Therm wind

.gitignore

@@ -4,3 +4,4 @@ _templates
 *.ipynb_checkpoints*
 /Tutorials_as_Jupyter_Notebooks/.ipynb_checkpoints/*
 .README.md.swp
+/ECCO-ACCESS/Downloading_ECCO_Datasets_from_PODAAC/~/

ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/Tutorial_Python3_Jupyter_Notebook_Downloading_ECCO_Datasets_from_PODAAC.ipynb

@@ -5,11 +5,11 @@
    "id": "d8999184",
    "metadata": {},
    "source": [
-    "# Tutorial Python 3 Notebook for Downloading ECCO Datasets from PO.DAAC\n",
+    "# Using Python to Download ECCO Datasets\n",
     "\n",
-    "**Note: This notebook is modified from the tutorial on the [ECCO-GROUP Github](https://github.com/ECCO-GROUP/ECCO-ACCESS/blob/master/PODAAC/Downloading_ECCO_datasets_from_PODAAC/Tutorial_Python3_Jupyter_Notebook_Downloading_ECCO_Datasets_from_PODAAC.ipynb) by Jack McNelis and Ian Fenty, Version 1.1 dated 2021-06-25.**\n",
+    "**Note: This notebook was modified by Andrew Delman (updated 2022-12-15) from the tutorial on the [ECCO-GROUP Github](https://github.com/ECCO-GROUP/ECCO-ACCESS/blob/master/PODAAC/Downloading_ECCO_datasets_from_PODAAC/Tutorial_Python3_Jupyter_Notebook_Downloading_ECCO_Datasets_from_PODAAC.ipynb) by Jack McNelis and Ian Fenty, Version 1.1 dated 2021-06-25.**\n",
     "\n",
-    "This notebook provides instructions for downloading a set of granules (files) for an ECCO \"Dataset\" hosted by PO.DAAC. The focus is on downloading datasets in the lat-lon-cap 90 (llc90) native grid of the ECCO v4 simulations, since the tutorials mostly use output on the native grid. If you're new to this grid geometry, don't worry! The ecco_v4_py package discussed in the previous tutorial will help you load the ECCO output, make computations, and plot the results while hardly needing to interact with the model grid.\n",
+    "This Jupyter notebook provides instructions and Python code for downloading a set of granules (files) for an ECCO \"Dataset\" hosted by PO.DAAC. The focus is on downloading datasets in the lat-lon-cap 90 (llc90) native grid of the ECCO v4 simulations, since the tutorials mostly use output on the native grid. If you're new to this grid geometry, don't worry! The ecco_v4_py package discussed in the previous tutorial will help you load the ECCO output, make computations, and plot the results while hardly needing to interact with the model grid.\n",
     "\n",
     "The example ECCO Dataset used in this tutorial is \"ECCO Sea Surface Height - Daily Mean llc90 Grid (Version 4 Release 4)\" which provides daily mean sea surface height on the native llc90 grid ([10.5067/ECL5D-SSH44](https://doi.org/10.5067/ECL5D-SSH44)). \n",
     "\n",
@@ -925,7 +925,7 @@
     "\n",
     "[**ecco_download** module](../../ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/ecco_download.py)\n",
     "\n",
-    "You can save this file either in the same directory where you store the tutorial notebooks, or a different directory that you then add to your path using sys.path.append. The syntax for using this module will be discussed in the next tutorial (Geostrophic Balance)."
+    "You can save this file either in the same directory where you store the tutorial notebooks, or a different directory that you then add to your path using sys.path.append. You can see the syntax of how the module is used in upcoming tutorials."
    ]
   }
  ],

ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/Tutorial_wget_Command_Line_HTTPS_Downloading_ECCO_Datasets_from_PODAAC.md

@@ -1,4 +1,4 @@
-# Tutorial: Using Command Line _wget_ to Download ECCO Datasets from PO.DAAC
+# Using _wget_ to Download ECCO Datasets from PO.DAAC
 
 Version 1.0 2021-06-25
 
@@ -91,4 +91,4 @@ $wget --no-verbose \
      --no-clobber \
      --continue \
      -i 5237392644-download.txt -P data/
-```
+```

Intro_to_PO_Tutorials/ecco_download.py

@@ -0,0 +1 @@
+../ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/ecco_download.py

Intro_to_PO_Tutorials/geos_vel.py

@@ -0,0 +1,78 @@
+def geos_vel_compute(dens_press_filename,grid_filename="~/Downloads/ECCO_V4r4_PODAAC/ECCO_L4_GEOMETRY_LLC0090GRID_V4R4/GRID_GEOMETRY_ECCO_V4r4_native_llc0090.nc",fc_filename="llc_13tile_fc.txt"):
+    """
+    This routine computes geostrophic velocities from an input netCDF file containing ECCO v4r4 density and pressure anomalies on the native llc90 grid.
+
+    Parameters
+    ----------
+    dens_press_filename: the name (including path if not in current directory) of the netCDF file containing the density and pressure anomalies
+
+    grid_filename: the name (including path if not in current directory) of the netCDF file containing the latitudes ('YC') and grid parameters ('dxC','dyC') needed to compute horizontal derivatives
+
+    fc_filename: text file containing a Python dictionary specifying the tile/face connections in the ECCO llc90 grid
+    """
+
+    import numpy as np
+    import xarray as xr
+    import json
+    import xgcm
+
+    # load file into workspace
+    ds_denspress = xr.open_dataset(dens_press_filename, data_vars='minimal',\
+                                     coords='minimal', compat='override')
+
+    densanom = ds_denspress.RHOAnoma
+
+    rhoConst = 1029.
+    dens = rhoConst + densanom
+
+    pressanom = ds_denspress.PHIHYDcR
+
+
+    # load grid parameters file
+    ds_grid = xr.open_dataset(grid_filename)
+
+
+    # load face_connections dictionary
+
+    # read in as string
+    with open(fc_filename) as fc:
+        data = fc.read()
+    # convert string to dictionary
+    face_connections = json.loads(data)
+
+
+    # create xgcm Grid object
+    grid = xgcm.Grid(ds_grid,periodic=False,face_connections=face_connections)
+
+    # compute derivatives of pressure in x and y
+    d_press_dx = (grid.diff(rhoConst*pressanom,axis="X",boundary='extend'))/ds_grid.dxC
+    d_press_dy = (grid.diff(rhoConst*pressanom,axis="Y",boundary='extend'))/ds_grid.dyC
+
+    # interpolate (vector) gradient values to center of grid cells
+    press_grads_interp = grid.interp_2d_vector({'X':d_press_dx,'Y':d_press_dy},boundary='extend')
+    dp_dx = press_grads_interp['X']
+    dp_dy = press_grads_interp['Y']
+
+    # compute f from latitude of grid cell centers
+    lat = ds_grid.YC
+    Omega = (2*np.pi)/86164
+    lat_rad = (np.pi/180)*lat    # convert latitude from degrees to radians
+    f = 2*Omega*np.sin(lat_rad)
+
+    # compute geostrophic velocities
+    v_g = dp_dx/(f*dens)
+    u_g = -dp_dy/(f*dens)
+
+    # assign attributes to DataArrays (names) and units
+    u_g.name = 'u_g'
+    u_g.attrs.update({'long_name': 'Geostrophic velocity in model-x direction',\
+                      'units': 'm s-1'})
+    v_g.name = 'v_g'
+    v_g.attrs.update({'long_name': 'Geostrophic velocity in model-y direction',\
+                      'units': 'm s-1'})
+
+    # create xarray Dataset containing geostrophic velocities
+    ds_geos_vel = u_g.to_dataset(name='u_g',promote_attrs=True)
+    ds_geos_vel['v_g'] = v_g
+
+    return ds_geos_vel

Intro_to_PO_Tutorials/llc_13tile_fc.txt

@@ -0,0 +1 @@
+{'tile': {0: {'X': ((12, 'Y', False), (3, 'X', False)), 'Y': (None, (1, 'Y', False))}, 1: {'X': ((11, 'Y', False), (4, 'X', False)), 'Y': ((0, 'Y', False), (2, 'Y', False))}, 2: {'X': ((10, 'Y', False), (5, 'X', False)), 'Y': ((1, 'Y', False), (6, 'X', False))}, 3: {'X': ((0, 'X', False), (9, 'Y', False)), 'Y': (None, (4, 'Y', False))}, 4: {'X': ((1, 'X', False), (8, 'Y', False)), 'Y': ((3, 'Y', False), (5, 'Y', False))}, 5: {'X': ((2, 'X', False), (7, 'Y', False)), 'Y': ((4, 'Y', False), (6, 'Y', False))}, 6: {'X': ((2, 'Y', False), (7, 'X', False)), 'Y': ((5, 'Y', False), (10, 'X', False))}, 7: {'X': ((6, 'X', False), (8, 'X', False)), 'Y': ((5, 'X', False), (10, 'Y', False))}, 8: {'X': ((7, 'X', False), (9, 'X', False)), 'Y': ((4, 'X', False), (11, 'Y', False))}, 9: {'X': ((8, 'X', False), None), 'Y': ((3, 'X', False), (12, 'Y', False))}, 10: {'X': ((6, 'Y', False), (11, 'X', False)), 'Y': ((7, 'Y', False), (2, 'X', False))}, 11: {'X': ((10, 'X', False), (12, 'X', False)), 'Y': ((8, 'Y', False), (1, 'X', False))}, 12: {'X': ((11, 'X', False), None), 'Y': ((9, 'Y', False), (0, 'X', False))}}}

doc/Downloading_ECCO_Datasets_from_PODAAC_Python.ipynb

@@ -0,0 +1 @@
+../ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/Tutorial_Python3_Jupyter_Notebook_Downloading_ECCO_Datasets_from_PODAAC.ipynb

doc/Downloading_ECCO_Datasets_from_PODAAC_wget.md

@@ -0,0 +1 @@
+../ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/Tutorial_wget_Command_Line_HTTPS_Downloading_ECCO_Datasets_from_PODAAC.md

doc/Geostrophic_balance.ipynb

@@ -0,0 +1 @@
+../Intro_to_PO_Tutorials/Geostrophic_balance.ipynb

doc/Thermal_wind.ipynb

@@ -0,0 +1 @@
+../Intro_to_PO_Tutorials/Thermal_wind.ipynb

doc/conf.py

@@ -91,9 +91,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = u'4.3-20191128'
+version = u'4.4-20221215'
 # The full version, including alpha/beta/rc tags.
-release = u'4.3-20191128'
+release = u'4.4-20221215'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

doc/index.rst

@@ -29,6 +29,8 @@ The `ecco_v4_py`_ package used in this tutorial was inspired by the `xmitgcm`_ p
    fields
    Installing_Python_and_Python_Packages
    Downloading_the_ECCO_v4_state_estimate
+   Downloading_ECCO_Datasets_from_PODAAC_Python.ipynb
+   Downloading_ECCO_Datasets_from_PODAAC_wget.md
    Tutorial_Introduction
 
 .. toctree::
@@ -68,6 +70,13 @@ The `ecco_v4_py`_ package used in this tutorial was inspired by the `xmitgcm`_ p
 
    ECCO_v4_Example_calculations_with_scalar_quantities.ipynb
 
+.. toctree::
+   :maxdepth: 2
+   :caption: Intro to PO Tutorials
+
+   Geostrophic_balance.ipynb
+   Thermal_wind.ipynb
+
 .. toctree::
    :maxdepth: 2
    :caption: More Advanced Calculations