Project Funding: 2013 - 2015

NRA: 2012 NASA: Ocean Biology and Biogeochemistry   

Funded by NASA

Abstract:
Autochthonous primary production is the major source of energy for the Arctic Ocean (AO)ecosystem. In the last decade, it appears that net primary productivity (NPP) in the AO has increased considerably, as estimated from remotely-sensed observations; however, we do not yet have sufficient spatial data coverage to validate such trends over the entire AO. Although Arctic marine NPP is strongly seasonal, some Arctic shelf seas rank among the most productive regions in the world ocean, whereas mean NPP in deep AO basins is among the lowest. Through bottomup forcing in the food web, marine NPP constrains pelagic and benthic higher trophic levels,including significant national and local community fisheries. Therefore, changes in NPP are likely to significantly impact the Arctic's living marine resources and many biogeochemical cycles. However, consensus about the relative importance of variables and processes controlling NPP in the AO at different times and in different regions is lacking. Sea ice, colored dissolved organic matter, and stratification are the major controls of the light regime for phytoplankton while winter wind mixing, upwelling, eddies, river discharge and stratification are involved in nutrient replenishment. Given projected high sensitivity of the AO to climate change, combined with the observed contemporary changes, a regional AO PP assessment will provide an essential step forward in this region. We propose to conduct a Primary Productivity Algorithm Round Robin activity (PPARR) as a framework in which the skill and sensitivities of NPP models in the AO, including both satellite NPP models and coupled biogeochemical-circulation models, can be assessed through multiple types of comparisons. Regional NPP models are becoming available for the AO and helping to understand the biogeochemistry of this region, especially at times and in sectors where field sampling is difficult, if not impossible, due to extremely harsh conditions or diplomatic lack of access to major portions of the AO. Most ocean color models estimate NPP from concentrations of surface chlorophyll-a, which is especially important in the AO where the heterogeneity in space and time of the available in situ chlorophyll-a and NPP data make the extensive coverage of satellite data particularly attractive. However, the AO presents several obstacles to remote sensing of ocean color and derivation of accurate estimates of surface chlorophyll-a, such as sea ice, cloud cover, land-derived river-borne colored dissolved organic matter, deep subsurface chlorophyll-a maxima, and climate change. Our proposed PPARR5 will include a comparison of 20-30 ocean color, biogeochemical ocean circulation models, and 7-10 fully-coupled Earth System Models contributing to the fifth assessment of the Intergovernmental Panel on Climate Change (IPCC). Model estimates of NPP will be compared to each other in terms of bias and variability. Average and individual model skill will be assessed on a region-specific basis (e.g., neritic versus pelagic) by comparing estimates of integrated and depth-specific NPP to in situ 14C measurements. Next, the effect of deep chlorophyll-a maximum on integrated vs. surface NPP will be determined. Finally, we will compare projections of NPP up to the year 2100 for the AO from the Earth System Models under the climate change scenarios in the fifth IPCC assessment. Our project responds directly to the NRA- Ocean Biology and Biogeochemistry (OBB) priority areas on New analyses of impacts to and vulnerability of aquatic ecosystems/ biological oceanography to global environmental or climate variability and change and Successor studies that offer to significantly advance the results of prior NASA OBB research toward meaningful answers to important NASA and USGCRP carbon cycle and ecosystems and NOC research questions.

Publications:

Laliberte, J., Belanger, S., Frouin, R. 2016. Evaluation of satellite-based algorithms to estimate photosynthetically available radiation (PAR) reaching the ocean surface at high northern latitudes. Remote Sensing of Environment. 184, 199-211. DOI: 10.1016/j.rse.2016.06.014

Lee, Y. J., Matrai, P. A., Friedrichs, M. A. M., Saba, V. S., Antoine, D., Ardyna, M., Asanuma, I., Babin, M., Belanger, S., Benoit-Gagne, M., Devred, E., Fernandez-Mendez, M., Gentili, B., Hirawake, T., Kang, S., Kameda, T., Katlein, C., Lee, S. H., Lee, Z., Melin, F., Scardi, M., Smyth, T. J., Tang, S., Turpie, K. R., Waters, K. J., Westberry, T. K. 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(9), 6508-6541. DOI: 10.1002/2015JC011018

Lee, Y. J., Matrai, P. A., Friedrichs, M. A. M., Saba, V. S., Aumont, O., Babin, M., Buitenhuis, E. T., Chevallier, M., de Mora, L., Dessert, M., Dunne, J. P., Ellingsen, I. H., Feldman, D., Frouin, R., Gehlen, M., Gorgues, T., Ilyina, T., Jin, M., John, J. G., Lawrence, J., Manizza, M., Menkes, C. E., Perruche, C., Le Fouest, V., Popova, E. E., Romanou, A., Samuelsen, A., Schwinger, J., Seferian, R., Stock, C. A., Tjiputra, J., Tremblay, L. B., Ueyoshi, K., Vichi, M., Yool, A., Zhang, J. 2016. Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models. Journal of Geophysical Research: Oceans. 121(12), 8635-8669. DOI: 10.1002/2016JC011993

2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)

• An Assessment of Ocean Color Model Estimates of Net Primary Productivity (NPP) in the Arctic Ocean   --   (Younjoo Lee, Patricia Matrai, Marjorie Friedrichs, Vincent S Saba)   [abstract]

More details may be found in the following project profile(s):

• NASA Ocean Biology & Biogeochemistry (OBB) Project Profile