Global map of the M2-tidal conversion into modes 1⁠ – ⁠5 by continental margins

Gaspard Geoffroy

This dataset is a global map of the barotropic-to-baroclinic tidal conversion rate at continental slopes and shelves for the first five modes of the M2 constituent (the largest lunar constituent of the tides). The method used to compute the conversion rate (or baroclinic energy flux) resolves the onshore and offshore fluxes. The horizontal direction of the computed fluxes is estimated from the normal to the slope.

Such modally decomposed, anisotropic energy flux estimate is valuable to predict the propagation and, ultimately, the dissipation of internal tides generated at continental margins. The diapycnal mixing that results from the breaking of these internal waves is known to have wide implications on the ocean state, and therefore on our climate system.

The data takes the form of a collection of polygons (representing small slices of the global continental slopes) each associated with an energy flux. The energy flux was calculated using a semi-analytical method that relies on global observations of the bathymetry, barotropic tidal transports, and stratification.

Citation

Gaspard Geoffroy (2024) Global map of the M2-tidal conversion into modes 1⁠ – ⁠5 by continental margins. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/geoffroy-2024-slopit-1

References

Egbert GD, Erofeeva SY (2002) Efficient inverse modeling of barotropic ocean tides. Journal of Atmospheric and Oceanic Technology 19:183–204. https://doi.org/10.1175/1520-0426(2002)019%3C0183:EIMOBO%3E2.0.CO;2

Gouretski V, Koltermann KP (2004) WOCE global hydrographic climatology. Berichtedes BSH, 35, 1–52.

NASA Ocean Biology Processing Group (OBPG), Stumpf RP (2012) Distance to Nearest Coastline: 0.01-Degree Grid. Distributed by the Pacific Islands Ocean Observing System (PacIOOS).

Kelly SM, Jones NL, Nash JD (2013) A coupled model for Laplace’s tidal equations in a fluid with one horizontal dimension and variable depth. Journal of Physical Oceanography 43:1780–1797. https://doi.org/10.1175/jpo-d-12-0147.1

Harris PT, Macmillan-Lawler M, Rupp J, Baker EK (2014) Geomorphology of the oceans. Marine Geology 352:4–24. https://doi.org/10.1016/j.margeo.2014.01.011

GEBCO Bathymetric Compilation Group 2023 (2023) The GEBCO_2023 Grid - a continuous terrain model of the global oceans and land. https://doi.org/10.5285/f98b053b-0cbc-6c23-e053-6c86abc0af7b

Geoffroy G, Kelly SM, Nycander J (2024) Tidal conversion into vertical normal modes by continental margins. Geophysical Research Letters. [Manuscript under review].

Geoffroy G (2024) Scripts for mapping the tidal conversion by continental margins. Software version 1.0.0. Bolin Centre Code Repository. https://doi.org/10.57669/geoffroy-2024-slopit-1.0.0

Data description

This dataset is composed of two main files:

• The slope_poly.zip archive contains a collection of slices (polygons) of the global continental slopes, in geographical and projected coordinates, written in the standard ESRI Shapefile format.
• The M2conv_m5_margins.nc netCDF file contains the barotropic-to-baroclinic tidal conversion rate for the first five modes of the M2 constituent associated with each slice, C, along with different variables related to the geometry of the slice, computed following Geoffroy et al. (2024).

In both files, slices are referenced using an unique identifier labeled FID. The phase and direction of the energy flux are given by the ph and ang variables, respectively, while the partitioning between the offshore and on-shelf fluxes is embedded in the Ndir dimension in M2conv_m5_margins.nc.

Comments

This dataset was produced by using the Scripts for mapping the tidal conversion by continental margins by Geoffroy (2024). The computations are based on the semi-analytical method described in Geoffroy et al. (2024). Please cite the latter article when using this dataset and contact the corresponding author Gaspard Geoffroy for any scientific or data-related questions.

The semi-analytical method uses different observational data as inputs, including:

• the barotropic tidal elevations and transports from the inverse model TPXO-atlas-v5 (Egbert & Eerofeva 2002)
• the WOCE/Argo climatology of Gouretski & Koltermann (2004)
• the bathymetry from GEBCO Bathymetric Compilation Group 2023 (2023)
• the distance to the nearest coastline dataset of NASA Ocean Biology Processing Group (OBPG) & Stumpf (2012)
• the geomorphic data of Harris et al. (2014).

The computations of the tidal conversion are done using the CELT model (Kelly et al. 2013).