Notebooks that are considered delivered results for the project should go in here.
- download_nsidc.py - Downloads data from the nsidc using file extentions and patterns
The goal is to evaluate the SMP to SSA conversion coefficients presented by Calonne et al. 2020 on the Grand Mesa Dataset.
- Anna Valentine
- Michael Durand
- Robbie Mallet
- Mel Sandells
- Batuhan Osmanoglu
- Micah Johnson
What problem are you going to explore? Provide a few sentences. If this is a technical exploration of software or data science methods, explain why this work is important in a broader context.
Accurate characterisation of snow microstructure is critical for understanding volume scattering from airborne and spaceborne radars and radiometers.
This downloads the profiles found with in the date and site id constraints shown in the which_pit.ipynb notebook.
Warning You must have the .netrc file as described by the NSIDC here on
programmatic access
To download all the SMP profiles taken by the pit for our locations just use
cd scripts/
python download_nsidc.py --just_give_it_to_me smp_sources.txt --output ../data/SMP/Otherwise here is an example to get the data from nsidc using our script using pattern searching and file extensions
cd scripts/
python download_nsidc.py https://n5eil01u.ecs.nsidc.org/SNOWEX/SNEX20_SMP.001/ --file_pattern 1S17_20200208 --file_ext PNT- https://nsidc.org/sites/nsidc.org/files/technical-references/SNEX20_SMP_FieldNotes.xlsx
- Micro-ct came from Michael Durand via CREL
- Are the coefficients provided derived by Neige Colonne and Martin Proksh valid at Grand Mesa?
- Which performs better there?
- If the performance is poor, can recalibrate our own?
- https://github.com/mjsandells/snowmicropyn - contains the implemented Colonne Coefficients.