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  • Gross primary production  (3)
  • Beaufort Gyre  (2)
  • American Geophysical Union  (5)
  • American Association for the Advancement of Science
  • Periodicals Archive Online (PAO)
  • Wiley
  • 2015-2019  (5)
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  • 2019  (5)
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  • American Geophysical Union  (5)
  • American Association for the Advancement of Science
  • Periodicals Archive Online (PAO)
  • Wiley
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  • 2015-2019  (5)
  • 1990-1994
  • 1970-1974
  • 1950-1954
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  • 2019  (5)
  • 1972
  • 1
    Publication Date: 2022-10-20
    Description: Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 123(11), (2018): 8411-8429, doi: 10.1029/2018JC014178.
    Description: A method for estimating gross primary production (GPP) is presented and validated against a numerical model of Chesapeake Bay that includes realistic physical and biological forcing. The method statistically fits a photosynthesis‐irradiance response curve using the observed near‐surface time rate of change of dissolved oxygen and the incoming solar radiation, yielding estimates of the light‐saturated photosynthetic rate and the initial slope of the photosynthesis‐irradiance response curve. This allows estimation of GPP with 15‐day temporal resolution. The method is applied to the output from a numerical model that has high skill at reproducing both surface and near‐bottom dissolved oxygen variations observed in Chesapeake Bay in 2013. The rate of GPP predicted by the numerical model is known, as are the contributions from physical processes, allowing the proposed diel method to be rigorously assessed. At locations throughout the main stem of the Bay, the method accurately extracts the underlying rate of GPP, including pronounced seasonal variability and spatial variability. Errors associated with the method are primarily the result of contributions by the divergence in turbulent oxygen flux, which changes sign over the surface mixed layer. As a result, there is an optimal vertical location with minimal bias where application of the method is most accurate.
    Description: This paper is the result of research funded in part by NOAA's U.S. Integrated Ocean Observing System (IOOS) Program Office as a subcontract to the Woods Hole Oceanographic Institution under award NA13NOS120139 to the Southeastern University Research Association. All of the model output, as well as both the CBIBS data (2010–2016) and the bottom oxygen data of Scully (2016b), are publicly available through the THREDDS server associated with the IOOS Coastal Modeling Testbed site: https://comt.ioos.us/projects/cb_hypoxia.
    Description: 2019-05-24
    Keywords: Gross primary production ; Vertical mixing ; Numerical model ; Chesapeake Bay
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-10-20
    Description: Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 123(11), (2018): 8430-8443, doi: 10.1029/2018JC014179.
    Description: A diel method for estimating gross primary production (GPP) is applied to nearly continuous measurements of near‐surface dissolved oxygen collected at seven locations throughout the main stem of Chesapeake Bay. The data were collected through the Chesapeake Bay Interpretive Buoy System and span the period 2010–2016. At all locations, GPP exhibits pronounced seasonal variability consistent temperature‐dependent phytoplankton growth. At the Susquehanna Buoy, which is located within the estuarine turbidity maximum, rates of GPP are negatively correlated with uncalibrated turbidity data consistent with light limitation at this location. The highest rates of GPP are located immediately down Bay from the estuarine turbidity maximum and decrease moving seaward consistent with nutrient limitation. Rates of GPP at the mouth (First Landing Buoy) are roughly a factor of 3 lower than the rates in the upper Bay (Patapsco). At interannual time scales, the summer (June–July) rate of GPP averaged over all stations is positively correlated (r2 = 0.62) with the March Susquehanna River discharge and a multiple regression model that includes spring river discharge, and summer water temperature can explain most (r2 = 0.88) of the interannual variance in the observed rate of GPP. The correlation with river discharge is consistent with an increase in productivity fueled by increased nutrient loading. More generally, the spatial and temporal patterns inferred using this method are consistent with our current understanding of primary production in the Bay, demonstrating the potential this method has for making highly resolved measurements in less well studied estuarine systems.
    Description: This paper is the result of research funded in part by NOAA's U.S. Integrated Ocean Observing System (IOOS) Program Office as a subcontract to the Woods Hole Oceanographic Institution under award NA13NOS120139 to the Southeastern University Research Association. All of the data analyzed in this paper are publicly available including the CBIBS data (http://buoybay.noaa.gov), the NCEP NARR data (https://www.esrl.noaa.gov/psd), and the Kd‐490 MODIS data (ftp://ftp.star.nesdis.noaa.gov/pub/socd1/ecn/data/modis/k490noaa/monthly/cd/). Model output analyzed in this paper is publicly available through the THREDDS server associated with the IOOS Coastal and Ocean Modeling Testbed (COMT) site (https://comt.ioos.us/projects/cb_hypoxia). Postprocessed and compiled data for all seven CBIBS locations including the interpolated values of incoming solar radiation and satellite‐derived Kd‐490 can also be download from the COMT site.
    Description: 2019-05-25
    Keywords: Gross primary production ; Chesapeake Bay ; Observing system ; Diel variability
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
    Publication Date: 2022-10-26
    Description: Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Oceans 124(6), (2019): 3628-3644, doi:10.1029/2018JC014805.
    Description: The Arctic Ocean is experiencing profound environmental changes as the climate warms. Understanding how these changes will affect Arctic biological productivity is key for predicting future Arctic ecosystems and the global CO2 balance. Here we use in situ gas measurements to quantify rates of gross oxygen production (GOP, total photosynthesis) and net community production (NCP, net CO2 drawdown by the biological pump) in the mixed layer in summer or fall from 2011 to 2016 in the Beaufort Gyre. NCP and GOP show spatial and temporal variations with higher values linked with lower concentrations of sea ice and increased upper ocean stratification. Mean rates of GOP range from 8 ± 1 to 54 ± 9 mmol O2·m−2·d−1 with the highest mean rates occurring in summer of 2012. Mean rates of NCP ranged from 1.3 ± 0.2 to 2.9 ± 0.5 mmol O2·m−2·d−1. The mean ratio of NCP/GOP, a measure of how efficiently the ecosystem is recycling its nutrients, ranged from 0.04 to 0.17, similar to ratios observed at lower latitudes. Additionally, a large increase in total photosynthesis that occurred in 2012, a year of historically low sea ice coverage, persisted for many years. Taken together, these data provide one of the most complete characterizations of interannual variations of biological productivity in this climatically important region, can serve as a baseline for future changes in rates of production, and give an intriguing glimpse of how this region of the Arctic may respond to future lack of sea ice.
    Description: We sincerely thank the scientific teams of Fisheries and Oceans Canada's Joint Ocean Ice Studies expedition and Woods Hole Oceanographic Institution's Beaufort Gyre Observing System. The hydrographic, nutrient, and chlorophyll data were collected and made available by the Beaufort Gyre Exploration Program based at the Woods Hole Oceanographic Institution (http://www.whoi.edu/beaufortgyre) in collaboration with researchers from Fisheries and Oceans Canada at the Institute of Ocean Sciences. We thank the captains and crews of the Canadian icebreaker CCGS Louis S. St‐Laurent and Mike Dempsey for sample collection. This paper was improved by the suggestions of Michael DeGrandpre and one anonymous reviewer. We are grateful to Qing Wang at Wellesley College for her assistance with statistics. We thank our funding sources: the National Science Foundation (NSF 1547011, NSF 1302884, NSF 1719280, NSF 1643735) and the support of Fisheries and Oceans Canada. Data presented and discussed in this paper can be found in the Arctic Data Center (http://10.18739/A2W389).
    Description: 2019-10-30
    Keywords: Oxygen ; Argon ; Gross primary production ; Net community production ; Sea ice ; Triple oxygen isotopes
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Oceans 124(2), (2019):863-881, doi:10.1029/2018JC014604.
    Description: Pacific Winter Water (PWW) enters the western Arctic Ocean from the Chukchi Sea; however, the physical mechanisms that regulate its circulation within the deep basin are still not clear. Here, we investigate the interannual variability of PWW with a comprehensive data set over a decade. We quantify the thickening and expansion of the PWW layer during 2002–2016, as well as its changing pathway. The total volume of PWW in the Beaufort Gyre (BG) region is estimated to have increased from 3.48 ± 0.04 × 1014 m3 during 2002–2006 to 4.11 ± 0.02 × 1014 m3 during 2011–2016, an increase of 18%. We find that the deepening rate of the lower bound of PWW is almost double that of its upper bound in the northern Canada Basin, a result of lateral flux convergence of PWW (via lateral advection of PWW from the Chukchi Borderland) in addition to the Ekman pumping. In particular, of the 70‐m deepening of PWW at its lower bound observed over 2003–2011 in the northwestern basin, 43% resulted from lateral flux convergence. We also find a redistribution of PWW in recent years toward the Chukchi Borderland associated with the wind‐driven spin‐up and westward shift of the BG. Finally, we hypothesize that a recently observed increase of lower halocline eddies in the BG might be explained by this redistribution, through a compression mechanism over the Chukchi Borderland.
    Description: Three anonymous reviewers provided helpful comments and suggestions, which greatly improved this manuscript. We thank John Marshall (MIT) and Georgy Manucharyan (Caltech) for valuable discussions and inputs. We thank Peigen Lin (WHOI), Qinyu Liu, and Jinping Zhao (OUC) for helpful discussions. The Matlab wind rose toolbox is written by Daniel Pereira. This study is supported by the National Key Basic Research Program of China (Program 973) (2015CB953900; 2018YFA0605901), the Key Project of Chinese Natural Science Foundation (41330960), and the National Natural Science Foundation of China (41706211 and 41776192), the Office of Naval Research (grant N00014‐12‐1‐0112), the NSF Office of Polar Programs (PLR‐1416920, PLR‐1503298, PLR‐1602985, PLR‐1603259, ARC‐1203425, and NSF‐1602926). Wenli Zhong (201606335011) is supported by the China Scholarship Council for his studies in APL. We appreciate Andrey Proshutinsky and Rick Krishfield (WHOI) for providing the Beaufort Gyre Exploration Project data publicly at http://www.whoi.edu/website/beaufortgyre/. The Ice‐Tethered Profiler data were collected and made available by the Ice‐Tethered Profiler Program (Krishfield et al., 2008; Toole et al., 2011) based at the Woods Hole Oceanographic Institution (http://www.whoi.edu/itp). The Monthly Isopycnal/Mixed‐layer Ocean Climatology (MIMOC) data are available at https://www.pmel.noaa.gov/mimoc/. The monthly Arctic Dynamic Ocean Topography data are distributed by CPOM (http://www.cpom.ucl.ac.uk/dynamic_topography/). The IBCAO Bathymetry data are available from NASA (http://www.ngdc.noaa.gov/mgg/bathymetry/arctic/arctic.html). The Data‐Interpolating Variational Analysis method is publicly available at http://modb.oce.ulg.ac.be/mediawiki/index.php/DIVA.
    Description: 2019-07-16
    Keywords: Beaufort Gyre ; Pacific Winter Water ; PWW pathway ; lower halocline eddies ; western Arctic Ocean
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2019. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research-Oceans 124(7), (2019): 4696-4709, doi: 10.1029/2019JC015022.
    Description: The Beaufort Gyre is a key feature of the Arctic Ocean, acting as a reservoir for freshwater in the region. Depending on whether the prevailing atmospheric circulation in the Arctic is anticyclonic or cyclonic, either a net accumulation or release of freshwater occurs. The sources of freshwater to the Arctic Ocean are well established and include contributions from the North American and Eurasian Rivers, the Bering Strait Pacific water inflow, sea ice meltwater, and precipitation, but their contribution to the Beaufort Gyre freshwater accumulation varies with changes in the atmospheric circulation. Here we use a Lagrangian backward tracking technique in conjunction with the 1/12‐degree resolution Nucleus for European Modelling of the Ocean model to investigate how sources of freshwater to the Beaufort Gyre have changed in recent decades, focusing on increase in the Pacific water content in the gyre between the late 1980s and early 2000s. Using empirical orthogonal functions we analyze the change in the Arctic oceanic circulation that occurred between the 1980s and 2000s. We highlight a “waiting room” advective pathway that was present in the 1980s and provide evidence that this pathway was caused by a shift in the center of Ekman transport convergence in the Arctic. We discuss the role of these changes as a contributing factor to changes in the stratification, and hence potentially the biology, of the Beaufort Gyre region.
    Description: The underpinning high‐resolution NEMO simulation was performed using the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk). ARIANE simulations were performed using the JASMIN data analysis environment (http://www.jasmin.ac.uk). Lagrangian analysis was carried out using computational tool ARIANE developed by B. Blanke and N. Grima. Arctic dynamic topography/geostrophic currents data were provided by the Centre for Polar Observation and Modelling, University College London (www.cpom.ucl.ac.uk/dynamic_topography; Armitage et al., 2016). The funding for A. Proshutinsky was provided by the NSF under grants supporting the Beaufort Gyre Observing System since 2003 (1845877, 1719280, 1604085) and by the Woods Hole Oceanographic Institution. Y. Aksenov was supported from the NERC Program “The North Atlantic Climate System Integrated Study (ACSIS), NE/N018044/1 and from the project “Advective pathways of nutrients and key ecological substances in the Arctic (APEAR)” NE/R012865/1, as a part of the joint UK/Germany “Changing Arctic Ocean” Programme. A. Yool and E. Popova were supported by NERC grants CLASS NE/R015953/1, and National Capability in Ocean Modelling. We acknowledge the FAMOS (http://web.whoi.edu/famos/) program for providing a framework for many fruitful discussions which thoroughly enhanced this work. Finally, we thank the two anonymous reviewers who greatly improved this work with their insightful input.
    Description: 2019-12-26
    Keywords: Beaufort Gyre ; Lagrangian modeling ; NEMO ; particle tracking
    Repository Name: Woods Hole Open Access Server
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