An overview of the AIRS radiative transfer model

By Larrabee L. Strow, Scott E. Hannon, S. D. Souza-Machado, H. Motteler, D. Tobin. IEEE Transactions on Geoscience and Remote Sensing, 2003

336 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/9821d28bd83106cfb83e5912c9d7c90f21d08bca

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Citations in the corpus

Aqua: an Earth-Observing Satellite mission to examine water and other climate variables (2003, methodology): “Details of the AIRS radiative transfer model can be found in [19], and details on the creation and validation of AIRS simulated data, used in the development of the retrieval algorithms, can be found in [20].”
Vertical Moist Thermodynamic Structure and Spatial-Temporal Evolution of the MJO in AIRS Observations (2006, background): “3), while the preconditioning water vapor anomaly can reach up to the middle troposphere (around 500 hPa; Fig.”
Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds (2003, methodology): “These pressure levels are a subset of the 100 levels used by Strow et al. [ 22 ] in the AIRS radiative transfer calculation.”
Advances in Radiative Transfer Modeling in Support of Satellite Data Assimilation (2007, positive): “It is shown that for specific instruments like the Atmospheric Infrared Spectrometer (AIRS), a Stand Alone Radiative Transfer model (SARTA) developed by University Maryland at Baltimore County (UMBC; Strow et al. 2003) performs the best.”
On the determination of atmospheric minor gases by the method of vanishing partial derivatives with application to CO2 (2005, methodology): “The Radiative Transfer Algorithm (RTA) currently used in the AIRS Retrieval assumes a constant CO2 mixing ratio of 370 ppmv throughout the atmosphere [Strow et al., 2003].”
AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems (2003, methodology): “The radiative transfer algorithm development for the IR channels and its validation is described in [34]; the microwave”
Performance of the line-by-line radiative transfer model (LBLRTM) for temperature and species retrievals: IASI case studies from JAIVEx (2009, methodology): “…for P-, Q-and Rbranch line coupling has been available in LBLRTM for a number of years and the importance of line coupling in the P-and R-branches had been explored by Strow et al. (2003), P-and R-branch line coupling coefficients were not available for LBLRTM before the Niro et al. (2005) work.”