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  • 1
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    Mixing of dissolved oxygen in Chesapeake Bay driven by the interaction between wind-driven circulation and estuarine bathymetry (2016)
    John Wiley & Sons
    Details
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2016. 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 121 (2016): 5639–5654, doi:10.1002/2016JC011924.
    Description: Field observations collected in Chesapeake Bay demonstrate how wind-driven circulation interacts with estuarine bathymetry to control when and where the vertical mixing of dissolved oxygen occurs. In the across-Bay direction, the lateral Ekman response to along-Bay wind forcing contributes to the vertical mixing of dissolved oxygen in two ways. First, the lateral tilting of the pycnocline/oxycline, consistent with the thermal wind relationship, advects the region of high vertical gradient into the surface and bottom boundary layers where mixing can occur. Second, upwelling of low-oxygen water to the surface enhances the atmospheric influx. In the along-Bay direction, the abrupt change in bottom depth associated with Rappahannock Shoal results in surface convergence and downwelling, leading to localized vertical mixing. Water that is mixed on the shoal is entrained into the up-Bay residual bottom flow resulting in increases in bottom dissolved oxygen that propagate up the system. The increases in dissolved oxygen are often associated with increases in temperature and decreases in salinity, consistent with vertical mixing. However, the lagged arrival moving northward suggests that the propagation of this signal up the Bay is due to advection.
    Description: National Science Foundation Grant Number: OCE-1338518
    Description: 2017-02-08
    Keywords: Mixing ; Hypoxia ; Chesapeake Bay
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
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    Estimating hypoxic volume in the Chesapeake Bay using two continuously sampled oxygen profiles (2018)
    John Wiley & Sons
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 123 (2018): 6392-6407, doi:10.1029/2018JC014129.
    Description: Low levels of dissolved oxygen (DO) occur in many embayments throughout the world and have numerous detrimental effects on biota. Although measurement of in situ DO is straightforward with modern instrumentation, quantifying the volume of water in a given embayment that is hypoxic (hypoxic volume (HV)) is a more difficult task; however, this information is critical for determining whether management efforts to increase DO are having an overall impact. This paper uses output from a three‐dimensional numerical model to demonstrate that HV in Chesapeake Bay can be estimated well with as few as two vertical profiles. In addition, the cumulative hypoxic volume (HVC; the total amount of hypoxia in a given year) can be calculated with relatively low uncertainty (〈10%) if continuous DO data are available from two strategically positioned vertical profiles. This is because HV in the Chesapeake Bay is strongly constrained by the geometry of the embayment. A simple Geometric HV calculation method is presented and numerical model results are used to illustrate that for calculating HVC, the results using two daily‐averaged profiles are typically more accurate than those of the standard method that interpolates bimonthly cruise data. Bimonthly data produce less accurate estimates of HVC because high‐frequency changes in oxygen concentration, for example, due to regional‐weather‐ or storm‐induced changes in wind direction and magnitude, are not resolved. The advantages of supplementing cruise‐based sampling with continuous vertical profiles to estimate HVC should be applicable to other systems where hypoxic water is constrained to a specific area by bathymetry.
    Description: NOAA Grant Number: NA13NOS0120139
    Keywords: Chesapeake Bay ; Oxygen ; Dead zone ; Hypoxia ; Observing systems ; Estuary
    Repository Name: Woods Hole Open Access Server
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  • 3
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    Combining observations and numerical model results to improve estimates of hypoxic volume within the Chesapeake Bay, USA (2014)
    John Wiley & Sons
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 118 (2013): 4924–4944, doi:10.1002/jgrc.20331.
    Description: The overall size of the “dead zone” within the main stem of the Chesapeake Bay and its tidal tributaries is quantified by the hypoxic volume (HV), the volume of water with dissolved oxygen (DO) less than 2 mg/L. To improve estimates of HV, DO was subsampled from the output of 3-D model hindcasts at times/locations matching the set of 2004–2005 stations monitored by the Chesapeake Bay Program. The resulting station profiles were interpolated to produce bay-wide estimates of HV in a manner consistent with nonsynoptic, cruise-based estimates. Interpolations of the same stations sampled synoptically, as well as multiple other combinations of station profiles, were examined in order to quantify uncertainties associated with interpolating HV from observed profiles. The potential uncertainty in summer HV estimates resulting from profiles being collected over 2 weeks rather than synoptically averaged ∼5 km3. This is larger than that due to sampling at discrete stations and interpolating/extrapolating to the entire Chesapeake Bay (2.4 km3). As a result, sampling fewer, selected stations over a shorter time period is likely to reduce uncertainties associated with interpolating HV from observed profiles. A function was derived that when applied to a subset of 13 stations, significantly improved estimates of HV. Finally, multiple metrics for quantifying bay-wide hypoxia were examined, and cumulative hypoxic volume was determined to be particularly useful, as a result of its insensitivity to temporal errors and climate change. A final product of this analysis is a nearly three-decade time series of improved estimates of HV for Chesapeake Bay.
    Description: Funding for this study was provided by the IOOS COMT Program through NOAA grants NA10NOS0120063 and NA11NOS0120141. Additional funding was provided by NSF grant OCE-1061564.
    Keywords: Hypoxia ; Hypoxic volume ; Chesapeake Bay ; Dead zone ; Water quality ; Dissolved oxygen
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
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    A diel method of estimating gross primary production: 1. Validation with a realistic numerical model of Chesapeake Bay (2019)
    American Geophysical Union
    Details
    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
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  • 5
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    A diel method of estimating gross primary production: 2. Application to 7 years of near-surface dissolved oxygen data in Chesapeake Bay. (2019)
    American Geophysical Union
    Details
    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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