Code as is depends on user manually downloading data and unzipping it to data/raw folder. Whether using manual download method or using amerifluxr package, you must be first registered with Ameriflux as a data user (they like to know how their data is being used + who is using it). Because registration is required either way, I shied away from using amerifluxr initially because of the risk of packages/functions not being maintained long-term or deprecated (i.e., code breaks) and I've also run into function wonkiness with using R packages a user be registered in a third party (e.g., with token authorization). BUT, in hindsight, reading dynamically might make Sarah + helpers lives easier when running this workflow each year.
Data that need to be fetched:
[ ] US-NR1 (Forest, near C1; Peter Blanken = PI; precip and temp available + other met data, temp has multiple sensors; completely infilled record available if needed, e.g., to assess possible artificial breaks or drifts in NWT time series)
[ ] US-NR3 (Tvan West tower; John Knowles = PI; no precip available)
[ ] US-NR4 (Tvan East tower; John Knowles = PI; no precip available)
milesalanmoore
commented
3 months ago
Code as is depends on user manually downloading data and unzipping it to data/raw folder. Whether using manual download method or using amerifluxr package, you must be first registered with Ameriflux as a data user (they like to know how their data is being used + who is using it). Because registration is required either way, I shied away from using amerifluxr initially because of the risk of packages/functions not being maintained long-term or deprecated (i.e., code breaks) and I've also run into function wonkiness with using R packages a user be registered in a third party (e.g., with token authorization). BUT, in hindsight, reading dynamically might make Sarah + helpers lives easier when running this workflow each year.
Data that need to be fetched: