On the Scattering-Angle Dependence of the Spectral Consistency of Ice Cloud Optical Thickness Retrievals Based on Geostationary Satellite Observations

Li, ., M. Saito, P. Yang, N. Loeb, W.L. Smith, and P. Minnis (2023), On the Scattering-Angle Dependence of the Spectral Consistency of Ice Cloud Optical Thickness Retrievals Based on Geostationary Satellite Observations, IEEE Trans. Geosci. Remote Sens., 61, 4108012, doi:10.1109/TGRS.2023.3331970.
Abstract

Visible-near infrared (VIS-NIR) and thermal infrared (TIR) methods have long been used for ice cloud property retrievals based on satellite observations. Both retrieval methods are sensitive to the assumed ice particle models, which can significantly impact the accuracy of the retrieved microphysical and radiative properties of ice clouds. The two-habit model (THM) is considered a suitable ice particle model for passive remote sensing of global ice clouds, as confirmed by spectral consistency in cloud optical thickness (COT), which refers to the agreement between VIS-NIR and TIR COT retrievals. However, the ratio of COTs retrieved from these two methods using the THM varies with the scattering angle, indicating the potential influence of atmospheric and cloud properties on the spectral consistency of the inferred COT. The present study investigates potential factors affecting the angular dependence of the COT ratio based on observations made by the Advanced Baseline Imager (ABI) sensors on the 17th Geostationary Operational Environmental Satellite (GOES-17). For optically thin clouds (COT < 1) illuminated at a solar zenith angle (SZA) < 20◦ , the heterogeneous particle combination of mixed-phase clouds is the dominant factor that produces an angular-dependent negative bias in COT spectral consistency. At greater SZAs, cloud 3-D radiative effects are presumed to be a dominant factor. Negative biases in the cloud top temperature (CTT) and sea surface temperature contribute to negative biases in the COT ratio. This study suggests that the angular dependence of the COT ratio could help identify mixed-phase clouds and estimate their impact on the spectral consistency in retrieving ice cloud COT.

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