v9.1
Tools for simulating drifters given gridded vector data, such as from oceanographic HF radar data. Use of this code has resulted in at least two papers, which are cited below. Improvements developed for Matson et al. (2019), which includes error estimation, are not yet included here. Otherwise the toolbox includes:
- Use of 4th order Runge-Kutta for accurate integration of discrete velocities.
- Optional settings to simulate subgrid turbulence.
- Dependencies in the /private folder. Also see the note about the use of code folding and subfunctions.
HOW TO USE IT Download it and add the unzipped directory to your MATLAB path.
Run the example:
% EXAMPLE:
% Load TUV data in the HFRProgs TUV format (see test_data folder)
load ./test_data/drifter_simulation.mat TUV
% create drifter deployment location and time arrays:
dstart = pacific2GMT(datenum(2015,5,20,11,0,0));
xy = [-120-10.68/60 34+25.38/60
-120-09.12/60 34+26.22/60
-120-09.42/60 34+27.30/60
-120-08.58/60 34+26.52/60
-120-06.03/60 34+27.67/60
-120-06.03/60 34+27.67/60];
% Deploy a drifter at these locations at every time step in the TUV data:
% (These basically just need to have the same number of rows)
CFG.deploy_locations = repmat(xy,length(TUV.TimeStamp),1);
CFG.deploy_times = reshape( TUV.TimeStamp(:)*ones(1,size(xy,1)), numel(TUV.TimeStamp(:)*ones(1,size(xy,1))),1);
% Now run the code:
DRFT = drifter_simulation(TUV, CFG);
More details in the 'test_case' subfunction.
AUTHORS
Brian Emery
Krisada Letcherononguong
Kirk Ireson
Chris Gotschalk
Carter Ohlmann
Libe Washburn
ACKNOWLEDGMENT
The development of this software was made possible in part through support from the National Science Foundation under Grant OCE-0352187 and the Minerals Management Service, U.S. Department of Interior under MMS Agreement 1435-01-00-CA-31063 to 18212. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. government.
REFERENCES
Ohlmann, J. C., J. H. LaCasce, L. Washburn, A. J. Mariano, and B. Emery, 2012, Relative dispersion observations and trajectory modeling in the Santa Barbara Channel, J. Geophys. Res., 117, C05040, doi:10.1029/2011JC007810.
Matson, Paul G., L. Washburn, E. A. Fields, C. Gotschalk, T. M. Ladd, D. A. Siegel, Z. S. Welch, and M. D. Iglesias‐Rodriguez. "Formation, development, and propagation of a rare coastal coccolithophore bloom." Journal of Geophysical Research: Oceans 124, no. 5 (2019): 3298-3316.
NOTES
- .m files use functions as blocks of code, so code folding (for example using the keyboard shortcut 'cmd =' ) makes it easy to move among these.
- Data structures contain variables of similar origin following the HFRProgs convention, rows = locations, cols = time
HOW TO CITE
@misc{Emery2018code,
author = {Emery, Brian and Letcherononguong, Krisada and Ireson, Kirk and Gotschalk, Chris and Ohlmann, Carter and Washburn, Libe},
title = {{Drifter Simulation Toolbox for MATLAB}, Software Release Version 9.0, https://doi.org/10.5281/zenodo.3350830},
version = {9.0},
month = Jul,
year = 2019,
doi = {10.5281/zenodo.3350830},
url = {https://doi.org/10.5281/zenodo.3350830}
}
EXAMPLE OUTPUT
Based on the test data, drifter positions as green dots, final positions as blue dots.
