English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll‐a‐based models

Lee, Y. J., Matrai, P. A., Friedrichs, M. A. M., Saba, V. S., Antoine, D., Ardyna, M., et al. (2015). An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll‐a‐based models. Journal of Geophysical Research: Oceans, 120: 10.1002/2015JC011018, pp. 1-34.

Item is

Files

show Files
hide Files
:
Fernandez_15.pdf (Publisher version), 6MB
Name:
Fernandez_15.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Lee, Younjoo J., Author
Matrai, Patricia A., Author
Friedrichs, Marjorie A. M., Author
Saba, Vincent S., Author
Antoine, David, Author
Ardyna, Mathieu, Author
Asanuma, Ichio, Author
Babin, Marcel, Author
Belanger, Simon, Author
Benoit-Gagne, Maxime, Author
Devred, Emmanuel, Author
Fernandez-Mendez, Mar1, Author           
Gentili, Bernard, Author
Hirawake, Toru, Author
Kang, Sung-Ho, Author
Kameda, Takahiko, Author
Katlein, Christian1, Author           
Lee, Sang H., Author
Lee, Zhongping, Author
Melin, Frederic, Author
Scardi, Michele, AuthorSmyth, Tim J., AuthorTang, Shilin, AuthorTurpie, Kevin R., AuthorWaters, Kirk J., AuthorWestberry, Toby K., Author more..
Affiliations:
1HGF MPG Joint Research Group for Deep Sea Ecology & Technology, Max Planck Institute for Marine Microbiology, Max Planck Society, ou_2481702              

Content

show
hide
Free keywords: -
 Abstract: We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.

Details

show
hide
Language(s): eng - English
 Dates: 2015-09-27
 Publication Status: Issued
 Pages: 34
 Publishing info: -
 Table of Contents: -
 Rev. Type: Internal
 Identifiers: eDoc: 713960
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Journal of Geophysical Research: Oceans
  Other : JGR-C
  Abbreviation : J. Geophys. Res. - C
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Hoboken, NJ : Wiley
Pages: - Volume / Issue: 120 Sequence Number: 10.1002/2015JC011018 Start / End Page: 1 - 34 Identifier: ISSN: 2169-9291
CoNE: https://pure.mpg.de/cone/journals/resource/2169-9291