era5ify_point: Download and process ERA5 data for a point location

In varunayan: Download and Process 'ERA5', IMD, 'HadEX3' and 'CRU TS' Data

Download and process ERA5 data for a point location

Description

Download and process ERA5 data for a point location

Usage

ERA5ifyPoint(...)

era5ify_point(
  request_id,
  variables,
  start_date,
  end_date,
  lat,
  lon,
  dataset_type = "single",
  pressure_levels = NULL,
  frequency = "hourly",
  save_raw = FALSE,
  output_dir = tempdir(),
  use_cache = TRUE,
  convert_units = TRUE,
  verbose = FALSE,
  use_timeseries_api = NA
)

Arguments

...	Arguments passed to the main function (used by aliases).
request_id	Unique identifier for the data request.
variables	List of ERA5 variables to download.
start_date	Start date in "YYYY-MM-DD" format.
end_date	End date in "YYYY-MM-DD" format.
lat	Latitude of the point location.
lon	Longitude of the point location.
dataset_type	Type of dataset ("single" or "pressure").
pressure_levels	Pressure levels for pressure dataset.
frequency	Temporal frequency ("hourly", "daily", "monthly").
save_raw	If TRUE, save the raw downloaded files.
output_dir	Directory for the saved files (default: tempdir()).
use_cache	If TRUE, use cached data when it is available (default: TRUE).
convert_units	If TRUE, convert units to user-friendly formats (default: TRUE). When TRUE, the function returns temperature variables in Celsius (converted from Kelvin). It returns precipitation variables in mm (converted from meters).
verbose	If TRUE, print detailed progress messages.
use_timeseries_api	If TRUE, use the CDS time-series endpoint. This endpoint gives the data for a point directly. It is much faster than a subset of a gridded download. The default is NA: use the endpoint only for hourly single-level requests, because the endpoint supports only these requests. Set FALSE to always use the gridded download. If the endpoint is not available, the function automatically uses the gridded download.

Value

data.frame with processed climate data. When convert_units = TRUE:

• Temperature variables (e.g., 2m_temperature): Celsius

• Precipitation variables (e.g., total_precipitation): mm

• Other variables: original ERA5 units

Examples

setup_cds_credentials(key = "your-cds-api-key")

data <- era5ify_point(
  request_id = "my_request",
  variables = c("2m_temperature", "total_precipitation"),
  start_date = "2023-01-01",
  end_date = "2023-01-31",
  lat = 40.7128,
  lon = -74.0060
)
# Temperature is in Celsius. Precipitation is in mm.

varunayan documentation built on Oct. 30, 2026, 1:07 a.m.