The Floor of the Arctic Ocean: Geographic Names

A table listing 54 major features of the ocean floor in the Arctic, gives the final suggested name, approx location, and the status of the name with the US Board on Geographic Names and the Intl. Hydrographic Bureau. Recommendations are based on decisions made at a meeting called by the US Navy Electronics Laboratory, San Diego, Calif, Jan 1966. The criteria for decisions were: consistency with Undersea terms and definitions (US Board on Geographic Names, 1964) and Limits of oceans and seas (Intl Hydrographic Bureau 1953), common usage, priority of discovery or naming, association with established geographic features, and minimizing ambiguity. It is suggested that a straight line across the narrowest constriction of Bering Strait should mark the southern boundary of Chukchi Sea, rather than the Arctic Circle, as recommended by the I.H.B., and that, in the absence of any hydrographic or physiographic features designating a unique region, the name Beaufort Sea should be dropped. The opinions ar those of the writers personally

The temporal response of the length of a partially stratified estuary to changes in river flow and tidal amplitude

Author Posting. © American Meteorological Society, 2009. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 39 (2009): 915-933, doi:10.1175/2008JPO3933.1.The temporal response of the length of a partially mixed estuary to changes in freshwater discharge Qf and tidal amplitude UT is studied using a 108-day time series collected along the length of the Hudson River estuary in the spring and summer of 2004 and a long-term (13.4 yr) record of Qf, UT, and near-surface salinity. When Qf was moderately high, the tidally averaged length of the estuary L5, here defined as the distance from the mouth to the up-estuary location where the vertically averaged salinity is 5 psu, fluctuated by more than 47 km over the spring–neap cycle, ranging from 28 to >75 km. During low flow periods, L5 varied very little over the spring–neap cycle and approached a steady length. The response is quantified and compared to predictions of a linearized model derived from the global estuarine salt balance. The model is forced by fluctuations in Qf and UT relative to average discharge Qo and tidal amplitude UTo and predicts the linear response time scale τ and the steady-state length Lo for average forcing. Two vertical mixing schemes are considered, in which 1) mixing is proportional to UT and 2) dependence of mixing on stratification is also parameterized. Based on least squares fits between L5 and estuary length predicted by the model, estimated τ varied by an order of magnitude from a period of high average discharge (Qo = 750 m3 s−1, τ = 4.2 days) to a period of low discharge (Qo = 170 m3 s−1, τ = 40.4 days). Over the range of observed discharge, Lo Qo−0.30±0.03, consistent with the theoretical scaling for an estuary whose landward salt flux is driven by vertical estuarine exchange circulation. Estimated τ was proportional to the discharge advection time scale (LoA/Qo, where A is the cross-sectional area of the estuary). However, τ was 3–4 times larger than the theoretical prediction. The model with stratification-dependent mixing predicted variations in L5 with higher skill than the model with mixing proportional to UT. This model provides insight into the time-dependent response of a partially stratified estuary to changes in forcing and explains the strong dependence of the amplitude of the spring–neap response on freshwater discharge. However, the utility of the linear model is limited because it assumes a uniform channel, and because the underlying dynamics are nonlinear, and the forcing Qf and UT can undergo large amplitude variations. River discharge, in particular, can vary by over an order of magnitude over time scales comparable to or shorter than the response time scale of the estuary.This study was generously funded by Hudson River Foundation Grant 005/03A and NSF Grant OCE-0452054. Lerczak also received partial support from the Woods Hole Center for Oceans and Human Health, NSF Grant OCE-0430724 and NIEHS Grant 1-P50-ES012742-01

Subtidal salinity and velocity in the Hudson River estuary : observations and modeling

Author Posting. © American Meteorological Society, 2008. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 38 (2008): 753-770, doi:10.1175/2007JPO3808.1.A tidally and cross-sectionally averaged model based on the temporal evolution of the quasi-steady Hansen and Rattray equations is applied to simulate the salinity distribution and vertical exchange flow along the Hudson River estuary. The model achieves high skill at hindcasting salinity and residual velocity variation during a 110-day period in 2004 covering a wide range of river discharges and tidal forcing. The approach is based on an existing model framework that has been modified to improve model skill relative to observations. The external forcing has been modified to capture meteorological time-scale variability in salinity, stratification, and residual velocity due to sea level fluctuations at the open boundary and along-estuary wind stress. To reflect changes in vertical mixing due to stratification, the vertical mixing coefficients have been modified to use the bottom boundary layer height rather than the water depth as an effective mixing length scale. The boundary layer parameterization depends on the tidal amplitude and the local baroclinic pressure gradient through the longitudinal Richardson number, and improves the model response to spring–neap variability in tidal amplitude during periods of high river discharge. Finally, steady-state model solutions are evaluated for both the Hudson River and northern San Francisco Bay over a range of forcing conditions. Agreement between the model and scaling of equilibrium salinity intrusions lends confidence that the approach is transferable to other estuaries, despite significant differences in bathymetry. Discrepancies between the model results and observations at high river discharge are indicative of limits at which the formulation begins to fail, and where an alternative approach that captures two-layer dynamics would be more appropriate.This research was supported by the Hudson River Foundation Grant 005/03A, NSF Grant OCE-0452054, and by the Postdoctoral Scholar Program at the Woods Hole Oceanographic Institution, with funding provided by the J. Seward Johnson Fund

Semi-Automated Image Analysis for the Assessment of Megafaunal Densities at the Arctic Deep-Sea Observatory HAUSGARTEN

Megafauna play an important role in benthic ecosystem function and are sensitive indicators of environmental change. Non-invasive monitoring of benthic communities can be accomplished by seafloor imaging. However, manual quantification of megafauna in images is labor-intensive and therefore, this organism size class is often neglected in ecosystem studies. Automated image analysis has been proposed as a possible approach to such analysis, but the heterogeneity of megafaunal communities poses a non-trivial challenge for such automated techniques. Here, the potential of a generalized object detection architecture, referred to as iSIS (intelligent Screening of underwater Image Sequences), for the quantification of a heterogenous group of megafauna taxa is investigated. The iSIS system is tuned for a particular image sequence (i.e. a transect) using a small subset of the images, in which megafauna taxa positions were previously marked by an expert. To investigate the potential of iSIS and compare its results with those obtained from human experts, a group of eight different taxa from one camera transect of seafloor images taken at the Arctic deep-sea observatory HAUSGARTEN is used. The results show that inter- and intra-observer agreements of human experts exhibit considerable variation between the species, with a similar degree of variation apparent in the automatically derived results obtained by iSIS. Whilst some taxa (e. g. Bathycrinus stalks, Kolga hyalina, small white sea anemone) were well detected by iSIS (i. e. overall Sensitivity: 87%, overall Positive Predictive Value: 67%), some taxa such as the small sea cucumber Elpidia heckeri remain challenging, for both human observers and iSIS

Semi-Automated Image Analysis for the Assessment of Megafaunal Densities at the Arctic Deep-Sea Observatory HAUSGARTEN

Megafauna play an important role in benthic ecosystem function and are sensitive indicators of environmental change. Non-invasive monitoring of benthic communities can be accomplished by seafloor imaging. However, manual quantification of megafauna in images is labor-intensive and therefore, this organism size class is often neglected in ecosystem studies. Automated image analysis has been proposed as a possible approach to such analysis, but the heterogeneity of megafaunal communities poses a non-trivial challenge for such automated techniques. Here, the potential of a generalized object detection architecture, referred to as iSIS (intelligent Screening of underwater Image Sequences), for the quantification of a heterogenous group of megafauna taxa is investigated. The iSIS system is tuned for a particular image sequence (i.e. a transect) using a small subset of the images, in which megafauna taxa positions were previously marked by an expert. To investigate the potential of iSIS and compare its results with those obtained from human experts, a group of eight different taxa from one camera transect of seafloor images taken at the Arctic deep-sea observatory HAUSGARTEN is used. The results show that inter- and intra-observer agreements of human experts exhibit considerable variation between the species, with a similar degree of variation apparent in the automatically derived results obtained by iSIS. Whilst some taxa (e. g. Bathycrinus stalks, Kolga hyalina, small white sea anemone) were well detected by iSIS (i. e. overall Sensitivity: 87%, overall Positive Predictive Value: 67%), some taxa such as the small sea cucumber Elpidia heckeri remain challenging, for both human observers and iSIS