download_daymet: Function to download single location 'Daymet' data

In daymetr: Interface to the 'Daymet' Web Services

Function to download single location 'Daymet' data

Description

Function to download single location 'Daymet' data

Usage

download_daymet(
  site = "Daymet",
  lat = 36.0133,
  lon = -84.2625,
  start = 2000,
  end = as.numeric(format(Sys.time(), "%Y")) - 2,
  path = tempdir(),
  internal = TRUE,
  silent = FALSE,
  force = FALSE,
  simplify = FALSE
)

Arguments

site	the site name.
lat	latitude (decimal degrees)
lon	longitude (decimal degrees)
start	start of the range of years over which to download data
end	end of the range of years over which to download data
path	set path where to save the data if internal = FALSE (default = NULL)
internal	TRUE or FALSE, if TRUE returns a list to the R workspace if FALSE puts the downloaded data into the current working directory (default = FALSE)
silent	TRUE or FALSE (default), to provide verbose output
force	TRUE or FALSE (default), override the conservative end year setting
simplify	output data as a tibble, logical FALSE or TRUE (default = TRUE)

Value

Daymet data for a point location, returned to the R workspace or written to disk as a csv file.

Examples

## Not run: 
# The following commands download and process Daymet data
# for 10 years of the >30 year of data available since 1980.
daymet_data <- download_daymet(
"testsite_name",
 lat = 36.0133,
 lon = -84.2625,
 start = 2000,
 end = 2010,
 internal = TRUE
 )

# We can now quickly calculate and plot
# daily mean temperature. Also, take note of
# the weird format of the header. This format 
# is not altered as to keep compatibility
# with other ways of acquiring Daymet data
# through the ORNL DAAC website.

# The below command lists headers of 
# the downloaded nested list.
# This data includes information on the site
# location etc. The true climate data is stored
# in the "data" part of the nested list.
# In this case it can be accessed through
# daymet_data$data. Other attributes include
# for example the tile location (daymet_data$tile),
# the altitude (daymet_data$altitude), etc.
str(daymet_data)

# load the tidyverse (install if necessary)
if(!require(tidyverse)){install.package(tidyverse)}
library(tidyverse)

# Calculate the mean temperature from min
# max temperatures and convert the year and doy
# to a proper date format.
daymet_data$data <- daymet_data$data |>
 mutate(
 tmean = (tmax..deg.c. + tmin..deg.c.)/2,
 date = as.Date(paste(year, yday, sep = "-"), "%Y-%j")
 )

# show a simple graph of the mean temperature
plot(daymet_data$data$date,
     daymet_data$data$tmean,
     xlab = "Date",
     ylab = "mean temperature")
 
# For other practical examples consult the included
# vignette. 

## End(Not run)

daymetr documentation built on Sept. 15, 2023, 5:07 p.m.