Modulation Effects of Atmospheric Environmental Conditions on Mesoscale Convective Systems over Tropical Oceans
Huaiping Wang, Qiu Yang

TL;DR
This study quantifies how environmental factors like moisture and atmospheric instability influence tropical mesoscale convective systems, revealing regional and seasonal variability using satellite data and machine learning.
Contribution
It constructs a comprehensive observational dataset and applies a Random Forest model to quantify environmental controls on tropical MCSs at the monthly scale.
Findings
Environmental predictors explain up to 50% of MCS frequency variance.
Moisture convergence and water vapor are key controlling factors.
Nonlinear interactions among predictors vary regionally and seasonally.
Abstract
Mesoscale convective systems MCSs play a central role in tropical rainfall and are closely linked to extreme precipitation and large scale variability. However, a quantitative understanding of their environmental controls remains incomplete. In this study, we construct an observational MCS dataset by applying an objective tracking algorithm to satellite and reanalysis data, and examine the climatology of tropical MCSs. We further use a Random Forest model to quantify environmental controls at the monthly scale. The results show pronounced spatial and seasonal variability in tropical MCS activity, closely tied to large scale circulation and moisture availability. Environmental predictors explain up to about 50\% of the variance in monthly MCS frequency and associated precipitation. Moisture convergence atmospheric instability and column integrated water vapor emerge as the leading…
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