FN Archimer Export Format PT J TI Which ocean colour algorithm for MERIS in North West European waters? BT AF TILSTONE, Gavin MALLOR-HOYA, Silvana GOHIN, Francis COUTO, Andre Belo SA, Carolina GOELA, Priscila CRISTINA, Sonia AIRS, Ruth ICELY, John ZUEHLKE, Marco GROOM, Steve AS 1:1;2:1;3:2;4:3;5:3;6:4,5;7:4,5;8:1;9:4,5;10:6;11:1; FF 1:;2:;3:PDG-ODE-DYNECO-PELAGOS;4:;5:;6:;7:;8:;9:;10:;11:; C1 PML, Prospect Pl, Plymouth PL1 3DH, Devon, England. IFREMER, Lab Ecol Pelag, DYNECO PELAGOS, BP 70, F-29280 Plouzane, France. Univ Lisbon, Fac Ciencias, MARE Marine & Environm Sci Ctr, P-1749016 Lisbon, Portugal. Univ Algarve, FCT, CIMA, Campus Gambelas, P-8005139 Faro, Portugal. SAGREMARISCO Lda, Apartado 21, P-8650999 Vila Do Bispo, Portugal. Brockmann Consult, Max Planck Str 2, D-21502 Geesthacht, Germany. C2 PML, UK IFREMER, FRANCE UNIV LISBON, PORTUGAL UNIV ALGARVE, PORTUGAL SAGREMARISCO LDA, PORTUGAL BROCKMANN CONSULT, GERMANY SI BREST SE PDG-ODE-DYNECO-PELAGOS IN WOS Ifremer jusqu'en 2018 copubli-europe IF 6.457 TC 30 UR https://archimer.ifremer.fr/doc/00359/46995/46924.pdf https://archimer.ifremer.fr/doc/00359/46995/48634.pdf LA English DT Article CR BOUSSOLE DE ;Case 2 waters;Coastal waters;Shelf waters;Chlorophyll-a;North Sea;Ocean colour;Remote sensing;MERIS;English Channel;Mediterranean coast;Portuguese coast AB Chlorophyll-a (Chl a) is a key parameter for the assessment of water quality in coastal and shelf environments. The availability of satellite ocean colour offers the potential of monitoring these regions at unprecedented spatial and temporal scales, as long as a high level of accuracy can be achieved. To use satellite derived Chl a to monitor these environments, it is imperative that rigorous accuracy assessments are undertaken to select the most accurate ocean colour algorithm(s). To this end, the accuracy of a range of ocean colour Chl a algorithms for use with Medium Imaging Resolution Spectrometer (MERIS) Level 2 (L2) Remote Sensing Reflectance (Rrs), using two different atmospheric correction (AC) processors (COASTCOLOUR and MERIS Ground Segment processor version 8.0 – MEGS8.0), were assessed in North West European waters. A total of 594 measurements of Rrs(λ) and/or Chl a were made in the North Sea, Mediterranean Sea, along the Portuguese Coast, English Channel and Celtic Sea between June 2001 and March 2012, where Chl a varied from 0.2 to 35 mg m− 3. The following algorithms were compared: MERIS Case 1 water Chl a algorithm OC4Me, the MERIS Case 2 algorithm Algal Pigment 2 (AP2), the MODIS-Aqua Case 1 Chl a algorithm OC3 adapted for MERIS (OC3Me), the MODIS-Aqua Garver-Siegel-Maritorena algorithm (GSM) adapted for MERIS and the Gohin et al. (2002) algorithm for MERIS (OC5Me). For both COASTCOLOUR and MEGS8.0 processors, OC5Me was the most accurate Chl a algorithm, which was within ~ 25% of in situ values in these coastal and shelf waters. The uncertainty in MEGS8.0 Rrs(442) (~ 17%) was slightly higher compared to COASTCOLOUR (~ 12%) from 0.3 to 7 mg m− 3 Chl a, but for Rrs(560) the uncertainty was lower for MEGS8.0 (~ 10%) compared to COASTCOLOUR (~ 13%), which meant that MEGS8.0 Chl a was more accurate than COASTCOLOUR for all of the Chl a algorithms tested. Compared to OC5Me, OC4Me tended to over-estimate Chl a, which was caused by non-algal SPM especially at values > 14 g m− 3. GSM also over-estimated Chl a, which was caused by variations in absorption coefficient of coloured dissolved organic matter at 442 nm (aCDOM(442)). AP2 consistently under-estimated Chl a, especially when non-algal SPM was > 4 g m− 3. PY 2017 PD FEB SO Remote Sensing Of Environment SN 0034-4257 PU Elsevier Science Inc VL 189 UT 000393005400011 BP 132 EP 151 DI 10.1016/j.rse.2016.11.012 ID 46995 ER EF