Evaluation of cloud height, optical thickness, and phase retrievals from the CHROMA algorithm applied to Sentinel-3 OLCI data

dc.contributor.authorSayer, Andrew
dc.contributor.authorCairns, Brian
dc.contributor.authorKnobelspiesse, Kirk D.
dc.contributor.authorLelli, Luca
dc.contributor.authorRajapakshe, Chamara
dc.contributor.authorGiangrande, Scott E.
dc.contributor.authorThomas, Gareth E.
dc.contributor.authorZhang, Damao
dc.date.accessioned2025-07-09T17:54:55Z
dc.date.issued2025-6-18
dc.description.abstractWe previously developed the Cloud Height Retrieval from O2 Molecular Absorption (CHROMA) algorithm for the Ocean Color Instrument (OCI) on the new NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Here, we apply CHROMA to observations from the Ocean Land Colour Instrument (OLCI) to guide expectations for PACE, as it will take some time to obtain large-scale validation data for OCI. We use cloud top height (CTH), phase, and (for liquid clouds) cloud 5 optical thickness (COT) data from the ground-based Atmospheric Radiation Measurement (ARM) network to evaluate the OLCI retrievals. We found that OLCI and Moderate Resolution Imaging Spectroradiometer (MODIS) CTH compare similarly well to the ARM reference. OLCI has a tendency to underestimate CTH as CTH increases, and algorithm assumptions about cloud geometric thickness may contribute to this. ARM COT from multifilter shadowband radiometers (MFRSR) and Sun photometers are well-correlated with one another, albeit with a roughly 30 % offset on average; OLCI and MODIS COT agree 10 more closely with the MFRSR data. OLCI retrieval uncertainty estimates show skill at telling low-uncertainty cases from highuncertainty ones, although CTH uncertainties are underestimated. Additionally, we compare the OLCI data to satellite retrievals based on thermal infrared measurements from MODIS and and Sea and Land Surface Temperature Radiometer (SLSTR) data. Differences are broadly consistent with physical expectations based on the A-band vs. thermal techniques, although one key challenge in such aggregated comparisons is different cloud masking sensitivities and algorithm failure rates meaning 15 additional sampling differences are introduced. We conclude by discussing the transition to and possible enhancements for PACE OCI.
dc.description.sponsorshipNASA-affiliated authors were funded by the NASA PACE project. LL was funded by the Alexander von Humboldt foundation via the Feodor-Lynen fellowship 2020. This work (SEG and DZ) was also supported by the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program and Atmospheric System Research (ASR) program. This paper has been authored by an employee of Brookhaven Science Associates, LLC, under contract no. DE-SC0012704 with the US DOE. René Preusker (Freie Universität Berlin) and Julien Chimot (EUMETSAT) are thanked for the OLCI smile distortion model, as well as numerous discussions on OLCI data. Christine Chiu’s (Colorado State University) insights into the Sun photometer and MFRSR COT data were greatly appreciated. NASA’s Global Modeling and Assimilation Office (GMAO) are thanked for the MERRA2 meteorological data used as ancillary input for the CHROMA algorithm. We acknowledge the free use of the TROPOMI surface DLER database provided through the Sentinel-5p+ Innovation project of the European Space Agency (ESA). The TROPOMI surface DLER database was created by the Royal Netherlands Meteorological Institute (KNMI); Gijsbert Tilstra (KNMI) is thanked for assistance in better understanding this data base. Ground data were obtained from the ARM user facility, a U.S. DOE Office of Science user facility managed by the Biological and Environmental Research Program. Site staff, algorithm developers/VAP translators, and the ARM program are thanked for the creation and stewardship of these data records - in particular, in addition to those on the author list of this manuscript, Karen Johnson and Dié Wang (Brookhaven National Laboratory).
dc.description.urihttps://egusphere.copernicus.org/preprints/2025/egusphere-2025-2005/
dc.format.extent32 pages
dc.genrejournal articles
dc.genrepreprints
dc.identifierdoi:10.13016/m2dvcv-29qk
dc.identifier.urihttps://doi.org/10.5194/egusphere-2025-2005
dc.identifier.urihttp://hdl.handle.net/11603/39237
dc.language.isoen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC GESTAR II
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
dc.rightsPublic Domain
dc.rights.urihttps://creativecommons.org/publicdomain/mark/1.0/
dc.titleEvaluation of cloud height, optical thickness, and phase retrievals from the CHROMA algorithm applied to Sentinel-3 OLCI data
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0001-9149-1789

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