Bracher, Astrid; Dinter, Tilman; Wolanin, Aleksandra; Rozanov, Vladimir V; Losa, Svetlana; Soppa, Mariana A (2017): Global monthly mean chlorophyll a surface concentrations from August 2002 to April 2012 for diatoms, coccolithophores and cyanobacteria from PhytoDOAS algorithm version 3.3 applied to SCIAMACHY data, link to NetCDF files in ZIP archive. PANGAEA, https://doi.org/10.1594/PANGAEA.870486, In supplement to: Losa, Svetlana; Soppa, Mariana A; Dinter, Tilman; Wolanin, Aleksandra; Brewin, Robert J W; Bricaud, Annick; Oelker, Julia; Peeken, Ilka; Gentili, Bernard; Rozanov, Vladimir V; Bracher, Astrid (2017): Synergistic Exploitation of Hyper- and Multi-Spectral Precursor Sentinel Measurements to Determine Phytoplankton Functional Types (SynSenPFT). Frontiers in Marine Science, 4(203), 22 pp, https://doi.org/10.3389/fmars.2017.00203
Always quote above citation when using data! You can download the citation in several formats below.
This phytoplankton group (PFT) concentration a (Chl a) data are output from the algorithm PhytoDOAS version 3.3 applied to SCIAMACHY data from 2 Aug 2002 to 8 Apr 2012. Data have been gridded monthly on 0.5° latitude to 0.5°. For cyanobacteria (includes all prokaryotic phytoplankton) and diatoms the PhytoDOAS PFT retrieval algorithm by Bracher et al. (2009) and for coccolithophores the algorithm by Sadeghi et al. (2012) have been used. However, these methods have slightly been improved which includes:
- Data during SCIAMACHY instrument decontamination are excluded in the analysis.
- SCIAMACHY level-1b input data for PhytoDOAS are now version 7.04 data (instead of version 6.0).
- The wavelength window for all three phytoplankton groups (PFTs) fit factor starts at 427.5 nm (instead of 429 nm).
- Coccolithophores fit factors are retrieved in a retrieval fitting simultaneously diatoms and coccolithophores (instead of a triple fit with also fitting dinoflagellates as in Sadeghi et al. 2012).
- Vibrational Raman Scattering (VRS) is now fitted directly in the blue spectrum (450 to 495 nm), following Dinter et al. (2015), (instead of in the UV—A region as in Vountas et al. 2007) except that here the daily solar background spectrum measured by SCIAMACHY and the VRS pseudo absorption spectrum calculated based on a SCIAMACHY solar spectrum following Vountas et al. (2007) was used in order to correct for the variation of instrumental effects over time (this is not achieved when using the RTM simulated background spectrum as done in Dinter et al. 2015).
- The PFT Chl a are derived from the ratio of the PFT fit factor to the VRS fit factor multiplied by a LUT (Look Up Table). The LUT is based on radiative transfer model (RTM) SCIATRAN simulations (see Rozanov et al. 2014) accounting also for changing solar zenith angle (SZA).
Bracher, Astrid; Vountas, Marco; Dinter, Tilman; Burrows, John Philip; Röttgers, Rüdiger; Peeken, Ilka (2009): Quantitative observation of cyanobacteria and diatoms from space using PhytoDOAS on SCIAMACHY data. Biogeosciences, 6(5), 751-764, https://doi.org/10.5194/bg-6-751-2009
Dinter, Tilman; Rozanov, Vladimir V; Burrows, John Philip; Bracher, Astrid (2015): Retrieving the availability of light in the ocean utilising spectral signatures of vibrational Raman scattering in hyper-spectral satellite measurements. Ocean Science, 11(3), 373-389, https://doi.org/10.5194/os-11-373-2015
Rozanov, Vladimir V; Rozanov, Alexei; Kokhanovsky, Alexander A; Burrows, John Philip (2014): Radiative transfer through terrestrial atmosphere and ocean: Software package SCIATRAN. Journal of Quantitative Spectroscopy and Radiative Transfer, 133, 13-71, https://doi.org/10.1016/j.jqsrt.2013.07.004
Sadeghi, Alireza; Dinter, Tilman; Vountas, Marco; Taylor, Bettina B; Soppa, Mariana A; Peeken, Ilka; Bracher, Astrid (2012): Improvement to the PhytoDOAS method for identification of coccolithophores using hyper-spectral satellite data. Ocean Science, 8(6), 1055-1070, https://doi.org/10.5194/os-8-1055-2012
- SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY) on ENVISAT
Variable names for variables provided:
- DIA - Diatoms
- COC - Coccolithophores
- CYA - Cyanobacteria
- [mg Chl a/m**3] for DIA_YYYYDD.grd
- [mg Chl a/m**3] for COC_YYYYDD.grd
- [mg Chl a/m**3] for CYA_YYYYDD.grd