Proposed Recipes for Daymet

[TomAugspurger]

Dataset Name

Daymet

Dataset URL

https://daymet.ornl.gov/

Description

Daymet provides long-term, continuous, gridded estimates of daily weather and climatology variables by interpolating and extrapolating ground-based observations through statistical modeling techniques. The Daymet data products provide driver data for biogeochemical terrestrial modeling and have myriad applications in many Earth science, natural resource, biodiversity, and agricultural research areas. Daymet weather variables include daily minimum and maximum temperature, precipitation, vapor pressure, shortwave radiation, snow water equivalent, and day length produced on a 1 km x 1 km gridded surface over continental North America and Hawaii from 1980 and over Puerto Rico from 1950 through the end of the most recent full calendar year.

It's one of the more popular NASA datasets.

This will likely be 9 separate recipes, one for each of the 3 regions (North America, Puerto Rico, Hawaii) and 3 temporal frequencies (daily, monthly, and annual).

I hear from @sharkinsspatial that some others might be interested, so I'm sharing my WIP recipes at https://github.com/TomAugspurger/daymet-recipe. I ran into some slow performance issues on the NA-daily recipe that I haven't debugged yet.

License

https://science.nasa.gov/earth-science/earth-science-data/data-information-policy

Data Format

NetCDF

Data Format (other)

No response

Access protocol

HTTP(S)

Source File Organization

Each region (NA, PR, HI) is completely independent.

For each frequency (daily, monthly, yearly) there's a single file per year. The number of time steps per file depends on the frequency (daily=365, monthly=12, yearly=1)

There's several variables (prcp, tmax, ...), all with the same coordinates / dimensions.

Example URLs

https://thredds.daac.ornl.gov/thredds/fileServer/ornldaac/1855/daymet_v4_prcp_monttl_hi_1980.nc

Authorization

No response

Transformation / Processing

Combine the variables and concatenate along time.

Target Format

Zarr

Comments

https://github.com/TomAugspurger/daymet-recipe/blob/main/recipe.py has my work in progress. Azure specific storage for now, but can be generalized.