Articles | Volume 21, issue 2
Research article
26 Jan 2021
Research article |  | 26 Jan 2021

3D radiative heating of tropical upper tropospheric cloud systems derived from synergistic A-Train observations and machine learning

Claudia J. Stubenrauch, Giacomo Caria, Sofia E. Protopapadaki, and Friederike Hemmer


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Claudia Stubenrauch on behalf of the Authors (19 Nov 2020)  Author's response    Manuscript
ED: Publish as is (24 Nov 2020) by Manish Shrivastava
Short summary
Tropical anvils formed by convective outflow play a crucial role in modulating the Earth’s energy budget and heat transport. To explore the relation between these anvils and convection, we built 3D radiative heating fields, based on machine learning employed on cloud and atmospheric properties from IR sounder and meteorological reanalyses, trained on lidar–radar retrievals. The 15-year time series reveals colder convective systems during warm periods, affecting the atmospheric heating structure.
Final-revised paper