Not logged in
PANGAEA.
Data Publisher for Earth & Environmental Science

Gonçalves-Araujo, Rafael; Peeken, Ilka; Bracher, Astrid (2018): Colored dissolved organic matter absorption by waters of central-eastern Arctic Ocean. PANGAEA, https://doi.org/10.1594/PANGAEA.867532, Supplement to: Gonçalves-Araujo, Rafael; Rabe, Benjamin; Peeken, Ilka; Bracher, Astrid (2018): High colored dissolved organic matter (CDOM) absorption in surface waters of the central-eastern Arctic Ocean: Implications for biogeochemistry and ocean color algorithms. PLoS ONE, 13(1), e0190838, https://doi.org/10.1371/journal.pone.0190838

Always quote above citation when using data! You can download the citation in several formats below.

RIS CitationBibTeX CitationShow MapGoogle Earth

Abstract:
As consequences of global warming sea-ice shrinking, permafrost thawing and changes in fresh water and terrestrial material export have already been reported in the Arctic environment. These processes impact light penetration and primary production. To reach a better understanding of the current status and to provide accurate forecasts Arctic biogeochemical and physical parameters need to be extensively monitored. In this sense, bio-optical properties are useful to be measured due to the applicability of optical instrumentation to autonomous platforms, including satellites. This study characterizes the non-water absorbers and their coupling to hydrographic conditions in the poorly sampled surface waters of the central and eastern Arctic Ocean. Over the entire sampled area colored dissolved organic matter (CDOM) dominates the light absorption in surface waters. The distribution of CDOM, phytoplankton and non-algal particles absorption reproduces the hydrographic variability in this region of the Arctic Ocean which suggests a subdivision into five major bio-optical provinces: Laptev Sea Shelf, Laptev Sea, Central Arctic/Transpolar Drift, Beaufort Gyre and Eurasian/Nansen Basin. Evaluating ocean color algorithms commonly applied in the Arctic Ocean shows that global and regionally tuned empirical algorithms provide poor chlorophyll-a (Chl-a) estimates. The semi-analytical algorithms Generalized Inherent Optical Property model (GIOP) and Garver-Siegel-Maritorena (GSM), on the other hand, provide robust estimates of Chl-a and absorption of colored matter. Applying GSM with modifications proposed for the western Arctic Ocean produced reliable information on the absorption by colored matter, and specifically by CDOM. These findings highlight that only semi-analytical ocean color algorithms are able to identify with low uncertainty the distribution of the different optical water constituents in these high CDOM absorbing waters. In addition, a clustering of the Arctic Ocean into bio-optical provinces will help to develop and then select province-specific ocean color algorithms.
Coverage:
Median Latitude: 84.087473 * Median Longitude: 125.372209 * South-bound Latitude: 76.177000 * West-bound Longitude: 28.797170 * North-bound Latitude: 89.965000 * East-bound Longitude: -116.180000
Date/Time Start: 2011-08-07T12:07:00 * Date/Time End: 2011-09-26T02:11:00
Size:
9 datasets

Download Data

Download ZIP file containing all datasets as tab-delimited text (use the following character encoding: )

Datasets listed in this Collection

  1. Bracher, A; Gonçalves-Araujo, R; Dinter, T et al. (2018): Convoluted remote sensing reflectance obtained from spectral underwater upwelling radiance and in air solar downwelling irradiance measurements during POLARSTERN cruise ARK-XXVI/3 (PS78). https://doi.org/10.1594/PANGAEA.884525
  2. Bracher, A; Gonçalves-Araujo, R; Dinter, T et al. (2018): Convoluted remote sensing reflectance obtained from spectral underwater upwelling radiance and solar downwelling irradiance measurements during POLARSTERN cruise ARK-XXVI/3 (PS78). https://doi.org/10.1594/PANGAEA.884527
  3. Bracher, A; Gonçalves-Araujo, R; Dinter, T et al. (2018): Remote sensing reflectance obtained from spectral underwater upwelling radiance and in air solar downwelling irradiance measurements during POLARSTERN cruise ARK-XXVI/3 (PS78). https://doi.org/10.1594/PANGAEA.884526
  4. Bracher, A; Gonçalves-Araujo, R; Dinter, T et al. (2018): Remote sensing reflectance obtained from spectral underwater upwelling radiance and solar downwelling irradiance measurements during POLARSTERN cruise ARK-XXVI/3 (PS78). https://doi.org/10.1594/PANGAEA.884528
  5. Gonçalves-Araujo, R; Wiegmann, S; Bracher, A (2018): Absorption coefficient spectra of colored dissolved organic matter during POLARSTERN cruise ARK-XXVI/3 (PS78, TRANSARC). https://doi.org/10.1594/PANGAEA.885244
  6. Gonçalves-Araujo, R; Wiegmann, S; Bracher, A (2018): Absorption coefficient spectra of non-algal particles during POLARSTERN cruise ARK-XXVI/3 (PS78, TRANSARC). https://doi.org/10.1594/PANGAEA.885245
  7. Gonçalves-Araujo, R; Wiegmann, S; Bracher, A (2016): Non-water absorption of colored dissolved organic matter, phytoplanktonn and non-algal particles during POLARSTERN cruise ARK-XXVI/3 (TRANSARC ). https://doi.org/10.1594/PANGAEA.867507
  8. Gonçalves-Araujo, R; Wiegmann, S; Bracher, A (2018): Phytoplankton absorption coefficient spectra during POLARSTERN cruise ARK-XXVI/3 (PS78, TRANSARC). https://doi.org/10.1594/PANGAEA.885246
  9. Peeken, I; Murawski, S (2016): Chlorophyll a measured on water bottle samples using HPLC during POLARSTERN cruise ARK-XXVI/3 (TRANSARC ). https://doi.org/10.1594/PANGAEA.867473