About SURF

The SURF platform enables you to easily and quickly create your own high-resolution limited area, nested ocean models.

This is the repository of an the Relocatable Ocean Modeling platform knwn as SURF, which enables the nesting of NEMO and SHYFEM codes into larger-scale ocean circulation models. SURF is distributed embedded in a Virtual Machine Environment in which the hydrodynamic model and several pre- and post-processing tools will be connected to the required inputs fields and the SURF numerical outputs. SURF has developed pre-processing for bathymetry, initial and lateral boundary conditions, atmospheric and tidal forcing, and it has a specific configuration interface to NEMO and/or SHYFEM namelist parameters. The aim is that this configuration will be part of a web-based graphical user interface, which is currently under construction.

SURF provides a numerical platform for the forecasting of hydrodynamic and thermodynamic fields at high spatial and temporal resolution. It is designed to be embedded in any region of a larger scale ocean prediction system at a coarser resolution. The platform includes approaches based both on multiple nesting with structured grid model NEMO and cross-scale seamless modeling with unstructured grid model SHYFEM. For multiple nesting (with increasing grid resolutions), the platform is capable of reaching horizontal grid resolutions of a few hundred meters. For each nesting, the coarser parent grid model fields provide the initial and lateral boundary conditions for the SURF child components. The cross-scale seamless modeling approach consists of a representation of different scales through a unique-continuum computational grid, from the basin to the shelf-coastal to the near-shore scale, up to the estuaries. The sequential steps executed within the SURF-NEMO numerical platform (as depicted in the image below) can be grouped as follows:

  • Initialization: The user defines the configuration parameters for the preprocessing (such as data source, variables of interest), simulation (such as grids, time step, output frequency, subgrid scale parameterizations), and postprocessing (like data analysis or visualization) of an ocean model in the configuration file (input data location, horizontal and vertical grids, subgrid scale parameterizations, etc).
  • Grid generation: This is an automated step, which generates the bathymetry on the child grid, as well as horizontal and vertical grids for the child model.
  • Input data regridding: This is an automated step, which generates the surface atmospheric forcing, the initial and open lateral boundary conditions datasets on the child grid.
  • Forecast: Another automated step, which produces the final downscaled model outputs based on the configured parameters.
  • Post-processing: In this step, visualization and analysis procedures for the parent-child model forecast are considered. These procedures can be activated after the run execution and may involve tasks such as comparing parent/child fields, validating model results with in-situ or satellite datasets, and converting datasets for further analysis.

The following diagram illustrates the data flow and task dependencies within the platform.

Configuration File{json}SecA: Parameters forPre-processing andSimulation TasksDATA SOURCESCoastline{shp}Bathymetry{netCDF}Initial condition fromcoarser-resol. model{netCDF}Lateral OB conditionsfrom coarser-resol model{netCDF}AtmosphericForcing{netCDF}TidalForcing{netCDF}PRE-PROCESSINGCHILD MESH GENERATIONBathymetryRemap+ManipChild-3DMeshGeneration1REMAPPING2InitialCondition2aLateral bound.Condition2bAtmosphericForcing2cTidalForcing2dDATA NORMALIZATIONOCEAN SIMULATION(NEMO / SHYFEM)3
Configuration File{json}SecB: Parameters forVisualization and DataAnalysisDATA SOURCESINPUTOUTPUTREGRIDDEDOBSERVATIONsPOST-PROCESSINGVisualize the input,regridded, output dataCompare parentVS child fieldsOutput formatconversionValidation of themodel data with obs