![]() ![]() Let’s load it up again and take a closer look at its coordinates. In the last tutorial we analyzed the contents of a single ECCOv4 file, the 2010 monthly-averaged potential temperature. open_dataset is very convenient because it automatically parses the NetCDF file and constructs a Dataset object using all of the dimensions, coordinates, variables, and metadata information. This tutorial document is current as of Sep 2019 with the ECCOv4 NetCDF grid files provided in the following directories:Īs we showed in the first tutorial, we can use the open_dataset method from xarray to load a NetCDF tile file into Python as a Dataset object. The file you have may look a little different than the ones shown here because we have been working hard at improving how what exactly goes into our NetCDF files. The ECCOv4 files are provided as NetCDF files. Vector calculus in ECCO: The Transport, divergence, vorticity and the Barotropic Vorticity Budget.UNDER CONSTRUCTION: Budget and Vorticity Calculations Compute MOC along the approximate OSNAP array from ECCO.Example calculations with scalar quantities.Interpolating fields from the model llc grid to a regular lat lon grid.Saving Datasets and DataArrays to NetCDF.ECCOv4 Loading llc binary files in the ‘compact’ format.Loading the ECCOv4 state estimate fields on the native model grid.Loading the ECCOv4 native model grid parameters.Input/Output, Data Structure Manipulation Non-Dimension Model Geometry Coordinates.The Dimension Coordinates of the Arakawa C-Grid.The Dimensions and Coordinates of THETA. ![]() Coordinates and Dimensions of ECCOv4 NetCDF files.The Dataset and DataArray objects used in the ECCOv4 Python package.ECCO v4 state estimate ocean, sea-ice, and atmosphere fields.The ECCO Ocean and Sea-Ice State Estimate. ![]()
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