Description: Satellite remote sensing of chlorophyll a concentration (Chl-a) in the Arctic Ocean is spatially and temporally limited and needs to be supplemented and validated with substantial volumes of in situ observations. Here, we evaluated the capability of obtaining highly resolved in situ surface Chl-a using underway spectrophotometry operated during two summer cruises in 2015 and 2016 in the Fram Strait. Results showed that Chl-a measured using high pressure liquid chromatography (HPLC) was well related (R2 = 0.90) to the collocated particulate absorption line height at 676 nm obtained from the underway spectrophotometry system. This enabled continuous surface Chl-a estimation along the cruise tracks. When used to validate Chl-a operational products as well as to assess the Chl-a algorithms of the aqua moderate resolution imaging spectroradiometer (MODIS-A) and Sentinel-3 Ocean Land Color Imager (OLCI) Level 2 Chl-a operational products, and from OLCI Level 2 products processed with Polymer atmospheric correction algorithm (version 4.1), the underway spectrophotometry based Chl-a data sets proved to be a much more sufficient data source by generating over one order of magnitude more match-ups than those obtained from discrete water samples. Overall, the band ratio (OCI, OC4) Chl-a operational products from MODIS-A and OLCI as well as OLCI C2RCC products showed acceptable results. The OLCI Polymer standard output provided the most reliable Chl-a estimates, and nearly as good results were obtained from the OCI algorithm with Polymer atmospheric correction method. This work confirms the great advantage of the underway spectrophotometry in enlarging in situ Chl-a data sets for the Fram Strait and improving satellite Chl-a validation and Chl-a algorithm assessment over discrete water sample analysis in the laboratory.

Description: Gaussian decomposition and Singular Value Decomposition combined with Non-Negative Least Squares (SVD-NNLS) method are compared and combined to estimate the concentration of 18 phytoplankton pigments (names and abbreviations are displayed in Table 2) from phytoplankton absorption spectra. Results show that both methods tend to overestimate pigment concentration. Gaussian decomposition method provides robust estimation of TChl-a, TChl-b, Chl-c1/2, PSC and PPC. The estimates of TChl-a, Fuco, Diato, $\beta$-Caro, Prasino, TChl-b, Zea, Viola and Lut from SVD-NNLS show reasonable estimation accuracy, while the other pigments are subjected to relatively large prediction errors. The estimated pigments concentrations are further exploited based on Diagnostic Pigment Analysis to derive four phytoplankton functional types, i.e. diatoms, prymnesiophytes, green algae and prokaryotes. By the application of these two methods to the particulate absorption spectra collected by underway spectrophotometry during three summer cruises in 2015 - 2017 in the Fram Strait, continuous surface phytoplankton functional types are estimated along the cruise course.