs is essential for predicting mean climate patterns and extreme events. In this study, we compared MCS features simulated by a 10-yr high-resolution global climate model (25 km) and a 2-yr global storm-resolving model (3.25 km) developed at the Geophysical Fluid Dynamics Laboratory (GFDL), highlighting the strengths and limitations of each model in capturing MCS features and their interaction with large-scale circulation and climate change.

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Publication Details

Journal
Journal of Climate
Published
2025-03-28
DOI
https://doi.org/10.1175/jcli-d-24-0303.1
Citations
1
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
1.30
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article

Comparison of Global Mesoscale Convective System Simulations in a Global Storm-Resolving Model and a High-Resolution General Circulation Model

Lucas Harris, V. Ramaswamy, Ming Zhao, Huan Guo et al.
1 citations
Journal of Climate
Meteorological Phenomena and Simulations
1.30
article

Comparison of Global Mesoscale Convective System Simulations in a Global Storm-Resolving Model and a High-Resolution General Circulation Model

Lucas Harris, V. Ramaswamy, Ming Zhao, Huan Guo, Linjiong Zhou, Wenhao Dong, Kai-Yuan Cheng
article en
1 citations

Abstract

Abstract This study compares the characteristics of global mesoscale convective systems (MCSs) simulated in a global storm-resolving model (GSRM) and a high-resolution (∼25-km) general circulation model (GCM), both developed at the Geophysical Fluid Dynamics Laboratory. By comparing with two satellite datasets, we examine the spatial distribution, seasonal/diurnal cycles, and event-based features such as duration, size, intensity, and propagation of MCSs across six global hotspots. MCS-related precipitation features and their contribution to the total precipitation are also analyzed. Our results show that both models effectively capture the observed spatial patterns and seasonal cycles of MCSs, although notable differences exist in absolute values, particularly in the GCM. Both models not only simulate event-based statistics but also show large geographical variations with an overall tendency to produce longer-lasting and larger MCSs. The GSRM performs better in simulating MCS diurnal cycle and MCS intensity. While both models replicate spatial patterns of MCS-related precipitation, they struggle with accurately capturing intensity, and their contributions to total precipitation vary. This comparison highlights strengths and limitations of these two types of models, calling for further process-level investigation of model deficiencies and a detailed evaluation of observations due to dataset discrepancies. Significance Statement Mesoscale convective systems (MCSs) are organized deep convective systems that play a significant role in total precipitation, particularly in tropical and midlatitude regions. Due to their larger spatial coverage and longer lifespan compared to individual thunderstorms, MCSs can cause extreme weather events like flooding, gusty winds, hail, and tornadoes. Accurately simulating MCSs is essential for predicting mean climate patterns and extreme events. In this study, we compared MCS features simulated by a 10-yr high-resolution global climate model (25 km) and a 2-yr global storm-resolving model (3.25 km) developed at the Geophysical Fluid Dynamics Laboratory (GFDL), highlighting the strengths and limitations of each model in capturing MCS features and their interaction with large-scale circulation and climate change.

Journal of ClimateVol. 38(10)
NOAA Geophysical Fluid Dynamics Laboratory (US), Princeton University (US), University Corporation for Atmospheric Research (US), Tsinghua University (CN)
Openalex Percentile: Top 25%
Meteorological Phenomena and Simulations
1.30
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