Description: We derive the chlorophyll a concentration (Chla)for three main phytoplankton functional types (PFTs)-- diatoms, coccolithophores and cyanobacteria- by combining satellite multispectral-based information, being of a high spatial and temporal resolution, with retrievals based on high resolution of PFT absorption properties derived from hyperspectral measurements. The multispectral-based PFT Chla retrievals are based on a revised version of the empirical OC-PFT algorithm (Hirata et al. 2011) applied to the Ocean Colour Climate Change Initiative (OC-CCI) total Chla product. The PhytoDOAS analytical algorithm (Bracher et al. 2009, Sadeghi et al. 2012) is used with some modifications to derive PFT Chla from SCIAMACHY hyperspectral measurements. To combine synergistically these two PFT products (OC-PFT and PhytoDOAS), an optimal interpolation is performed for each PFT in every OC-PFT sub-pixel within a PhytoDOAS pixel, given its Chla and its a priori error statistics. The synergistic product (SynSenPFT) is presented for the period of August 2002 ? March 2012 and evaluated against in situ HPLC pigment data and satellite information on phytoplankton size classes (PSC) (Brewin et al. 2010, Brewin et al. 2015) and the size fraction (Sf) by Ciotti and Bricaud (2006. The most challenging aspects of the SynSenPFT algorithm implementation are discussed. Perspectives on SynSenPFT product improvements and prolongation of the time series over the next decades by adaptation to Sentinel multi- and hyperspectral instruments are highlighted.

Description: Fjords in the Arctic are key ecosystems and of great importance to both natural systems and human societies. The in situ monitoring of these systems is however quite difficult and some variables, such as light availability, are more difficult to collect than others. To address this knowledge gap the 'FjordLight' dataset was published on PANGAEA (Gentili et al., 2023). This dataset provides monthly values for bottom PAR (PAR_B) across seven key Arctic fjords, as well as annual averages and monthly climatology values for PAR_B, surface PAR (PAR(0-)), and the extinction coefficient of photosynthetically available radiation (K_PAR). Thanks to the rapid interest from the community for this dataset, we are now expanding upon it with an addendum: a collection of three additional files for each of the seven sites. Of particular importance to the study of photo-biological processes in the water column is K_PAR; however, the original FjordLight dataset did not include these monthly values because the size of these combined data would make the file large for many users' systems. In the present addendum, all monthly K_PAR data are included. These values are based on estimates of surface turbidity and irradiance derived from remotely sensed observations. Also included in this addendum are one file each for the standard deviation of the monthly climatologies and the annual climatologies for the three PAR variables (e.g. PAR(0-), K_PAR, PAR_B). Note that as these files are in addition to the original FjordLight dataset, they do not contain the same list of global variables and other metadata. All variables in the NetCDF files in this addendum are internally documented. The FjordLight R package that may be utilised to access and work with the FjordLight data has been updated and expanded for reading new files (Gentili et al., 2023; https://cran.r-project.org/web/packages/FjordLight/index.html).