https://github.com/chuhousen/daymetr
An R Interface to the Daymet Web Services
Science Score: 23.0%
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An R Interface to the Daymet Web Services
Basic Info
- Host: GitHub
- Owner: chuhousen
- License: other
- Default Branch: master
- Homepage: http://bluegreen-labs.github.io/daymetr/
- Size: 2.86 MB
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Fork of bluegreen-labs/daymetr
Created over 4 years ago
· Last pushed about 5 years ago
https://github.com/chuhousen/daymetr/blob/master/
# daymetr[](https://github.com/bluegreen-labs/daymetr/actions) [](https://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. ## 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(devtools)){install.packages("devtools")} devtools::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(devtools)){install.packages("devtools")} devtools::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. ## Citation 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](https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.12970), 9: 1-10. ## Acknowledgements This project was supported by the National Science Foundations Macro-system Biology Program (awards EF-1065029 and EF-1702697) and the Marie Skodowska-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.
Owner
- Name: Housen Chu
- Login: chuhousen
- Kind: user
- Website: https://sites.google.com/site/chuhousen/home
- Twitter: chuhousen
- Repositories: 2
- Profile: https://github.com/chuhousen
environmental scientist, studying plant-ecosystem-atmosphere interactions in natural and managed ecosystems
