Articles | Volume 15, issue 22
Research article
21 Nov 2022
Research article |  | 21 Nov 2022

A CO2-independent cloud mask from Infrared Atmospheric Sounding Interferometer (IASI) radiances for climate applications

Simon Whitburn, Lieven Clarisse, Marc Crapeau, Thomas August, Tim Hultberg, Pierre François Coheur, and Cathy Clerbaux


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-127', Anonymous Referee #1, 25 May 2022
    • AC1: 'Reply on RC1', Simon Whitburn, 05 Sep 2022
  • RC2: 'A good methodological work, which needs some generalization and improvement', Artem Feofilov, 24 Jun 2022
    • AC2: 'Reply on RC2', Simon Whitburn, 05 Sep 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Simon Whitburn on behalf of the Authors (05 Sep 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (03 Oct 2022) by Linlu Mei
Short summary
With more than 15 years of measurements, the IASI radiance dataset is becoming a reference climate data record. Its exploitation for satellite applications requires an accurate and unbiased detection of cloud scenes. Here, we present a new cloud detection algorithm for IASI that is both sensitive and consistent over time. It is based on the use of a neural network, relying on IASI radiance information only and taking as a reference the last version of the operational IASI L2 cloud product.