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Evaluation of Modeled Hyperspectral Infrared Spectra Against All‐Sky AIRS Observations Using Different Cloud Overlap Schemes

Le, Tianhao and Natraj, Vijay and Braverman, Amy J. and Yung, Yuk L. (2022) Evaluation of Modeled Hyperspectral Infrared Spectra Against All‐Sky AIRS Observations Using Different Cloud Overlap Schemes. Earth and Space Science, 9 (7). Art. No. e2022EA002245. ISSN 2333-5084. doi:10.1029/2022ea002245.

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Hyperspectral infrared sounding contains information about clouds, which plays an important role in modulating Earth's climate. However, there is a great deal of uncertainty in modeling the radiative effect of clouds due to its complex dependence on various parameters. Therefore, cloudy scenarios are often neglected in retrievals of infrared spectral measurements and in data assimilation. One-dimensional radiative transfer (RT) models have a limited capability to represent the cloud three-dimensional multilayer structure. This issue is typically resolved by using a multiple independent column approach, which is computationally demanding. Therefore, it is necessary to find a balance between computational speed and accuracy for infrared RT all-sky radiance simulations. In this study, we utilize the Community Radiative Transfer Model with four different cloud overlap schemes and compare against observations made by the Atmospheric Infrared Sounder (AIRS) using a statistical metric called the first Wasserstein distance. Our results show that the average cloud overlap scheme performs the best and successfully predicts the overall probability distribution of brightness temperature over nonfrozen oceans for a wide range of wavelengths. The mean absolute differences are less than 0.7 K for 846 selected AIRS channels between 790 cm⁻¹ and 1231 cm⁻¹.

Item Type:Article
Related URLs:
URLURL TypeDescription ItemAIRS observations and ECMWF vertical profiles ItemRT code used in this manuscript (CRTM version 2.4.0)
Le, Tianhao0000-0002-6600-8270
Natraj, Vijay0000-0003-3154-9429
Braverman, Amy J.0000-0001-5127-9230
Yung, Yuk L.0000-0002-4263-2562
Additional Information:© 2022. The Authors. Earth and Space Science published by Wiley Periodicals LLC on behalf of American Geophysical Union. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Issue Online: 01 July 2022. Version of Record online: 01 July 2022. Accepted manuscript online: 26 June 2022. Manuscript accepted: 17 June 2022. Manuscript revised: 08 June 2022. Manuscript received: 25 January 2022. The authors would like to thank members of Prof. Yung's research group for useful comments. We also acknowledge Dr. Hartmut Aumann and Dr. Alan Geer for providing the AIRS observations and ECMWF profiles used in this study and Dr. Benjamin Johnson for helpful discussions on CRTM. A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). Data Availability Statement. The AIRS observations and ECMWF vertical profiles used in this study can be downloaded from Figures were made with Matplotlib version 3.0.2 (Caswell et al., 2018; Hunter, 2007), available under the Matplotlib license at The first Wasserstein distances were calculated using Scipy v1.0 (Virtanen et al., 2020), available at The RT code used in this manuscript (CRTM version 2.4.0) is licensed under CC0 and published on Github:
Funding AgencyGrant Number
Subject Keywords:radiative transfer; cloud overlap; model-AIRS intercomparison; first Wasserstein distance
Issue or Number:7
Record Number:CaltechAUTHORS:20220722-768945000
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Official Citation:Le, T., Natraj, V., Braverman, A. J., & Yung, Y. L. (2022). Evaluation of modeled hyperspectral infrared spectra against all-sky AIRS observations using different cloud overlap schemes. Earth and Space Science, 9, e2022EA002245.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:115780
Deposited By: George Porter
Deposited On:26 Jul 2022 19:40
Last Modified:26 Jul 2022 19:40

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