Global retrieval of phytoplankton functional types based on empirical orthogonal functions using CMEMS GlobColour merged products and further extension to OLCI data

REMOTE SENSING OF ENVIRONMENT

卷:240

Article

Xi, Hongyan¹  Losa, Svetlana N.^1,2  Mangin, Antoine³  Soppa, Mariana A.¹  Garnesson, Philippe³  Demaria, Julien³  Liu, Yangyang^1,4  D'Andon, Odile Hembise Fanton³  Bracher, Astrid^1,5 

[1] Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, Bremerhaven, Germany

[2] Russian Acad Sci, Shirshov Inst Oceanol, Moscow, Russia

[3] ACRI ST, F-06904 Sophia Antipolis, France

[4] Univ Bremen, Fac Biol & Chem, Bremen, Germany

[5] Univ Bremen, Inst Environm Phys, Bremen, Germany

关键词: Retrieval algorithm;    Chlorophyll a;    Phytoplankton functional types;    Empirical orthogonal functions;    Remote sensing reflectance;    HPLC pigments;    CMEMS GlobColour;    OLCI;   

DOI  :  10.1016/j.rse.2020.111704

来源: Elsevier

【 摘 要 】

This study presents an algorithm for globally retrieving chlorophyll a (Chl-a) concentrations of phytoplankton functional types (PFTs) from multi-sensor merged ocean color (OC) products or Sentinel-3A (S3) Ocean and Land Color Instrument (OLCI) data from the GlobColour archive in the frame of the Copernicus Marine Environmental Monitoring Service (CMEMS). The retrieved PFTs include diatoms, haptophytes, dinoflagellates, green algae and prokaryotic phytoplankton. A previously proposed method to retrieve various phytoplankton pigments, based on empirical orthogonal functions (EOF), is investigated and adapted to retrieve Chl-a concentrations of multiple PFTs using extensive global data sets of in situ pigment measurements and matchups with satellite OC products. The performance of the EOF-based approach is assessed and cross-validated statistically. The retrieved PFTs are compared with those derived from diagnostic pigment analysis (DPA) based on in situ pigment measurements. Results show that the approach predicts well Chl-a concentrations of most of the mentioned PFTs. The performance of the approach is, however, less accurate for prokaryotes, possibly due to their general low variability and small concentration range resulting in a weak signal which is extracted from the reflectance data and corresponding EOF modes. As a demonstration of the approach utilization, the EOF-based fitted models based on satellite reflectance products at nine bands are applied to the monthly GlobColour merged products. Climatological characteristics of the PFTs are also evaluated based on ten years of merged products (2002-2012) through inter-comparisons with other existing satellite derived products on phytoplankton composition including phytoplankton size class (PSC), SynSenPFT, OC-PFT and PHYSAT. Inter-comparisons indicate that most PFTs retrieved by our study agree well with previous corresponding PFT/PSC products, except that prokaryotes show higher Chl-a concentration in low latitudes. PFT dominance derived from our products is in general well consistent with the PHYSAT product. A preliminary experiment of the retrieval algorithm using eleven OLCI bands is applied to monthly OLCI products, showing comparable PFT distributions with those from the merged products, though the matchup data for OLCI are limited both in number and coverage. This study is to ultimately deliver satellite global PFT products for long-term continuous observation, which will be updated timely with upcoming OC data, for a comprehensive understanding of the variability of phytoplankton composition structure at a global or regional scale.

【 授权许可】

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