Heuristic estimation of low-level cloud fraction over the globe based on a decoupling parameterization

Park, Sungsu; Shin, Jihoon

doi:https://doi.org/10.5194/acp-19-5635-2019

Articles | Volume 19, issue 8

https://doi.org/10.5194/acp-19-5635-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-19-5635-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 8

Research article

|

30 Apr 2019

Research article |

| 30 Apr 2019

Heuristic estimation of low-level cloud fraction over the globe based on a decoupling parameterization

Sungsu Park and Jihoon Shin

Supplement

https://doi.org/10.5194/acp-19-5635-2019-supplement

Data sets

Extended Edited Synoptic Cloud Reports Archive (EECRA) from Ships and Land Stations Over the Globe Fleet Numerical Meteorology and Oceanography Center/U.S. Navy/U. S. Department of Defense, Department of Atmospheric Science/University of Washington, Department of Atmospheric Sciences/University of Arizona, and National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce http://rda.ucar.edu/datasets/ds292.2/

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Short summary

Clouds exert substantial impacts on the global radiation budget and hydrological cycle. We propose a new proxy for the observed low-level cloud amount (LCA), so-called ELF (estimated low-level cloud fraction), and we show that ELF achieves the unprecedented best performance in diagnosing spatiotemporal variations of the observed LCA. Our study can be used to evaluate the performance of GCMs, identify the source of inaccurate simulation of LCA, and better understand climate sensitivity.