Title:	Toolbox for Downloading and Extracting Copernicus AgERA5 Data
Version:	0.0.2
Description:	Tools for downloading and extracting data from the Copernicus "Agrometeorological indicators from 1979 to present derived from reanalysis" https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-agrometeorological-indicators?tab=overview (AgERA5).
Config/reticulate/autoconfigure:	list( packages = list( list(package = "cdsapi", pip = TRUE) ) )
Depends:	R (≥ 3.5.0)
License:	MIT + file LICENSE
Encoding:	UTF-8
LazyData:	true
Imports:	terra, reticulate, fs, doParallel, foreach
RoxygenNote:	7.2.3
Suggests:	rmarkdown, knitr
VignetteBuilder:	knitr
URL:	https://agrdatasci.github.io/ag5Tools/
NeedsCompilation:	no
Packaged:	2023-10-12 20:43:47 UTC; db877
Author:	David Brown [aut, cre], Kaue de Sousa [ctb], Jacob van Etten [ths], Sytze de Bruin [ths]
Maintainer:	David Brown <db877@cornell.edu>
Repository:	CRAN
Date/Publication:	2023-10-12 21:10:14 UTC

Downloads AgERA5 data from the Copernicus Climate Change Service - Copernicus Climate Data Store

Description

The data is downloaded from Copernicus Climate Change Service (C3S) using the Copernicus Climate Data Store (CDSAPI) Python library https://github.com/ecmwf/cdsapi

This function provides programmatic access to the AgERA5 dataset. For more information about the data license, please visit: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf

To download the data you should have a valid CDS account, an CDS API key. Please follow the instructions at: https://cds.climate.copernicus.eu/api-how-to to create a file to store your API key. You do not need to install Python or the cdsapi, Ag5Tools will do it if required.

Usage

ag5_download(
  variable,
  statistic = NULL,
  year,
  month,
  day,
  time = NULL,
  version = "1_1",
  path
)

Arguments

Value

No return value, called for side effects.

AgERA5 variables available for download:

• cloud_cover

• liquid_precipitation_duration_fraction

• snow_thickness_lwe

• solar_radiation_flux

• 2m_temperature

• 2m_dewpoint_temperature

• precipitation_flux

• solid_precipitation_duration_fraction

• snow_thickness

• vapour_pressure

• 10m_wind_speed

• 2m_relative_humidity

Statistics for variable "2m_temperature"

Variable "2m_temperature" requires to indicate at least one of the following options in statistic:

• 24_hour_maximum

• 24_hour_mean

• 24_hour_minimum

• day_time_maximum

• day_time_mean

• night_time_mean

• night_time_minimum

Parameter "time" for Variable "2m_relative_humidity"

Variable "2m_relative_humidity" requires to indicate one of the following options in time:

• 06_00

• 09_00

• 12_00

• 15_00

• 18_00

Variables that require statistic

For the following variables, only "24_hour_mean" statistic is available, but should be explicitly indicated.

• cloud_cover

• snow_thickness_lwe

• 2m_dewpoint_temperature

• snow_thickness

• vapour_pressure

• 10m_wind_speed

Examples

## Not run: 
ag5_download(variable = "2m_temperature",
            statistic = "night_time_minimum",
            day = "all",
            month = "all",
            year = 2015,
            path = "C:/custom_target_folder"
            )
            
## End(Not run)

Extract AgERA5 data stored in a local hard drive

Description

Extract data from AgERA5 data files previously downloaded from the Copernicus Climate Data Store. These functions use package 'terra' to read *.nc files and extract the requested data for a given location and dates. If dates is one value it extracts a single observation for the specified variable and location. If dates is a character vector of length == 2, it will extract a time series of the specified variable and location, where the first dates value is the start date and the second the end date.

Usage

ag5_extract(coords, ..., path)

## S3 method for class 'numeric'
ag5_extract(
  coords,
  dates,
  variable,
  statistic = NULL,
  time = NULL,
  celsius = FALSE,
  parallel = TRUE,
  ...,
  path
)

## S3 method for class 'data.frame'
ag5_extract(
  coords,
  lon = "lon",
  lat = "lat",
  start_date = "start_date",
  end_date = "end_date",
  variable,
  statistic = NULL,
  time = NULL,
  celsius = FALSE,
  ncores = NULL,
  ...,
  path
)

Arguments

Value

numeric vector with length equal to the number of dates between first and second date. The returned vecter is a named vector, with requested dates as names. If only one date is provided the function returns a numeric vector with length = 1. If coords is a data.frame, the function returns a list of numeric vectors, each one corresponding to the rows in the input data.frame

Valid variable values

• "cloud_cover"

• "liquid_precipitation_duration_fraction"

• "snow_thickness_lwe"

• "Solar-Radiation-Flux"

• "Temperature-Air-2m"

• "2m_dewpoint_temperature"

• "Precipitation-Flux"

• "solid_precipitation_duration_fraction"

• "snow_thickness"

• "vapour_pressure"

• "10m_wind_speed"

• "Relative-Humidity-2m"

Valid statistics for variable "Temperature-Air-2m"

• Max-24h

• Mean-24h

• Min-24h

• Max-Day-Time

• Mean-Day-Time

• Mean-Night-Time

• Min-Night-Time

Variables that require statistic

For the following variables, only "24_hour_mean" statistic is available, but should be explicitly indicated.

• cloud_cover

• snow_thickness_lwe

• 2m_dewpoint_temperature

• snow_thickness

• vapour_pressure

• 10m_wind_speed

Valid time values for variable "Relative-Humidity-2m"

• 06h

• 09h

• 12h

• 15h

• 18h

References

Temperature conversion is made accordingly to: Preston-Thomas, H. (1990). The International Temperature Scale of 1990 (ITS-90). Metrologia, 27(1), 3-10. doi:10.1088/0026-1394/27/1/002

Examples

## Not run: 
temp <- ag5_extract(coords = c(lon = 35.72636, lat = -2.197162),
                      dates = "1991-04-22",
                      variable = "Temperature-Air-2m",
                      statistic = "Max-Day-Time",
                      path = "C:/temperature_data/")

## End(Not run)

Example dataset for the agera5 package

Description

100 points in Arusha, Tanzania The geographic coordinates were generated with the function st_sample from package sf

Usage

arusha_df

Format

An object of class data.frame with 100 rows and 4 columns.