Articles | Volume 13, issue 1
https://doi.org/10.5194/amt-13-323-2020
https://doi.org/10.5194/amt-13-323-2020
Research article
 | 
30 Jan 2020
Research article |  | 30 Jan 2020

kCARTA: a fast pseudo line-by-line radiative transfer algorithm with analytic Jacobians, fluxes, nonlocal thermodynamic equilibrium, and scattering for the infrared

Sergio DeSouza-Machado, L. Larrabee Strow, Howard Motteler, and Scott Hannon

Related authors

COSP-RTTOV-1.0: Flexible radiation diagnostics to enable new science applications in model evaluation, climate change detection, and satellite mission design
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
EGUsphere, https://doi.org/10.5194/egusphere-2025-169,https://doi.org/10.5194/egusphere-2025-169, 2025
Short summary
Horizontal small-scale variability of water vapor in the atmosphere: implications for intercomparison of data from different measuring systems
Xavier Calbet, Cintia Carbajal Henken, Sergio DeSouza-Machado, Bomin Sun, and Tony Reale
Atmos. Meas. Tech., 15, 7105–7118, https://doi.org/10.5194/amt-15-7105-2022,https://doi.org/10.5194/amt-15-7105-2022, 2022
Short summary
Establishment of AIRS climate-level radiometric stability using radiance anomaly retrievals of minor gases and sea surface temperature
L. Larrabee Strow and Sergio DeSouza-Machado
Atmos. Meas. Tech., 13, 4619–4644, https://doi.org/10.5194/amt-13-4619-2020,https://doi.org/10.5194/amt-13-4619-2020, 2020
Short summary
Can turbulence within the field of view cause significant biases in radiative transfer modeling at the 183 GHz band?
Xavier Calbet, Niobe Peinado-Galan, Sergio DeSouza-Machado, Emil Robert Kursinski, Pedro Oria, Dale Ward, Angel Otarola, Pilar Rípodas, and Rigel Kivi
Atmos. Meas. Tech., 11, 6409–6417, https://doi.org/10.5194/amt-11-6409-2018,https://doi.org/10.5194/amt-11-6409-2018, 2018
Short summary
Single-footprint retrievals for AIRS using a fast TwoSlab cloud-representation model and the SARTA all-sky infrared radiative transfer algorithm
Sergio DeSouza-Machado, L. Larrabee Strow, Andrew Tangborn, Xianglei Huang, Xiuhong Chen, Xu Liu, Wan Wu, and Qiguang Yang
Atmos. Meas. Tech., 11, 529–550, https://doi.org/10.5194/amt-11-529-2018,https://doi.org/10.5194/amt-11-529-2018, 2018
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Combining commercial microwave links and weather radar for classification of dry snow and rainfall
Erlend Øydvin, Renaud Gaban, Jafet Andersson, Remco (C. Z.) van de Beek, Mareile Astrid Wolff, Nils-Otto Kitterød, Christian Chwala, and Vegard Nilsen
Atmos. Meas. Tech., 18, 2279–2293, https://doi.org/10.5194/amt-18-2279-2025,https://doi.org/10.5194/amt-18-2279-2025, 2025
Short summary
Improved consistency in solar-induced fluorescence retrievals from GOME-2A with the SIFTER v3 algorithm
Juliëtte C. S. Anema, K. Folkert Boersma, Lieuwe G. Tilstra, Olaf N. E. Tuinder, and Willem W. Verstraeten
Atmos. Meas. Tech., 18, 1961–1979, https://doi.org/10.5194/amt-18-1961-2025,https://doi.org/10.5194/amt-18-1961-2025, 2025
Short summary
An information content approach to diagnosing and improving CLIMCAPS retrieval consistency across instruments and satellites
Nadia Smith and Christopher D. Barnet
Atmos. Meas. Tech., 18, 1823–1839, https://doi.org/10.5194/amt-18-1823-2025,https://doi.org/10.5194/amt-18-1823-2025, 2025
Short summary
Characterizing urban planetary boundary layer dynamics using 3-year Doppler wind lidar measurements in a western Yangtze River Delta city, China
Tianwen Wei, Mengya Wang, Kenan Wu, Jinlong Yuan, Haiyun Xia, and Simone Lolli
Atmos. Meas. Tech., 18, 1841–1857, https://doi.org/10.5194/amt-18-1841-2025,https://doi.org/10.5194/amt-18-1841-2025, 2025
Short summary
Radar-based high-resolution ensemble precipitation analyses over the French Alps
Matthieu Vernay, Matthieu Lafaysse, and Clotilde Augros
Atmos. Meas. Tech., 18, 1731–1755, https://doi.org/10.5194/amt-18-1731-2025,https://doi.org/10.5194/amt-18-1731-2025, 2025
Short summary

Cited articles

Aumann, H., Chahine, M., Gautier, C., Goldberg, M., Kalnay, E., McMillin, L., Revercomb, H., Rosenkranz, P., Smith, W., Staelin, D., Strow, L., and Susskind, J.: AIRS/AMSU/HSB on the Aqua Mission: Design, Science Objectives, Data Products and Processing Systems, IEEE T. Geosci. Remote, 41, 253–264, 2003. a
Buehler, S., Eriksson, P., and Lemke, O.: Absorption lookup tables in the radiative transfer model ARTS, J. Quant. Spectrosc. Ra., 112, 1559–1567, https://doi.org/10.1016/j.jqsrt.2011.03.008, 2011. a
Chou, M.-D., Lee, K.-T., Tsay, S.-C., and Fu, Q.: Parameterization for Cloud Longwave Scattering for use in Atmospheric Models, J. Climate, 12, 159–169, 1999. a, b, c, d
Clerbaux, C., Boynard, A., Clarisse, L., George, M., Hadji-Lazaro, J., Herbin, H., Hurtmans, D., Pommier, M., Razavi, A., Turquety, S., Wespes, C., and Coheur, P.-F.: Monitoring of atmospheric composition using the thermal infrared IASI/MetOp sounder, Atmos. Chem. Phys., 9, 6041–6054, https://doi.org/10.5194/acp-9-6041-2009, 2009. a
Clough, S. and Iacono, M. J.: Line by line calculation of atmospheric fluxes and cooling rates, 2. Application to Carbon-Dioxide,Ozone, Methane, Nitrous-Oxide and the Halocarbons, J. Geophys. Res.-Atmos., 100, 16519–16535, 1995. a
Download

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Short summary
The current instruments being used for weather forecasting and climate require accurate radiative transfer codes to process the acquired data. In addition the codes are becoming more realistic, as they can now account for the effects of cloud and aerosols, rather than only simulating radiances for a clear sky. We describe a fast, accurate, and general purpose code that we have developed to help model data from these instruments.
Share