Tracking shallow convective mixing and its influence on low-level clouds with stable water isotopes in vapor

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JGR Atmospheres - 2022 - Hu - Tracking Shallow Convective Mixing and Its Influence on Low‐Level Clouds With Stable Water.pdf (7.25 MB)
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https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2021JD035355

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https://doi.org/10.1029/2021JD035355
 http://hdl.handle.net/11603/24403

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UMBC Mechanical Engineering Department
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2022-02-17

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journal articles
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Citation of Original Publication

Hu, J., Bailey, A., Nusbaumer, J., Dee, S., Sasser, C., & Worden, J. (2022). Tracking shallow convective mixing and its influence on low-level clouds with stable water isotopes in vapor. Journal of Geophysical Research: Atmospheres, 127, e2021JD035355. https://doi.org/10.1029/2021JD035355

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This is a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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Abstract

Low-cloud feedbacks contribute large uncertainties to climate projections and estimated climate sensitivity. A key physical process modulating low-cloud feedbacks is shallow convective mixing between the boundary layer and the free troposphere. However, there are challenges in acquiring observational constraints of shallow convective mixing with global coverage. To this end, we propose a novel approach to constraining convective mixing using stable water vapor isotope profiles from satellite retrievals. We demonstrate that the vertical gradient of water vapor δD between the boundary layer and free troposphere can be used to track shallow convective mixing. Analyzing isotopes in water vapor alongside low-cloud properties from satellite retrievals, we find that low-cloud fraction appears largely insensitive to convective mixing in shallow cumulus regions. Our results also suggest that strong shallow convective mixing is associated with the moistening of the free troposphere. The new estimate of shallow convective mixing and its relationship with low-cloud properties offers a potential constraint on simulations of low-cloud feedbacks and estimates of climate sensitivity.