Traditionally, what we would do is to go to a data hosting service such as Earthdata Search and search for the exact file. While this approach works for this project, there are several drawbacks for a general data-search case:
It is hard to reproduce the data query process using these services. Researchers might be confused by the complexity of the website and struggle to find the right data.
Not every data hosting sites provide the bulk access/download service. If not, retrieve large volume of data from them is time-consuming and requires manual and frequent checks.
This step is often disconnected from the following data processing, which means extra efforts for researchers to check and assimilate their data.
Tools in the Jupyter ecosystem (here Icepyx) can mitigate these issues as they are executed on a Jupyter Notebook. So all the data query and download steps can be scripted and documented. As we continue to use Notebook, accessing data can better connect to the rest of the research stages.
Download the ICESat-2 granule we need.