{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T14:57:03Z","timestamp":1784300223293,"version":"3.55.0"},"reference-count":47,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T00:00:00Z","timestamp":1642723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"EMPIR","award":["16ENV03 and 19ENV07"],"award-info":[{"award-number":["16ENV03 and 19ENV07"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Atmospheric corrections introduce uncertainties in bottom-of-atmosphere Ocean Colour (OC) products. In this paper, we analyse the uncertainty budget of the SeaDAS atmospheric correction algorithm. A metrological approach is followed, where each of the error sources are identified in an uncertainty tree diagram and briefly discussed. Atmospheric correction algorithms depend on ancillary variables (such as meteorological properties and column densities of gases), yet the uncertainties in these variables were not studied previously in detail. To analyse these uncertainties for the first time, the spread in the ERA5 ensemble is used as an estimate for the uncertainty in the ancillary data, which is then propagated to uncertainties in remote sensing reflectances using a Monte Carlo approach and the SeaDAS atmospheric correction algorithm. In an example data set, wind speed and relative humidity are found to be the main contributors (among the ancillary parameters) to the remote sensing reflectance uncertainties.<\/jats:p>","DOI":"10.3390\/rs14030497","type":"journal-article","created":{"date-parts":[[2022,1,23]],"date-time":"2022-01-23T20:34:40Z","timestamp":1642970080000},"page":"497","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Ancillary Data Uncertainties within the SeaDAS Uncertainty Budget for Ocean Colour Retrievals"],"prefix":"10.3390","volume":"14","author":[{"given":"Pieter","family":"De Vis","sequence":"first","affiliation":[{"name":"National Physical Laboratory, Hampton Road, Teddington TW11 0LW, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fr\u00e9d\u00e9ric","family":"M\u00e9lin","sequence":"additional","affiliation":[{"name":"European Commission, Joint Research Centre (JRC), TP270, Via Fermi 2749, 21027 Ispra, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4176-9038","authenticated-orcid":false,"given":"Samuel E.","family":"Hunt","sequence":"additional","affiliation":[{"name":"National Physical Laboratory, Hampton Road, Teddington TW11 0LW, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rosalinda","family":"Morrone","sequence":"additional","affiliation":[{"name":"National Physical Laboratory, Hampton Road, Teddington TW11 0LW, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9184-9020","authenticated-orcid":false,"given":"Morven","family":"Sinclair","sequence":"additional","affiliation":[{"name":"National Physical Laboratory, Hampton Road, Teddington TW11 0LW, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bill","family":"Bell","sequence":"additional","affiliation":[{"name":"European Centre for Medium-Range Weather Forecasts, Reading RG2 9AX, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,21]]},"reference":[{"key":"ref_1","unstructured":"GCOS (2016). 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