Copernicus.eu provides a set of interesting data sets for research, education, and applied earth sciences on their Atmospheric Data Store (ADS) as part of the Copernicus Atmospheric Monitoring Service (CAMS). These data provide consistent information on the atmosphere anywhere in the world.
Before you will be able to download any data you need to get a free personal account.
Once you are in possession of your personal user (namely your user ID and a secret key)
ecmwfr allows to send requests to CDS and/or download the data.
ADS data retrievals are based on a
list object which specifies the data set to be downloaded. These definitions are called
requests (for those who are familiar with mars: these are basically mars requests). A
request defined the type of the
variables to be downloaded, the time period, output
target location, a custom
area extent, and other details.
The request syntax is available for a range of different CDS data sets. Check the ADS Dataset website to see a list of available datasets and to check whether API requests are allowed or not (go to Download Data, select some data, show request by clicking Show API Request (red button, bottom of page).
The conversion from a python based string to the list format can be automated if you use the RStudio based Addin. By selecting and using Addin -> python to list (or ‘Mars to list’) you dynamically convert queries copied from either ECMWF or CDS based services.
# Specify the data set request <- list( date = "2003-01-01/2003-01-01", format = "netcdf", variable = "particulate_matter_2.5um", time = "00:00", dataset_short_name = "cams-global-reanalysis-eac4", target = "particulate_matter.nc" )
This request downloads global re-analysis data on particulate matter on January first 2003.
The data set as specified above can be downloaded calling the
# Start downloading the data, the path of the file # will be returned as a variable (ncfile) file <- wf_request(user = "2345", # user ID (for authentification) request = request, # the request transfer = TRUE, # download the file path = ".") # store data in current working directory
Depending on the request (the amount of data you are asking for) the request function may take a while! Please note: if you try to download larger amounts of data it is suggested to split the data sets, e.g., download year-by-year, or even month-by-month, if you are trying to download several variables/fields.
Once the retrieval has finished you should now be the owner of a NetCDF containing the requested information located in the current working directory, called