CopernicusMarineEasily access information from https://data.marine.copernicus.eu
Overview
Copernicus Marine Service
Information is a programme
subsidised by the European Commission. Its mission is to provide free
authoritative information on the oceans physical and biogeochemical
state. The CopernicusMarine R package is developed apart from this
programme and facilitates retrieval of information from
https://data.marine.copernicus.eu. With the package you can:
- List available marine data for Copernicus and provide meta-information.
- Download and use the data directly in R.
Why use CopernicusMarine
Copernicus Marine offers access to their data services through a Python
application interface. For
R users this requires complex installation procedures and is difficult
to maintain in a stable R package. The CopernicusMarine R package has
a much simpler installation procedure (see below) and does not depend on
third party software, other than packages available from
CRAN.
Installation
Get CRAN version
install.packages("CopernicusMarine")Get development version on github
devtools::install_github('pepijn-devries/CopernicusMarine')Usage
The package provides an interface between R and the Copernicus Marine services. Note that for some of these services you need an account and have to comply with specific terms. The usage section briefly shows three different ways of obtaining data from Copernicus:
Please check the manual for complete documentation of the package.
Unfortunately, downloading subsets is not operational in R due to some technical issues. It seems that it might take some time to get this fixed. In the meantime, you could have a look at this work-around.
If you don’t want to subset the data and want the complete set, you can use the SpatioTemporal Asset Catalogs (STAC), if these are available for your product. First you can list STAC files available for a specific product (and layer):
stac_files <-
cms_list_stac_files(
"GLOBAL_ANALYSISFORECAST_PHY_001_024",
"cmems_mod_glo_phy-cur_anfc_0.083deg_P1D-m")
stac_files
#> # A tibble: 946 × 8
#> home native current_path LastModified ETag Size StorageClass Type
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"4… 1939… STANDARD Norm…
#> 2 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"9… 1939… STANDARD Norm…
#> 3 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"9… 1939… STANDARD Norm…
#> 4 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"c… 1939… STANDARD Norm…
#> 5 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"2… 1938… STANDARD Norm…
#> 6 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"0… 1938… STANDARD Norm…
#> 7 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"5… 1939… STANDARD Norm…
#> 8 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"5… 1939… STANDARD Norm…
#> 9 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"9… 1939… STANDARD Norm…
#> 10 s3.waw3-1.cl… mdl-n… native/GLOB… 2024-04-18T… "\"1… 1939… STANDARD Norm…
#> # ℹ 936 more rowsDownloading the first file can be done with
cms_download_stac(stac_files[1,,drop = FALSE], tempdir()), where the
file would be stored in a temporary directory. By default the progress
is printed as files can be very large and may take some time to
download.
Web Map Tile Services (WMTS) allow to quickly plot pre-rendered images onto a map. This may not be useful when you need the data for analyses but is handy for quick visualisations, inspection or presentation of data. In R it is very easy to add WMTS layers to an interactive map using leaflet widgets. This is demonstrated with the example below (note that in the documentation the map is only shown statically and is not interactive).
leaflet::leaflet() |>
leaflet::setView(lng = 3, lat = 54, zoom = 4) |>
leaflet::addProviderTiles("Esri.WorldImagery") |>
addCmsWMTSTiles(
product = "GLOBAL_ANALYSISFORECAST_PHY_001_024",
layer = "cmems_mod_glo_phy-thetao_anfc_0.083deg_P1D-m",
variable = "thetao"
)Citing the data you use
A Copernicus account comes with several terms of use. One of these is that you properly cite the data you use in publications. In fact, we also have credit the data used in this documentation, which can be easily done with the following code:
cms_cite_product("GLOBAL_ANALYSISFORECAST_PHY_001_024")
#> doi
#> "E.U. Copernicus Marine Service Information; Global Ocean Physics Analysis and Forecast - GLOBAL_ANALYSISFORECAST_PHY_001_024 (2016-10-14). DOI:10.48670/moi-00016"