correcting links to download modules and tutorials

Author: andrewdelman

ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/Tutorial_Python3_Downloading_ECCO_Subsets.ipynb

@@ -21,7 +21,7 @@
     "\n",
     "\\- Time subsetting in non-continuous ranges (e.g., downloading boreal summer files from multiple years)\n",
     "\n",
-    "> Currently the `ecco_download` module is a [standalone download](https://raw.githubusercontent.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/master/ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/ecco_download.py). However, we hope to include it in the `ecco_v4_py` package soon so that it does not need to be downloaded or imported into your workspace separately. Stay tuned!\n",
+    "> Currently the `ecco_download` module is a [standalone download](https://raw.githubusercontent.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/master/ECCO-ACCESS/ecco_download.py). However, we hope to include it in the `ecco_v4_py` package soon so that it does not need to be downloaded or imported into your workspace separately. Stay tuned!\n",
     "\n",
     "## Getting Started\n",
     "\n",

ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/Tutorial_Python3_Jupyter_Notebook_Downloading_ECCO_Datasets_from_PODAAC.ipynb

@@ -7,15 +7,15 @@
    "source": [
     "# Using Python to Download ECCO Datasets\n",
     "\n",
-    "**Note: This notebook was modified by Andrew Delman (updated 2023-12-22) 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 2024-04-04) 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 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",
     "These data can also be accessed directly through [NASA Earthdata search](https://search.earthdata.nasa.gov/search?fpj=ECCO). You will need to set up a NASA Earthdata account if you do not have one already. There is [a nice graphical interface](https://www.ecco-group.org/datasets.htm) to sort through the ECCO datasets available from PO.DAAC.\n",
     "\n",
-    "> Tip: if you are already familiar with Python and ECCO output, and have edited your `netrc` file as described [below](#Earthdata-Login-Requirements), you can download the [ECCO_download](https://raw.githubusercontent.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/master/ECCO-ACCESS/Downloading_ECCO_datasets_from_PODAAC/ecco_download.py) module. 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 [here](https://github.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/tree/master/varlist). To see the syntax of the `ecco_podaac_download` function use `help(ecco_podaac_download)`, or see the end of this tutorial for an example.\n",
+    "> Tip: if you are already familiar with Python and ECCO output, and have edited your `netrc` file as described [below](#Earthdata-Login-Requirements), you can download the [ECCO_download](https://raw.githubusercontent.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/master/ECCO-ACCESS/ecco_download.py) module. 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 [here](https://github.com/ECCO-GROUP/ECCO-v4-Python-Tutorial/tree/master/varlist). To see the syntax of the `ecco_podaac_download` function use `help(ecco_podaac_download)`, or see the end of this tutorial for an example.\n",
     "\n",
     "\n",
     "## Getting Started\n",
@@ -938,7 +938,7 @@
     "\n",
     "If you've made it this far, that means you can now download and plot any available ECCOv4r4 variable on your local machine. Woohoo! But to make it easier in the future, you can also download the following Python module that runs the downloading routines contained in this notebook.\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 you can download using the `ecco_podaac_download` function. To see the syntax of how this is used, let's invoke the module to download daily SSH data for the week 2000-01-08 to 2000-01-14:"
    ]

Tutorials_as_Jupyter_Notebooks/ECCO_v4_Salt_and_salinity_budget.ipynb

@@ -349,7 +349,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now we can use [wget](https://github.com/ECCO-GROUP/ECCO-ACCESS/blob/master/PODAAC/Downloading_ECCO_datasets_from_PODAAC/Tutorial_wget_Command_Line_HTTPS_Downloading_ECCO_Datasets_from_PODAAC.md) to download the list of files in *etan_snaps_filenames.txt* and *salt_snaps_filenames.txt*, e.g., wget --no-verbose --no-clobber --continue -i etan_snaps_filenames.txt -P ~/Downloads/ECCO_V4r4_PODAAC/ECCO_L4_SSH_LLC0090GRID_SNAPSHOT_V4R4/"
+    "Now we can use [wget](https://ecco-v4-python-tutorial.readthedocs.io/Tutorial_wget_Command_Line_HTTPS_Downloading_ECCO_Datasets_from_PODAAC.html) to download the list of files in *etan_snaps_filenames.txt* and *salt_snaps_filenames.txt*, e.g., wget --no-verbose --no-clobber --continue -i etan_snaps_filenames.txt -P ~/Downloads/ECCO_V4r4_PODAAC/ECCO_L4_SSH_LLC0090GRID_SNAPSHOT_V4R4/"
    ]
   },
   {
@@ -412,7 +412,7 @@
    "source": [
     "### Load monthly mean data \n",
     "\n",
-    "To download these files you can use the [ecco_download](https://ecco-v4-python-tutorial.readthedocs.io/Downloading_ECCO_Datasets_from_PODAAC_Python.html#ECCO_download-module) module or [wget](https://github.com/ECCO-GROUP/ECCO-ACCESS/tree/master/PODAAC/Downloading_ECCO_datasets_from_PODAAC). The ShortNames of the needed datasets are below."
+    "To download these files you can use the [ecco_download](https://ecco-v4-python-tutorial.readthedocs.io/Downloading_ECCO_Datasets_from_PODAAC_Python.html#ECCO_download-module) module or [wget](https://ecco-v4-python-tutorial.readthedocs.io/Tutorial_wget_Command_Line_HTTPS_Downloading_ECCO_Datasets_from_PODAAC.html). The ShortNames of the needed datasets are below."
    ]
   },
   {