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ecmwfr

Programmatic interface to the 'ECMWF' web API services. Allows for easy downloads of ECMWF public data.

Setup

Before starting save your provided ECMWF key to your local keychain. The package does not allow you to use your key inline in scripts to limit security issues when sharing scripts on github or otherwise.

# set a key to the keychain
wf_set_key(email = "john.smith@example.com", key = "XXXXXXXXXXXXXXXXXXXXXX")

# you can retrieve the key using
wf_get_key(email = "john.smith@example.com")

# the output should be the key you provided
# "XXXXXXXXXXXXXXXXXXXXXX"

Listing Ancillary data

You can list ancillary data such as user information, datasets and services using the following calls.

# user info
wf_user_info(email = "john.smith@example.com")

# services
wf_services(email = "john.smith@example.com")

# datasets
wf_datasets(email = "john.smith@example.com")

Data Requests

To download data use the wf_request() function, together with your email and a request string syntax as documented. Instead of json formatting the function uses a simple R list for all the arguments.

# this is an example of a request
my_request <- list(stream = "oper",
                  levtype = "sfc",
                  param = "165.128/166.128/167.128",
                  dataset = "interim",
                  step = "0",
                  grid = "0.75/0.75",
                  time = "00/06/12/18",
                  date = "2014-07-01/to/2014-07-31",
                  type = "an",
                  class = "ei",
                  area = "73.5/-27/33/45",
                  format = "netcdf",
                  target = "tmp.nc")

# an example download using fw_request()
# using the above request list()
# 
# data will be transferred to disk
# and saved in your home directory (~)
# set by the path argument

wf_request(
  email = "john.smith@example.com",
  transfer = TRUE,
  path = "~",
  request = my_request)

This operation might take a while. A progress indicator will keep you informed on the status of your request. Once downloaded you can read in the data using the ncdf4 or raster packages for post-processing.



lhmet-forks/ecmwfr documentation built on April 21, 2020, 1:24 a.m.