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How well can brightness temperature differences of spaceborne imagers help to detect cloud phase? A sensitivity analysis regarding cloud phase and related cloud properties

Authors :
J. Mayer
B. Mayer
L. Bugliaro
R. Meerkötter
C. Voigt
Source :
Atmospheric Measurement Techniques, Vol 17, Pp 5161-5185 (2024)
Publication Year :
2024
Publisher :
Copernicus Publications, 2024.

Abstract

This study investigates the sensitivity of two brightness temperature differences (BTDs) in the infrared (IR) window of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) to various cloud parameters in order to understand their information content, with a focus on cloud thermodynamic phase. To this end, this study presents radiative transfer calculations, providing an overview of the relative importance of all radiatively relevant cloud parameters, including thermodynamic phase, cloud-top temperature (CTT), optical thickness (τ), effective radius (Reff), and ice crystal habit. By disentangling the roles of cloud absorption and scattering, we are able to explain the relationships of the BTDs to the cloud parameters through spectral differences in the cloud optical properties. In addition, an effect due to the nonlinear transformation from radiances to brightness temperatures contributes to the specific characteristics of the BTDs and their dependence on τ and CTT. We find that the dependence of the BTDs on phase is more complex than sometimes assumed. Although both BTDs are directly sensitive to phase, this sensitivity is comparatively small in contrast to other cloud parameters. Instead, the primary link between phase and the BTDs lies in their sensitivity to CTT (or more generally the surface–cloud temperature contrast), which is associated with phase. One consequence is that distinguishing high ice clouds from low liquid clouds is straightforward, but distinguishing mid-level ice clouds from mid-level liquid clouds is challenging. These findings help to better understand and improve the working principles of phase retrieval algorithms.

Details

Language :
English
ISSN :
18671381 and 18678548
Volume :
17
Database :
Directory of Open Access Journals
Journal :
Atmospheric Measurement Techniques
Publication Type :
Academic Journal
Accession number :
edsdoj.85fed97fde8349399d5b5902da48978d
Document Type :
article
Full Text :
https://doi.org/10.5194/amt-17-5161-2024