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  • Gross primary production  (3)
  • Bay of Bengal  (2)
  • American Geophysical Union  (5)
  • 2015-2019  (5)
  • 1960-1964
  • 1930-1934
  • 2019  (5)
Collection
Publisher
  • American Geophysical Union  (5)
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  • 2015-2019  (5)
  • 1960-1964
  • 1930-1934
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  • 2019  (5)
  • 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 Geophysical Research Letters 46(10), (2019): 5369-5377, doi: 10.1029/2019GL082078.
    Description: Seasonal evolution of the barrier layer (BL) and temperature inversion in the northern Bay of Bengal and their role on the mixed layer temperature (MLT) is examined using observations from a single Argo during December 2013 to July 2017. During fall, low salinity at surface generates BL in this region. It thickens to almost 80 m in winter enhanced by deepening of isothermal layer depth due to remote forcing. During winter, surface cooling lowers near‐surface temperature, and thus, the subsurface BL experiences a significant temperature inversion (~2.5 °C). This temperature inversion diffuses to distribute heat within ML and surface heating begins deep penetration of shortwave radiation through ML during spring. Hence, the ML becomes thermally well stratified, resulting in the warmest MLT. The Monin‐Obukhov length attains its highest value during summer indicating wind dominance in the ML. During spring and fall, upper ocean gains heat allowing buoyancy to dominate over wind mixing.
    Description: A. S. and S. S. thank financial support from Space Application Centre (SAC), Indian Space Research Organization (ISRO), Government of India (Grant: SAC/EPSA/4.19/2016). This study was also supported by the first phase of Ministry of Earth Sciences (MoES), Government of India grant to establish a Bay of Bengal Coastal Observatory (BOBCO) at IITBBS (Grant: RP088). Authors acknowledged NCPOR Contribution number J ‐ 03/2019‐20 for this work. The authors are grateful to the reviewers and the Editor for constructive suggestions. The figures are generated using Matlab. The data source and availability are given in the Text S1.
    Description: 2019-10-24
    Keywords: Argo ; Bay of Bengal ; mixed layer ; temperature inversion ; barrier layer ; Monin‐Obukhov length
    Repository Name: Woods Hole Open Access Server
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  • 5
    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 Geophysical Research Letters, 46(8), (2019):4346-4355, doi:10.1029/2018GL081577.
    Description: A yearlong record from moored current, temperature, conductivity, and four mixing meters (χpods) in the northernmost international waters of the Bay of Bengal quantifies upper‐ocean turbulent diffusivity of heat (Kt) and its response to the Indian monsoon. Data indicate (1) pronounced intermittency in turbulence at semidiurnal, diurnal, and near‐inertial timescales, (2) strong turbulence above 25‐m depth during the SW (summer) and NE (winter) monsoon relative to the transition periods (compare Kt 〉 10−4 m2/s to Kt  ∼ 10−5 m2/s, and (3) persistent suppression of turbulence (Kt 〈 10−5 m2/s) for 3 to 5 months in the latter half of the SW monsoon coincident with enhanced near‐surface stratification postarrival of low‐salinity water from the Brahmaputra‐Ganga‐Meghna delta and monsoonal precipitation. This suppression promotes maintenance of the low‐salinity surface waters within the interior of the bay preconditioning the upper northern Indian Ocean for the next year's monsoon.
    Description: This work was supported by the U.S. Office of Naval Research (ONR) Grants N00014‐14‐1‐0236 and N00014‐17‐1‐2472, and the Ocean Mixing and Monsoon program of the Indian Ministry of Earth Sciences. The deployment of the Woods Hole Oceanographic Institution mooring and RW and JTF were supported by ONR Grant N00014‐13‐1‐0453. The deployment and recovery of the mooring were carried out by RV Sagar Nidhi and RV Sagar Kanya, respectively, with the help of the crew and science parties. Thanks to National Institute of Ocean Technology (India) for buoy support. The authors acknowledge invaluable discussions with Johannes Becherer, Deepak Cherian, and Sally Warner at CEOAS, OSU, and Dipanjan Chaudhuri, J Sree Lekha, and Debasis Sengupta at CAOS, IISc. The authors thank two anonymous reviewers for their detailed reviews, which have helped sharpen many aspects of this paper. Data can be accessed as described in section S2.
    Description: 2019-10-08
    Keywords: Ocean turbulence ; Turbulence suppression ; Indian Monsoon ; Bay of Bengal ; Turbulent Mixing ; Chipod
    Repository Name: Woods Hole Open Access Server
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