PO.DAAC is pleased to announce the public release of the Pre-SWOT Level-4 numerical simulation datasets Version 1.0. These datasets contain hourly model outputs subsetted from a global ocean simulation using the MITgeneral circulation model (MITgcm) on a 1/48-degree nominal Lat/Lon-Cap horizontal grid (namely, LLC4320). The MITgcm LLC4320 is a forward simulation progressively spun up from lower resolution products of the Estimating the Circulation & Climate of the Ocean (ECCO) project forced by ECMWF 6-hourly wind and barotropic tides. It has been used in studying global ocean submesoscale (10-50 km) dynamics (e.g., Rocha et al., 2016; Su et al., 2019, Qiu et al., 2019), baroclinic tides (e.g., Savage et al., 2017, Arbic et al., 2018) and SWOT mission support (e.g., Wang et al., 2018). A global model-observation comparison can be found in Yu et al. (2019). A more complete list of LLC4320-relevant references is available in the user guide.
This release includes ten regional subsets with an approximate 4x4-degree lat/lon box area that may host international SWOT calibration and validation activities under international CLIVAR Adopt-A-Crossover (AdAC) consortium. Each dataset comprises a collection of thirteen hourly oceanographic variables on a native 1/48-degree LLC grid. Each dataset includes five 3-D variables (temperature, salinity, and zonal/meridional/vertical velocities) and eight 2-D variables (sea level anomaly, ocean mixed layer thickness, bottom pressure anomaly, net freshwater flux, net heat flux, shortwave radiative flux, net salt flux, and ocean surface wind stress). All datasets are formatted in netCDF-4 and grouped into daily files. The simulation covers a period from 13 September 2011 to 14 November 2012.
These Pre-SWOT datasets are distributed directly from the NASA Earthdata Cloud and are described and discoverable via the PO.DAAC Portal and NASA Earthdata Search with direct access from the following DOIs.
Citation: NASA JPL. 2021. Pre-SWOT Level-4 Hourly MITgcm LLC4320 Native 2km Grid Oceanographic Version 1.0. Ver. 1.0. PO.DAAC, CA, USA. Dataset accessed [YYYY-MM-DD] at https://doi.org/10.5067/PRESW-ASJ10
Arbic, B.K., et al., (2018). A primer on global internal tide and internal gravity wave continuum modeling in HYCOM and MITgcm. In “New Frontiers in Operational Oceanography”, GODAE OceanView, 307-392, https://doi.org/10.17125/gov2018.ch13
Rocha, C., et al., (2016). Mesoscale to submesoscale wavenumber spectra in Drake Passage. Journal of Physical Oceanography, 46(2). https://doi.org/10.1175/JPO-D-15-0087.1
Savage, A. C., Arbic, B. K., Alford, M. H., Ansong, J. K., Farrar, J. T., Menemenlis, D., O’Rourke, A. K., Richman, J. G., Shriver, J. F., Voet, G., Wallcraft, A. J., & Zamudio, L. (2017). Spectral decomposition of internal gravity wave sea surface height in global models. J. Geophys. Res. Ocean., 122. https://doi.org/10.1002/2017JC013009
Su, Z., Torres, H., Klein, P., Thompson, A. F., Siegelman, L., Wang, J., Menemenlis, D., & Hill, C. (2020). High-frequency Submesoscale Motions Enhance the Upward Vertical Heat Transport in the Global Ocean. Journal of Geophysical Research: Oceans. https://doi.org/10.1029/2020JC016544
Torres, H. S., et al., (2018). Partitioning ocean motions into balanced motions and internal gravity waves: A modeling study in anticipation of future space missions. Journal of Geophysical Research: Oceans, 123(11), 8084–8105. https://doi.org/10.1029/2018JC014438
Wang, J., L.-L. Fu, B. Qiu, D. Menemenlis, J. T. Farrar, Y. Chao, A. F. Thompson, and M. M. Flexas, 2018: An Observing System Simulation Experiment for the Calibration and Validation of the Surface Water Ocean Topography Sea Surface Height Measurement Using In Situ Platforms. J Atmos Ocean Tech, 35, 281–297, https://doi.org/10.1175/jtech-d-17-0076.1.
Yu, X., Ponte, A. L., Elipot, S., Menemenlis, D., Zaron, E. D., & Abernathey, R. (2019). Surface Kinetic Energy Distributions in the Global Oceans From a High‐Resolution Numerical Model and Surface Drifter Observations. Geophysical Research Letters, 46(16), 9757–9766. https://doi.org/10.1029/2019gl083074