The goal of gadiera5 is to list ERA5 files stored in on gadi.
Installation
You can install the development version of gadiera5 like so:
pak::pak("eliocamp/gadiera5")Example
The era5() function is the main entry point. It returns a data.table with information of all available variables and their aggregation level, as well as a description. This data.table can then be filtered and subsetted as usual.
library(gadiera5)
(temp_2metres <- era5() |>
_[variable == "2t" & aggregation == "monthly-averaged"])
#> variable long_name level aggregation
#> <char> <char> <char> <char>
#> 1: 2t 2 metre temperature single-levels monthly-averagedThe set_date_range() function sets the dates of dates of interest. The range can be specified as full dates but setting year-month or just year is also supported.
temp_2metres |>
set_date_range(c("2020-01-03", "2022-03-15"))
#> variable long_name level aggregation range_start
#> <char> <char> <char> <char> <Date>
#> 1: 2t 2 metre temperature single-levels monthly-averaged 2020-01-03
#> range_end
#> <Date>
#> 1: 2022-03-15
temp_2metres |>
set_date_range(c("2020-01", "2022-03"))
#> variable long_name level aggregation range_start
#> <char> <char> <char> <char> <Date>
#> 1: 2t 2 metre temperature single-levels monthly-averaged 2020-01-01
#> range_end
#> <Date>
#> 1: 2022-03-31
(temp_2metres <- temp_2metres |>
set_date_range(c(2020, 2022)))
#> variable long_name level aggregation range_start
#> <char> <char> <char> <char> <Date>
#> 1: 2t 2 metre temperature single-levels monthly-averaged 2020-01-01
#> range_end
#> <Date>
#> 1: 2022-12-31Finally, use get_files() to retrieve all the files. The return is a data.table with a list column called files.
temp_2metres |>
get_files()
#> variable aggregation range_start range_end files
#> <char> <char> <Date> <Date> <list_of_files>
#> 1: 2t monthly-averaged 2020-01-01 2022-12-31 <36 files>