christianhart2019 / snotel_datacomparision

Compare the output from QC and gap-filling procedures

This workflow is designed to catch errors and any discrepencies in my data handling and quality control procedures.

Background

I was having trouble finding where my SUMMA setup for department of energy snoTEL data was having a problem. After I spent a fair amount of time trying to debug this, it was recommended that I compare the forcing data from previous working setups I’ve created.

Objectives

1. Narrow down where potential errors might occur within my current forcing file.
2. Create a statistical comparison of the different QC methods used for snoTEL data sources.
3. This will later be presented to an academic group who is beginning work on similar methodology.

Research Methods and Proposed Approach

1. Consolidate past and present forcing files into a desktop folder.
2. Create python notebook to open and compare various forcing variables from different snoTEL sites. Calculate some statistics and plot results across space.
3. Also find where differences between data sets are the greatest and possibly try to investigate why this might be.

Anticipated Results and Significance

Hopefully find where I’m incurring error in forcing file. Get a better idea of the relevance and value of QC procedures. Help others learn about this too.