Gulf of Mexico regional ocean model at 5km horizontal resolution assimilating satellite and float data with Ensemble Kalman Filter (EnKF) from 2010-04-01 to 2010-10-01
Funded By:
Gulf of Mexico Research Initiative
Funding Cycle:
RFP-V
Katja Fennel
Dalhousie University / Department of Oceanography
Katja.Fennel@Dal.Ca
circulation model, data assimilation, physical ocean fields, Regional Ocean Modelling System (ROMS), localized Ensemble Kalman Filter (EnKF), modeled sea surface height (SSH), modeled temperature, modeled salinity, modeled velocity fields
Abstract:
Accurate estimates of ocean circulation are essential for hindcasting and predicting the transport of the pollutants, assessing their environmental impacts, and managing response efforts. A standard method for improving ocean simulations and predictions is data assimilation, which combines observations and dynamical models to obtain more accurate estimates. This dataset represents such a combined estimate and was generated from a data-assimilative circulation model (horizontal resolution ~5 km) of the Gulf of Mexico (GOM). The circulation model is a configuration of the Regional Ocean Modelling System (ROMS, http://myroms.org) for the entire GOM, initialized on 1 April 2010 and run until 1 October 2010. Satellite and float data were assimilated using a localized Ensemble Kalman Filter (EnKF). Observations assimilated into the model include Sea Level Anomaly (SLA) from AVISO (Archiving Validation and Interpretation of Satellite Oceanographic Data, http://www.aviso.oceanobs.com/), 1/4° SST from the AVHRR (Advanced Very High-Resolution Radiometer, http://marine.copernicus.eu/), and temperature and salinity profiles from Shay et al., 2011. Daily ensemble means model outputs of sea surface height (SSH), temperature, salinity and velocity fields during April to September 2010 are generated and archived in this dataset. This dataset consists of four NetCDF files containing the model physical daily assembles, a model grid file, and the model's 7-years mean SSH (considered as the model’s mean dynamic topography) that was added to the satellite Sea Level Anomaly for assimilation and comparison. This dataset supports the publication (submitted to Journal of Geophysical Research: Oceans). Yu, L., Fennel, K., Wang, B., Laurent, A., Thompson, K. and Shay, L. EnKF-based data assimilation improves simulated circulation in the Gulf of Mexico but does it benefit the simulation of deep-water oil plumes?
Suggested Citation:
Liuqian Yu, Katja Fennel, Bin Wang, Arnaud Laurent, Keith R. Thompson and Lynn K. Shay. 2019. Gulf of Mexico regional ocean model at 5km horizontal resolution assimilating satellite and float data with Ensemble Kalman Filter (EnKF) from 2010-04-01 to 2010-10-01. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/n7-zc10-mz49
Purpose:
An ability to accurately simulate and predict circulation at depth is crucial in the event of deep-water oil spills like the 2010 Deepwater Horizon (DWH) disaster. Data assimilation (DA), i.e. the incorporation of observations into dynamical models, is a standard method for ocean prediction and reanalysis. Toward that objective, a localized Ensemble Kalman Filter (EnKF) assimilation technique was implemented in a three-dimensional circulation model (horizontal resolution ~5 km) of the Gulf of Mexico (GOM) to assimilate satellite and float data and generated this dataset.
Data Parameters and Units:
Daily model ensembles (gom_ensmean_0001.nc to gom_ensmean_0004.nc): ocean_time (seconds since 1858-11-17 00:00:00), zeta (free surface elevation, m) u (u-momentum component, m/s), v (v-momentum component, m s-1), temp (potential temperature, degrees C), salt (salinity, PSU). File “GOM_model_grid.mat”: angle (angle between XI-axis and EAST, radians), pm (curvilinear coordinate metric in XI, m-1), pn (curvilinear coordinate metric in ETA, m-1), F (Coriolis parameter at RHO-points, s-1), H (model bathymetry at RHO-points, m), x_rho (X-location of RHO-points, m), y_rho (Y-location of RHO-points, m), x_psi (X-location of PSI-points, m), y_psi (Y-location of PSI-points, m), x_u (X-location of U-points, m), y_u (Y-location of U-points, m), x_v (X-location of V-points, m), y_v (Y-location of V-points, m), lon_rho (longitude of RHO-points, degrees E), lat_rho (latitude of RHO-points, degrees N), lon_psi (longitude of PSI-points, degrees E), lat_psi (latitude of PSI-points, degrees N), lon_u (longitude of U-points, degrees E), lat_u (latitude of U-points, degrees N), lon_v (longitude of V-points, degrees E), lat_v (latitude of V-points, degree_north), mask_rho (mask on RHO-points, value 0 means land and 1 water, nondimensional), mask_rho_nan (mask on RHO-points, value NaN means land and 1 water, nondimensional, (mask_psi, mask on PSI-points, value 0 means land and 1 water, nondimensional), mask_u (mask on U-points, value 0 means land and 1 water, nondimensional), mask_v (mask on V-points, value 0 means land and 1 water, nondimensional), zeta (free surface elevation at RHO-points, m), z_r (actual depths of variables at RHO-points, negative downwards, m), z_w (actual depths of variables at W-points, negative downwards, m), theta_s (S-coordinate surface stretching parameter, nondimensional), theta_b (S-coordinate bottom stretching parameter, nondimensional), Tcline (S-coordinate surface/bottom layer width, m), hc (S-coordinate parameter, critical depth, m), N (number of vertical terrain-following levels at RHO-points, nondimensional), sc_w (S-coordinate at W-points, nondimensional), Cs_w (S-coordinate stretching curves at W-points, nondimensional), sc_r (S-coordinate at RHO-points, nondimensional), Cs_r (S-coordinate stretching curves at RHO-points, nondimensional), s_w (S-coordinate at W-points, nondimensional), s_rho (S-coordinate at RHO-points, nondimensional). File “Mean_Dynamic_Topography_2010-2016modelrun_SSH_mean.mat”: zeta_avg (7-year averaged model free surface elevation based on free model run’s daily outputs from 2010 to 2016, m).
Provenance and Historical References:
Shay, L. K., B. Jaimes, J. Brewster, P. Meyers, C. McCaskill, E. Uhlhorn, F. Marks, G. R. Halliwell Jr., O.-M. Smedstad, and P. Hogan (2011). Airborne Ocean Surveys of the Loop Current Complex From NOAA WP-3D in Support of the Deepwater Horizon Oil Spill. Geophysical Monograph Series, 131–151. doi:10.1029/2011gm001101