{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:42:54Z","timestamp":1767339774956,"version":"build-2065373602"},"reference-count":24,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2020,8,6]],"date-time":"2020-08-06T00:00:00Z","timestamp":1596672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000124211\/18\/I-EF"],"award-info":[{"award-number":["4000124211\/18\/I-EF"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Sentinel-3 tandem project represents the first time that two ocean colour satellites have been flown in the same orbit with minimal temporal separation (~30 s), thus allowing them to have virtually identical views of the ocean. This offers an opportunity for understanding how differences in individual sensor uncertainty can affect conclusions drawn from the data. Here, we specifically focus on trend estimation. Observational chlorophyll-a uncertainty is assessed from the Sentinel-3A Ocean and Land Colour Imager (OLCI-A) and Sentinel-3B OLCI (OLCI-B) sensors using a bootstrapping approach. Realistic trends are then imposed on a synthetic chlorophyll-a time series to understand how sensor uncertainty could affect potential long-term trends in Sentinel-3 OLCI data. We find that OLCI-A and OLCI-B both show very similar trends, with the OLCI-B trend estimates tending to have a slightly wider distribution, although not statistically different from the OLCI-A distribution. The spatial pattern of trend estimates is also assessed, showing that the probability distributions of trend estimates in OLCI-A and OLCI-B are most similar in open ocean regions, and least similar in coastal regions and at high northern latitudes. This analysis shows that the two sensors should provide consistent trends between the two satellites, provided future ageing is well quantified and mitigated. The Sentinel-3 programme offers a strong baseline for estimating long-term chlorophyll-a trends by offering a series of satellites (starting with Sentinel-3A and Sentinel-3B) that use the same sensor design, reducing potential issues with cross-calibration between sensors. This analysis contributes an important understanding of the reliability of the two current Sentinel-3 OLCI sensors for future studies of climate change driven chlorophyll-a trends.<\/jats:p>","DOI":"10.3390\/rs12162522","type":"journal-article","created":{"date-parts":[[2020,8,6]],"date-time":"2020-08-06T09:41:21Z","timestamp":1596706881000},"page":"2522","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Assessing the Effect of Tandem Phase Sentinel-3 OLCI Sensor Uncertainty on the Estimation of Potential Ocean Chlorophyll-a Trends"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8918-2351","authenticated-orcid":false,"given":"Matthew L.","family":"Hammond","sequence":"first","affiliation":[{"name":"National Oceanography Centre, European Way, Southampton SO14 3ZH, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3875-6802","authenticated-orcid":false,"given":"Stephanie A.","family":"Henson","sequence":"additional","affiliation":[{"name":"National Oceanography Centre, European Way, Southampton SO14 3ZH, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicolas","family":"Lamquin","sequence":"additional","affiliation":[{"name":"ACRI-ST, 260 Route du Pin Montard, Sophia Antipolis, 06410 Biot, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7393-5910","authenticated-orcid":false,"given":"S\u00e9bastien","family":"Clerc","sequence":"additional","affiliation":[{"name":"ACRI-ST, 260 Route du Pin Montard, Sophia Antipolis, 06410 Biot, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Craig","family":"Donlon","sequence":"additional","affiliation":[{"name":"European Space Agency, ESTEC\/EOP-SME, Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.rse.2011.07.024","article-title":"The Global Monitoring for Environment and Security (GMES) Sentinel-3 mission","volume":"120","author":"Donlon","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_2","unstructured":"GCOS (2011). Systematic observation requirements for satellite-based data products for climate. 2011 Update. Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC, World Meteorological Organization. GCOS-154."},{"key":"ref_3","unstructured":"Clerc, S., Donlon, C., Borde, F., Lamquin, N., Hunt, S., Smith, D., McMillan, M., Mittaz, J., Wooliams, E., and Hammond, M. Benefits and lessons learned from the Sentinel-3 Tandem phase. Remote Sens., in preparation."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1146\/annurev.marine.010908.163650","article-title":"A Decade of Satellite Ocean Color Observations","volume":"1","author":"McClain","year":"2009","journal-title":"Ann. Rev. Mar. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1002\/2016GB005600","article-title":"Assessing trends and uncertainties in satellite-era ocean chlorophyll using space-time modeling","volume":"31","author":"Hammond","year":"2017","journal-title":"Global Biogeochem. Cycles"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1111\/gcb.13152","article-title":"Observing climate change trends in ocean biogeochemistry: When and where","volume":"22","author":"Henson","year":"2016","journal-title":"Glob. Chang. Biol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2711","DOI":"10.5194\/bg-10-2711-2013","article-title":"Factors challenging our ability to detect long-term trends in ocean chlorophyll","volume":"10","author":"Beaulieu","year":"2013","journal-title":"Biogeosciences"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"251","DOI":"10.3354\/meps11411","article-title":"Patterns and ecological implications of historical marine phytoplankton change","volume":"534","author":"Boyce","year":"2015","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"621","DOI":"10.5194\/bg-7-621-2010","article-title":"Detection of anthropogenic climate change in satellite records of ocean chlorophyll and productivity","volume":"7","author":"Henson","year":"2010","journal-title":"Biogeosciences"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"819","DOI":"10.5194\/os-15-819-2019","article-title":"The CMEMS GlobColour chlorophyll a product based on satellite observation: Multi-sensor merging and flagging strategies","volume":"15","author":"Garnesson","year":"2019","journal-title":"Ocean Sci."},{"key":"ref_11","first-page":"29","article-title":"The Ocean Colour Climate Change Initiative: Merging ocean colour observations seamlessly","volume":"21","author":"Lavender","year":"2015","journal-title":"Ocean Chall."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/j.rse.2004.08.014","article-title":"Consistent merging of satellite ocean color data sets using a bio-optical model","volume":"94","author":"Maritorena","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Djavidnia, S. (2010). Comparison of global ocean colour data records. Ocean Sci., 61\u201376.","DOI":"10.5194\/os-6-61-2010"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Lamquin, N., Clerc, S., Bourg, L., and Donlon, C. (2020). OLCI A\/B tandem phase analysis, part 1: Level 1 homogenisation and harmonisation. Remote Sens., 12.","DOI":"10.3390\/rs12111804"},{"key":"ref_15","unstructured":"Lamquin, N., D\u00e9ru, A., Clerc, S., Bourg, L., and Donlon, C. OLCI A\/B tandem phase analysis, part 2: Benefits of sensors harmonisation for Level 2 products. Remote Sens., in preparation."},{"key":"ref_16","unstructured":"Antoine, D., and Fanton d\u2019Andon, O. (2010). Sentinel-3 optical products and algorithm definition. OLCI Level 2 Algorithm Theoretical Basis Document: Ocean Color Products in Case 1 Waters, European Space Agency."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1875","DOI":"10.1080\/014311699212533","article-title":"A multiple scattering algorithm for atmospheric correction of remotely-sensed ocean colour (MERIS instrument): Principle and implementation for atmospheres carrying various aerosols including absorbing ones","volume":"20","author":"Antoine","year":"1999","journal-title":"Int. J. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5921","DOI":"10.1002\/2014JC010158","article-title":"Decadal trends in global pelagic ocean chlorophyll: A new assessment integrating multiple satellites, in situ data, and models","volume":"119","author":"Gregg","year":"2014","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1080\/2150704X.2017.1354263","article-title":"Global trends in ocean phytoplankton: A new assessment using revised ocean colour data","volume":"8","author":"Gregg","year":"2017","journal-title":"Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/j.dsr.2011.02.003","article-title":"Inter-annual variations in the SeaWiFS global chlorophyll a concentration (1997\u20132007)","volume":"58","author":"Vantrepotte","year":"2011","journal-title":"Deep. Res. Part I Oceanogr. Res. Pap."},{"key":"ref_21","unstructured":"Levene, H. (1960). Robust Tests for Equality of Variances. Contributions to Probability and Statistics: Essays in Honor of Harold Hotelling, Stanford University Press."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4087","DOI":"10.5194\/bg-10-4087-2013","article-title":"Increasing cloudiness in Arctic damps the increase in phytoplankton primary production due to sea ice receding","volume":"10","author":"Babin","year":"2013","journal-title":"Biogeosciences"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2233","DOI":"10.1080\/01431161.2016.1168949","article-title":"Impact of inter-mission differences and drifts on chlorophyll-a trend estimates","volume":"37","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","unstructured":"Lamquin, N., Clerc, S., Bourg, L., and Donlon, C. OLCI A\/B tandem phase analysis, part 3: Post-tandem monitoring of cross-calibration from statistics of Deep Convective Clouds observations. Remote Sens., in preparation."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/16\/2522\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:56:58Z","timestamp":1760176618000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/16\/2522"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,6]]},"references-count":24,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2020,8]]}},"alternative-id":["rs12162522"],"URL":"https:\/\/doi.org\/10.3390\/rs12162522","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2020,8,6]]}}}