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https://github.com/bluegreen-labs/daymetr
An R Interface to the Daymet Web Services
https://github.com/bluegreen-labs/daymetr
climate-data data-science daymet gridded-data netcdf ornl-daac r-package rstats
Last synced: about 1 month ago
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An R Interface to the Daymet Web Services
- Host: GitHub
- URL: https://github.com/bluegreen-labs/daymetr
- Owner: bluegreen-labs
- License: other
- Created: 2016-05-25T18:21:27.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2024-02-04T09:45:24.000Z (8 months ago)
- Last Synced: 2024-06-11T16:27:55.709Z (3 months ago)
- Topics: climate-data, data-science, daymet, gridded-data, netcdf, ornl-daac, r-package, rstats
- Language: R
- Homepage: http://bluegreen-labs.github.io/daymetr/
- Size: 4.37 MB
- Stars: 29
- Watchers: 4
- Forks: 17
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- open-sustainable-technology - daymetr - Allows for easy downloads of Daymet climate data directly to your R workspace or your computer. (Climate Change / Climate Data Processing and Analysis)
README
# daymetr 
[](https://github.com/bluegreen-labs/daymetr/actions)
[](https://app.codecov.io/gh/bluegreen-labs/daymetr)
[](https://cran.r-project.org/package=daymetr)
A programmatic interface to the [Daymet web
services](https://daymet.ornl.gov). Allows for easy downloads of Daymet
climate data directly to your R workspace or your computer. Routines for
both single pixel data downloads and gridded (netCDF) data are provided.
Please use the below citation when using the package.
## How to cite this package
> Hufkens K., Basler J. D., Milliman T. Melaas E., Richardson A.D. 2018
> An integrated phenology modelling framework in R: Phenology modelling
> with phenor. Methods in Ecology &
> Evolution, 9: 1-10. https://doi.org/10.1111/2041-210X.12970
## Installation
### stable release
To install the current stable release use a CRAN repository:
``` r
install.packages("daymetr")
library("daymetr")
```
### development release
To install the development releases of the package run the following
commands:
``` r
if(!require(remotes)){install.packages("remotes")}
remotes::install_github("bluegreen-labs/daymetr")
library("daymetr")
```
Vignettes are not rendered by default, if you want to include additional
documentation please use:
``` r
if(!require(remotes)){install.packages("remotes")}
remotes::install_github("bluegreen-labs/daymetr", build_vignettes = TRUE)
library("daymetr")
```
## Use
### Single pixel location download
For a single site use the following format
``` r
download_daymet(site = "Oak Ridge National Laboratories",
lat = 36.0133,
lon = -84.2625,
start = 1980,
end = 2010,
internal = TRUE)
```
| Parameter | Description |
| --------- | ------------------------------------------------------------------------------------------------------------------------------- |
| site | site name |
| lat | latitude of the site |
| lon | longitude of the site |
| start | start year of the time series (data start in 1980) |
| end | end year of the time series (current year - 2 years, use force = TRUE to override) |
| internal | logical, TRUE or FALSE, if true data is imported into R workspace otherwise it is downloaded into the current working directory |
| path | path where to store the data when not used internally, defaults to tempdir() |
| force | force “out of temporal range” downloads |
| silent | suppress the verbose output |
Batch mode uses similar parameters but you provide a comma separated
file with site names and latitude longitude which are sequentially
downloaded. The format of the comma separated file is: site name,
latitude, longitude.
``` r
download_daymet_batch(file_location = 'my_sites.csv',
start = 1980,
end = 2010,
internal = TRUE)
```
### Gridded data downloads
For gridded data use either download\_daymet\_tiles() for individual
tiles or download\_daymet\_ncss() for a netCDF subset which is not bound
by tile limits (but restricted to a 6GB query size).
#### *Tiled data*
``` r
download_daymet_tiles(location = c(36.0133,-84.2625),
tiles = NULL,
start = 1980,
end = 2012,
param = "ALL")
```
| Parameter | Description |
| --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| location | vector with a point location c(lat,lon) or top left / bottom right pair c(lat,lon,lat,lon) |
| tiles | vector with tile numbers if location point or top left / bottom right pair is not provided |
| start | start year of the time series (data start in 1980) |
| end | end year of the time series (current year - 2 years, use force = TRUE to override) |
| param | climate variable you want to download vapour pressure (vp), minimum and maximum temperature (tmin,tmax), snow water equivalent (swe), solar radiation (srad), precipitation (prcp) , day length (dayl). The default setting is ALL, this will download all the previously mentioned climate variables. |
| path | path where to store the data, defaults to tempdir() |
| silent | suppress the verbose output |
If only the first set of coordinates is provided the tile in which these
reside is downloaded. If your region of interest falls outside the scope
of the DAYMET data coverage a warning is issued. If both top left and
bottom right coordinates are provided all tiles covering the region of
interst are downloaded. I would caution against downloading too much
data, as file sizes do add up. So be careful how you specify your region
of interest.
#### *netCDF subset (ncss) data*
``` r
download_daymet_ncss(location = c(36.61,-85.37,33.57,-81.29),
start = 1980,
end = 1980,
param = "tmin")
```
| Parameter | Description |
| --------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| location | bounding box extent defined as top left / bottom right pair c(lat,lon,lat,lon) |
| start | start year of the time series (data start in 1980) |
| end | end year of the time series (current year - 2 years, use force = TRUE to override) |
| param | climate variable you want to download vapour pressure (vp), minimum and maximum temperature (tmin,tmax), snow water equivalent (swe), solar radiation (srad), precipitation (prcp) , day length (dayl). The default setting is ALL, this will download all the previously mentioned climate variables. |
| mosaic | tile mosaic to use, defaults to “na” for North America (use “pr” for Puerto Rico and “hi” for Hawaii) |
| path | path where to store the data, defaults to tempdir() |
| silent | suppress the verbose output |
Keep in mind that the bounding box is defined by the minimum (square)
bounding box in a Lambert Conformal Conic (LCC) projection as defined by
the provided geographic coordinates. In general the query area will be
larger than the requested location. For more information I refer to
[Daymet documentation](https://daymet.ornl.gov/web_services.html) on the
web service.
## Acknowledgements
This project was supported by the National Science Foundation’s
Macro-system Biology Program (awards EF-1065029 and EF-1702697) and the Marie Skłodowska-Curie Action (H2020 grant 797668). Logo design elements are taken from the FontAwesome library according to [these terms](https://fontawesome.com/license), where the globe element was inverted and intersected.