12 citations as recorded by crossref.

1. An improved air mass factor calculation for nitrogen dioxide measurements from the Global Ozone Monitoring Experiment-2 (GOME-2) S. Liu et al. https://doi.org/10.5194/amt-13-755-2020
2. In-orbit Earth reflectance validation of TROPOMI on board the Sentinel-5 Precursor satellite L. Tilstra et al. https://doi.org/10.5194/amt-13-4479-2020
3. A directional surface reflectance climatology determined from TROPOMI observations L. Tilstra et al. https://doi.org/10.5194/amt-17-2235-2024
4. Directionally dependent Lambertian-equivalent reflectivity (DLER) of the Earth's surface measured by the GOME-2 satellite instruments L. Tilstra et al. https://doi.org/10.5194/amt-14-4219-2021
5. A Fast Retrieval of Cloud Parameters Using a Triplet of Wavelengths of Oxygen Dimer Band around 477 nm H. Choi et al. https://doi.org/10.3390/rs13010152
6. The CHROMA cloud-top pressure retrieval algorithm for the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission A. Sayer et al. https://doi.org/10.5194/amt-16-969-2023
7. Development of an Algorithm for the Simultaneous Retrieval of Cloud-Top Height and Cloud Optical Thickness Combining Radiative Transfer and Multisource Satellite Information From O₄ Hyperspectral Measurements W. Wang et al. https://doi.org/10.1109/TGRS.2024.3385030
8. Cloud parameter retrieval for EMI-series instruments from the O2–O2 band using a deep learning approach (ECRAD) T. Yang et al. https://doi.org/10.1016/j.atmosenv.2026.122272
9. MICRU: an effective cloud fraction algorithm designed for UV–vis satellite instruments with large viewing angles H. Sihler et al. https://doi.org/10.5194/amt-14-3989-2021
10. Retrieving cloud-base height and geometric thickness using the oxygen A-band channel of GCOM-C/SGLI T. Nagao et al. https://doi.org/10.5194/amt-18-773-2025
11. Cloud parameter retrieval for Environmental trace gases Monitoring Instrument (EMI) using the O2-O2 absorption band T. Yang et al. https://doi.org/10.1016/j.atmosres.2022.106597
12. A novel physics-based cloud retrieval algorithm based on neural networks (CRANN) from hyperspectral measurements in the O2-O2 band W. Wang et al. https://doi.org/10.1016/j.rse.2024.114267