A Map of Dominant Cloud‐Controlling Factors for Cloud Fraction and Total Liquid Water Path can Identify Marine Low‐Level Cloud Types

Abstract Daily means of Moderate resolution Imaging Spectroradiometer cloud fraction and multi‐sensor advanced climatology total liquid water path (TLWP) products are collected for open ocean regions spanning a 5‐year period. These two cloud properties are analyzed with respect to cloud‐controlling factors, or environmental metrics enabling estimation of changes in clouds given changes in their environment. The cloud data are filtered to only retain days with low‐level clouds, subsidence and surface sensible heat fluxes out of the ocean. Spearman's rank correlation coefficients are calculated in 1° × 1° oceanic boxes for a variety of environmental metrics and the metric with the largest coefficient is mapped. The map of the dominant cloud‐controlling factors (DCCF) for TLWP is presented for the first time with surface wind, column water vapor and a lower‐troposphere stability metric dominating most of the global oceans. When pairing the environmental metrics that dominate for cloud fraction with those that dominate for TLWP, known cloud type regimes emerge on the map including stratocumulus, stratocumulus‐to‐cumulus transition, and trade wind cumulus regimes. In the extratropics, a shortlist of eight metric pairs characterize most oceanic locations. Some pairs are coincident with storm tracks, while others highlight where western boundary currents dominantly influence clouds. Closer to the 30th parallels, metric pairs tend to match those characteristic of subtropical controlling factors on clouds. Overall, the DCCF map can be used to isolate regions with distinct characteristics that are likely important for understanding and representing low‐level cloud feedbacks.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2025-11-26
DOI
https://doi.org/10.1029/2025jd044503
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
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article

A Map of Dominant Cloud‐Controlling Factors for Cloud Fraction and Total Liquid Water Path can Identify Marine Low‐Level Cloud Types

James F. Booth, Gregory S. Elsaesser, Catherine M. Naud
Journal of Geophysical Research Atmospheres
Atmospheric aerosols and clouds
article

A Map of Dominant Cloud‐Controlling Factors for Cloud Fraction and Total Liquid Water Path can Identify Marine Low‐Level Cloud Types

James F. Booth, Gregory S. Elsaesser, Catherine M. Naud
article en

Abstract

Abstract Daily means of Moderate resolution Imaging Spectroradiometer cloud fraction and multi‐sensor advanced climatology total liquid water path (TLWP) products are collected for open ocean regions spanning a 5‐year period. These two cloud properties are analyzed with respect to cloud‐controlling factors, or environmental metrics enabling estimation of changes in clouds given changes in their environment. The cloud data are filtered to only retain days with low‐level clouds, subsidence and surface sensible heat fluxes out of the ocean. Spearman's rank correlation coefficients are calculated in 1° × 1° oceanic boxes for a variety of environmental metrics and the metric with the largest coefficient is mapped. The map of the dominant cloud‐controlling factors (DCCF) for TLWP is presented for the first time with surface wind, column water vapor and a lower‐troposphere stability metric dominating most of the global oceans. When pairing the environmental metrics that dominate for cloud fraction with those that dominate for TLWP, known cloud type regimes emerge on the map including stratocumulus, stratocumulus‐to‐cumulus transition, and trade wind cumulus regimes. In the extratropics, a shortlist of eight metric pairs characterize most oceanic locations. Some pairs are coincident with storm tracks, while others highlight where western boundary currents dominantly influence clouds. Closer to the 30th parallels, metric pairs tend to match those characteristic of subtropical controlling factors on clouds. Overall, the DCCF map can be used to isolate regions with distinct characteristics that are likely important for understanding and representing low‐level cloud feedbacks.

Journal of Geophysical Research AtmospheresVol. 130(23)
City College of New York (US), Applied Mathematics (United States) (US), Columbia University (US)
Openalex Percentile: Top 66%
Atmospheric aerosols and clouds
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