vignettes/advanced_vignette.Rmd
advanced_vignette.Rmd
This is a brief overview of some of the more advanced options in the
ecmwfr
package.
Another hidden feature of ecmwfr
is the fact that the
request is the first argument in the wf_request()
function.
This means that any valid list can be piped into this function (using
the %>% or pipe symbol).
list(
product_type = 'reanalysis',
variable = 'geopotential',
year = '2024',
month = '03',
day = '01',
time = '13:00',
pressure_level = '1000',
data_format = 'grib',
dataset_short_name = 'reanalysis-era5-pressure-levels',
target = 'test.grib'
) |>
wf_request(path = "~")
Once a valid request has been created it can be made into a dynamic
function using achetypes
. Archetype functions are build
using a valid ecmwfr
ECMWF or CDS request and the vector
naming the field which are to be set as dynamic.
The wf_archetype()
function creates a new function with
as parameters the dynamic fields previously assigned. The below example
show how to use the function to generate the custom
dynamic_request()
function. We then use this new function
to alter the area
and day
fields and pipe
(%>%) into the wf_request()
function to retrieve the
data.
# this is an example of a request
dynamic_request <- wf_archetype(
request = list(
product_type = 'reanalysis',
variable = 'geopotential',
year = '2024',
month = '03',
day = '01',
time = '13:00',
pressure_level = '1000',
data_format = 'grib',
dataset_short_name = 'reanalysis-era5-pressure-levels',
target = 'test.grib'
),
dynamic_fields = c("day", "target"))
# change the day of the month
dynamic_request(day = "01", target = "new.grib")
As of version 1.4.0
you can submit parallel batch
requests. Using the archetypes, as discussed above, it was easy to
request multiple data products. However, these requests would go through
sequentially. The ECMWF CDS infrastructure allows up to 20 parallel
requests in your queue. The speed of downloading data could be increased
when submitting jobs in parallel rather than sequentially. A new
function wf_request_batch()
now implements parallel CDS
requests, using lists of requests (potentially generated by an archetype
as per above).
# creating a list of requests using wf_archetype()
# setting the day value
batch_request <- list(
dynamic_request(day = "01"),
dynamic_request(day = "02")
)
# submit a batch job using 2 workers
# one for each in the list (the number of workers
# can't exceed 20)
wf_request_batch(
batch_request,
workers = 2
)
It is allowed to mix data services in a batch requests. This allows you to formulate complex multi-service requests. Below you see a simple example using a batch requests for data from both the CDS and ADS services in one pass.
# CDS
cds_request <-
list(
product_type = 'reanalysis',
variable = 'geopotential',
year = '2024',
month = '03',
day = '01',
time = '13:00',
pressure_level = '1000',
data_format = 'grib',
dataset_short_name = 'reanalysis-era5-pressure-levels',
target = 'test.grib'
)
# ADS
ads_request <- list(
dataset_short_name = "cams-global-radiative-forcings",
variable = "radiative_forcing_of_carbon_dioxide",
forcing_type = "instantaneous",
band = "long_wave",
sky_type = "all_sky",
level = "surface",
version = "2",
year = "2018",
month = "06",
target = "download.grib"
)
combined_request <- list(
cds_request,
ads_request
)
files <- wf_request_batch(
combined_request
)
For those familiar to ECMWF mars syntax: CDS/ADS does not
accept date = "2000-01-01/to/2000-12-31"
specifications at
the moment. It is possible to specify one specific date via
date = "2000-01-01"
or multiple days via
date = ["2000-01-01","2000-01-02","2000-10-20"]
or
date = "YYYY-MM-DD/YYYY-MM-DD"
but not via
".../to/..."
.
Alternatively, you can set an environmental variable containing your Personal Access Token.
Sys.setenv(ecmwfr_PAT="abcd1234-foo-bar-98765431-XXXXXXXXXX")
This will need to be set at the beginning of each setting or added to
the user .Renviron
file. Overall, this is considered
insecure, but might be the only option on some legacy or HPC systems to
get full ecmwfr
functionality. A good blog post on why you
should not do this is provided by Maëlle
Salmon.