Dataset: Relative Particle Density (RPD) calculations using High Frequency Radar (HFR) observed surface currents around Palmer Deep Canyon from January to March of 2020

Final no updates expectedDOI: 10.26008/1912/bco-dmo.917926.1Version 1 (2024-01-08)Dataset Type:Other Field Results

Principal Investigator: Joshua Kohut (Rutgers University)

Co-Principal Investigator: John M. Klinck (Old Dominion University)

Co-Principal Investigator: Matthew Oliver (University of Delaware)

Co-Principal Investigator: Hank Statscewich (Rutgers University)

Student: Jacquelyn Veatch (Rutgers University)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)


Project: Collaborative Research: Physical Mechanisms Driving Food Web Focusing in Antarctic Biological Hotspots (Project SWARM)


Abstract

Relative Particle Density (RPD) reports the position of drifters at a single timestamp by normalizing the density of drifters within a gridded bin system in the study field. Relative Particle Density calculations begin with releasing virtual particles over a regular grid and tracking them through a velocity field (High Frequency Radar observed surface currents). RPD is then quantified by summing the number of drifters in each grid box, and normalizing by the median number of drifters in all grid...

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Methods for these LCS results can be found in Veatch, et al. (2024, in revision).

Relative Particle Density provides the normalized density of drifters within each gridded bin of the study system. Relative Particle Density calculations begin with tracking virtual particles through a velocity field that are released over a regular grid. RPD is calculated by summing the number of drifters in each grid box, and normalizing by the median number of drifters in all grid boxes. In the following analysis, new particles were released in a regular grid across the 80 % coverage of the HFR footprint every three hours. Particles were not counted until they had been advected in the velocity field for 6 hours (when the autocorrelation of the HFR velocities cross the e-fold), and were no longer counted when they were advected out of the HFR domain, or after they became three days old. Given the average residence time of 2 days (Kohut et al., 2018), the three-day threshold was chosen to coordinate with the time phytoplankton will spend in the surface layer of our study domain. This methodology follows that used by (Oliver et al. 2019). RPD reports the normalized number of drifters present in each gridded bin at each timestamp. Two dimensional RPD assumes that no particles are lost from the surface layer due to vertical velocity, meaning that the integrated surface divergence in the x-y plane is assumed to be zero. Therefore, RPD will map the instantaneous concentration of surface associated particles across the entire domain given the evolving surface current fields provided by the HFR.


Related Datasets

IsRelatedTo

Dataset: High Frequency Radar, Palmer Deep
Relationship Description: The "High Frequency Radar, Palmer Deep" dataset provided the observed surface currents (velocity field) from which these Relative Particle Density were calculated from.
Veatch, J., Klinck, J. M., Oliver, M., Statscewich, H., Kohut, J. (2024) High Frequency Radar (HFR) observed surface currents at Palmer Deep Canyon in the coastal ocean west of the Antarctic Peninsula in 2020. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-01-08 doi:10.26008/1912/bco-dmo.917884.1

Related Publications

Results

Veatch, J., Kohut, J., Oliver, M., Statscewich, H., Fredj, E. (2024) Quantifying the role of sub-mesoscale lagrangian transport features in the concentration of plankton in a coastal system ICES JMS, In Revision.
Methods

Okubo, A. (1970). Horizontal dispersion of floatable particles in the vicinity of velocity singularities such as convergences. Deep Sea Research and Oceanographic Abstracts, 17(3), 445–454. https://doi.org/10.1016/0011-7471(70)90059-8
Methods

Oliver, M. J., Kohut, J. T., Bernard, K., Fraser, W., Winsor, P., Statscewich, H., Fredj, E., Cimino, M., Patterson-Fraser, D., & Carvalho, F. (2019). Central place foragers select ocean surface convergent features despite differing foraging strategies. Scientific Reports, 9(1). https://doi.org/10.1038/s41598-018-35901-7
Methods

Veatch, J., Fredj, E., & Kohut, J. (2022). High Frequency Radars as Ecological Sensors: Using Lagrangian Coherent Structures to Quantify Prey Concentrating Features. OCEANS 2022, Hampton Roads. https://doi.org/10.1109/oceans47191.2022.9977356
Methods

Weiss, J. (1991). The dynamics of enstrophy transfer in two-dimensional hydrodynamics. Physica D: Nonlinear Phenomena, 48(2–3), 273–294. https://doi.org/10.1016/0167-2789(91)90088-q