Satellite Retrievals Show Adiabatic Fraction of Marine Low Clouds Decreasing With Increasing Temperature and Height Above Cloud Base DOI Creative Commons
Xin Lü, Daniel Rosenfeld, Yannian Zhu

et al.

Journal of Geophysical Research Atmospheres, Journal Year: 2025, Volume and Issue: 130(5)

Published: March 8, 2025

Abstract Cloud adiabatic fraction (f ad ) is an important metric that quantitatively characterizes the impact of atmospheric mixing on cloud thermodynamic properties. Due to lack vertical profiling water, previous studies variability f within clouds have been confined single scales. Our prior research achieved a breakthrough in large‐scale retrieval fraction, while it only provided two‐dimensional information leaving variation in‐cloud unquantified. In this study, utilizing global‐scale data derived from our research, we developed predictive function for global marine low‐cloud based geometric thickness and base temperature (CBT). This enabled us successfully estimate distributions across various conditions scale. The exhibits quadratic reduction top, which more pronounced at higher temperatures. Specifically, as CBT rises 2 24°C, diminishes 0.85 0.23. decreasing trend with increasing temperatures expected reduce albedo coverage potentially constituting positive radiative feedback mechanism.

Language: Английский

Satellite Retrievals Show Adiabatic Fraction of Marine Low Clouds Decreasing With Increasing Temperature and Height Above Cloud Base DOI Creative Commons
Xin Lü, Daniel Rosenfeld, Yannian Zhu

et al.

Journal of Geophysical Research Atmospheres, Journal Year: 2025, Volume and Issue: 130(5)

Published: March 8, 2025

Abstract Cloud adiabatic fraction (f ad ) is an important metric that quantitatively characterizes the impact of atmospheric mixing on cloud thermodynamic properties. Due to lack vertical profiling water, previous studies variability f within clouds have been confined single scales. Our prior research achieved a breakthrough in large‐scale retrieval fraction, while it only provided two‐dimensional information leaving variation in‐cloud unquantified. In this study, utilizing global‐scale data derived from our research, we developed predictive function for global marine low‐cloud based geometric thickness and base temperature (CBT). This enabled us successfully estimate distributions across various conditions scale. The exhibits quadratic reduction top, which more pronounced at higher temperatures. Specifically, as CBT rises 2 24°C, diminishes 0.85 0.23. decreasing trend with increasing temperatures expected reduce albedo coverage potentially constituting positive radiative feedback mechanism.

Language: Английский

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