Package developed to assign Daymet climate records to catchments.
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zonalDaymet provides tools to establish a relationship between Daymet daily climate records and user-provided spatial polygons within the R environment. The package gives the user flexibility to index, concatenate, and average climate records in specified locations.

Daymet Data Description

Daily surface weather and climatalogical summaries are provided in netCDF format. Each netCDF mosaic file contains the record for a single variable over 1 year (1980 - present) across a 1 km2 resolution grid over North America. Each point location in the grid, specified by latitude/longitude coordinates, has a climatological time series associated with it for the specified variable in the file. For example, the prcp_1980.nc4 mosaic file contains the daily gridded precipitation record across North America for 1980. In the case of a leap year, the December 31st record is omitted.

Package Usage

The package provides tools to accomplish the following:

  • Download netCDF climate mosaics from the Daymet THREDDS Server
  • Iterate through netCDF files combining time series records and variables into tables
  • Spatially average climate records within user-specified spatial polygons
  • Divide spatial objects into manageable pieces within the R environment to avoid memory issues during spatial averaging
  • Return subsets from the climate mosaics given latitude/longitude coordinate bounds

Functionality is provided to return spatial averages as either a dataframe in the current R environment or write directly to a SQLite database. If a polygon is too small to warrant a spatial average of points, the nearest point is assigned to the polygon. A function is also provided to simplify record selection from the database.

Sample Workflow

The [Sample-Workflow Vignette]( provides a walk-through of the package functions and how they can be used together to process the Daymet netCDF mosaic files into a more useful format in R.

Package Installation

Currently, the package is only available through GitHub. It can be installed using the devtools package by executing the following commands in the R workspace:




Contact Info

Kyle O'Neil