Merge pull request #81 from andrewdelman/ecco_download_20240725

fixed broken links to ecco_download.py module

Author: andrewdelman

ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/Tutorial_Python3_Jupyter_Notebook_Downloading_ECCO_Datasets_from_PODAAC.ipynb

@@ -9,7 +9,7 @@
     "\n",
     "**Note: This notebook was modified by Andrew Delman (updated 2024-07-11) 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 Jupyter notebook provides an introduction to the Python [ecco_download module](https://raw.githubusercontent.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/master/ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/ecco_download.py), with 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",
+    "This Jupyter notebook provides an introduction to the Python [ecco_download module](https://raw.githubusercontent.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/master/ECCO-ACCESS/ecco_download.py), with 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",
@@ -120,7 +120,7 @@
     "\n",
     "If you are already broadly familiar with Python and want a quick way to download ECCO output, and have edited your `netrc` file as described [above](#Earthdata-Login-Requirements), you can use the `ecco_download` module.\n",
     "\n",
-    "[ecco_download module](https://raw.githubusercontent.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/master/ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/ecco_download.py)\n",
+    "[ecco_download module](https://raw.githubusercontent.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/master/ECCO-ACCESS/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`. Then import it to your code using `from ecco_download import *` and call the function `ecco_podaac_download` to start downloading. You will need to know the ShortName of the dataset you want, which you can look up using the variable lists [linked above](#Dataset-ShortNames-and-variables-associated-with-them). To see the syntax of the `ecco_podaac_download` function use `help(ecco_podaac_download)`, or consider the example below where we download daily SSH data for the week 2000-01-08 to 2000-01-14 inclusive:"
    ]