Global data sets of Chlorophyll a concentration for diatoms, coccolithophores (haptophytes) and cyanobacteria obtained from in situ observations and satellite retrievals ...
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...
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ftdatacite:10.1594/pangaea.873210 2024-03-31T07:51:05+00:00 Global data sets of Chlorophyll a concentration for diatoms, coccolithophores (haptophytes) and cyanobacteria obtained from in situ observations and satellite retrievals ... Losa, Svetlana N 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 application/zip https://dx.doi.org/10.1594/pangaea.873210 https://doi.pangaea.de/10.1594/PANGAEA.873210 en eng PANGAEA https://dx.doi.org/10.3389/fmars.2017.00203 Creative Commons Attribution 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 Arctic Amplification AC3 Supplementary Publication Series of Datasets article Collection 2017 ftdatacite https://doi.org/10.1594/pangaea.87321010.3389/fmars.2017.00203 2024-03-04T13:17:34Z 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 ... : submitted: 2017-03-08 ... Article in Journal/Newspaper Arctic Climate change Phytoplankton DataCite Metadata Store (German National Library of Science and Technology) Arctic |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
Arctic Amplification AC3 |
spellingShingle |
Arctic Amplification AC3 Losa, Svetlana N Soppa, Mariana A Dinter, Tilman Wolanin, Aleksandra Brewin, Robert J W Bricaud, Annick Oelker, Julia Peeken, Ilka Gentili, Bernard Rozanov, Vladimir V Bracher, Astrid Global data sets of Chlorophyll a concentration for diatoms, coccolithophores (haptophytes) and cyanobacteria obtained from in situ observations and satellite retrievals ... |
topic_facet |
Arctic Amplification AC3 |
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 ... : submitted: 2017-03-08 ... |
format |
Article in Journal/Newspaper |
author |
Losa, Svetlana N Soppa, Mariana A Dinter, Tilman Wolanin, Aleksandra Brewin, Robert J W Bricaud, Annick Oelker, Julia Peeken, Ilka Gentili, Bernard Rozanov, Vladimir V Bracher, Astrid |
author_facet |
Losa, Svetlana N Soppa, Mariana A Dinter, Tilman Wolanin, Aleksandra Brewin, Robert J W Bricaud, Annick Oelker, Julia Peeken, Ilka Gentili, Bernard Rozanov, Vladimir V Bracher, Astrid |
author_sort |
Losa, Svetlana N |
title |
Global data sets of Chlorophyll a concentration for diatoms, coccolithophores (haptophytes) and cyanobacteria obtained from in situ observations and satellite retrievals ... |
title_short |
Global data sets of Chlorophyll a concentration for diatoms, coccolithophores (haptophytes) and cyanobacteria obtained from in situ observations and satellite retrievals ... |
title_full |
Global data sets of Chlorophyll a concentration for diatoms, coccolithophores (haptophytes) and cyanobacteria obtained from in situ observations and satellite retrievals ... |
title_fullStr |
Global data sets of Chlorophyll a concentration for diatoms, coccolithophores (haptophytes) and cyanobacteria obtained from in situ observations and satellite retrievals ... |
title_full_unstemmed |
Global data sets of Chlorophyll a concentration for diatoms, coccolithophores (haptophytes) and cyanobacteria obtained from in situ observations and satellite retrievals ... |
title_sort |
global data sets of chlorophyll a concentration for diatoms, coccolithophores (haptophytes) and cyanobacteria obtained from in situ observations and satellite retrievals ... |
publisher |
PANGAEA |
publishDate |
2017 |
url |
https://dx.doi.org/10.1594/pangaea.873210 https://doi.pangaea.de/10.1594/PANGAEA.873210 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change Phytoplankton |
genre_facet |
Arctic Climate change Phytoplankton |
op_relation |
https://dx.doi.org/10.3389/fmars.2017.00203 |
op_rights |
Creative Commons Attribution 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 |
op_doi |
https://doi.org/10.1594/pangaea.87321010.3389/fmars.2017.00203 |
_version_ |
1795029635687251968 |