Biophysical consequences of a relaxing Beaufort Gyre

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zhang, J., Spitz, Y. H., Steele, M., Ashjian, C., Campbell, R., & Schweiger, A. Biophysical consequences of a relaxing Beaufort Gyre. Geophysica...

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Bibliographic Details
Published in:Geophysical Research Letters
Main Authors: Zhang, Jinlun, Spitz, Yvette H., Steele, Michael, Ashjian, Carin J., Campbell, Robert G., Schweiger, Axel
Format: Article in Journal/Newspaper
Language:unknown
Published: American Geophysical Union 2019
Subjects:
Kay
Online Access:https://hdl.handle.net/1912/25640
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Summary:© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zhang, J., Spitz, Y. H., Steele, M., Ashjian, C., Campbell, R., & Schweiger, A. Biophysical consequences of a relaxing Beaufort Gyre. Geophysical Research Letters, 47(2), (2020): e2019GL085990, doi:10.1029/2019GL085990. A biophysical model shows that Beaufort Gyre (BG) intensification in 2004–2016 is followed by relaxation in 2017–2018, based on a BG variability index. BG intensification leads to enhanced downwelling in the central Canada Basin (CCB) and upwelling along the coast. In the CCB, enhanced downwelling reduces nutrients, thus lowering primary productivity (PP) and plankton biomass. Enhanced upwelling along the coast and in parts of the Chukchi shelf/slope increases nutrients, leading to elevated PP/biomass in the Pacific Arctic Ocean (PAO) outside of the CCB. The overall PAO PP/biomass is dominated by the shelf/slope response and thus increases during BG intensification. As the BG relaxes in 2017–2018, these processes largely reverse, with increasing PP/biomass in the CCB and decreasing PP/biomass in most of the shelf/slope regions. Because the shelf/slope regions are much more productive than the CCB, BG relaxation has the tendency to reduce the overall production in the PAO. This work is funded by the NASA Cryosphere Program (NNX15AG68G and NNX17AD27G), the NSF Office of Polar Programs (PLR‐1416920, PLR‐1603259, PLR‐1603266, OPP‐1751363, PLR‐1602521, and PLR‐1503298), the NOAA Climate Program Office (NA15OAR4310170 and NA15OAR4320063AM170), and ONR (N00014‐17‐1‐2545). We thank Drs. Benjamin Rabe and Edward Doddridge for their constructive comments and Kay Runciman for graphics support. CFS reanalysis data used for model forcing are available online (https://www.ncdc.noaa.gov/data‐access/model‐data/model‐datasets/climate‐forecast‐system‐version2‐cfsv2). Model results are in https://pscfiles.apl.uw.edu/zhang/BIOMAS168x180/ website.