Articles | Volume 14, issue 4
Atmos. Meas. Tech., 14, 2957–2979, 2021
Atmos. Meas. Tech., 14, 2957–2979, 2021

Research article 20 Apr 2021

Research article | 20 Apr 2021

Can machine learning correct microwave humidity radiances for the influence of clouds?

Inderpreet Kaur et al.


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 Inderpreet Kaur on behalf of the Authors (04 Mar 2021)  Author's response    Manuscript
ED: Publish as is (08 Mar 2021) by S. Joseph Munchak
Short summary
Currently, cloud contamination in microwave humidity channels is addressed using filtering schemes. We present an approach to correct the cloud-affected microwave humidity radiances using a Bayesian machine learning technique. The technique combines orthogonal information from microwave channels to obtain a probabilistic prediction of the clear-sky radiances. With this approach, we are able to predict bias-free clear-sky radiances with well-represented case-specific uncertainty estimates.