Articles | Volume 18, issue 22
https://doi.org/10.5194/gmd-18-8511-2025
https://doi.org/10.5194/gmd-18-8511-2025
Development and technical paper
 | 
14 Nov 2025
Development and technical paper |  | 14 Nov 2025

Automatic optical depth parametrization in radiative transfer model RTTOV v13 via LASSO-induced sparsity

Franklin Vargas Jiménez and Juan Carlos De los Reyes

Cited articles

Belloni, A. and Chernozhukov, V.: L1-penalized quantile regression in high-dimensional sparse models, The Annals of Statistics, 39, 82–130, https://doi.org/10.1214/10-AOS840, 2011. a
Bertsimas, D., King, A., and Mazumder, R.: Best Subset Selection via a Modern Optimization Lens, The Annals of Statistics, 44, 813–852, https://doi.org/10.1214/15-AOS1388, 2016. a
Cao, C., Xiong, X. J., Wolfe, R., DeLuccia, F., Liu, Q. M., Blonski, S., Lin, G. G., Nishihama, M., Pogorzala, D., Oudrari, H., and Hillger, D.: Visible Infrared Imaging Radiometer Suite (VIIRS) Sensor Data Record (SDR) User’s Guide (Version 1.3), Noaa technical report nesdis 142, NOAA, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, https://ncc.nesdis.noaa.gov/documents/documentation/viirs-users-guide-tech-report-142a-v1.3.pdf (last access: 1 July 2025), 2017. a, b, c
Cao, D., Ma, Y., Sun, L., and Gao, L.: Fast observation simulation method based on XGBoost for visible bands over the ocean surface under clear-sky conditions, Remote Sensing Letters, 12, 674–683, https://doi.org/10.1080/2150704X.2021.1925371, 2021. a
Cardall, A. C., Hales, R. C., Tanner, K. B., Williams, G. P., and Markert, K. N.: LASSO (L1) regularization for development of sparse remote-sensing models with applications in optically complex waters using GEE tools, Remote Sensing, 15, 1670, https://doi.org/10.3390/rs15061670, 2023. a
Download
Short summary
This study proposes an automatic method to parameterize atmospheric optical depths in the Radiative Transfer for TIROS Operational Vertical Sounder (RTTOV) version 13 model. The approach combines statistical inference and Least Absolute Shrinkage and Selection Operator (LASSO) regression to reduce parameters and select relevant gases. Tests with Visible Infrared Imaging Radiometer Suite (VIIRS) channels show reduced computation while preserving accuracy.
Share