The ERA5Dataset superType

ERA5 reanalysis data is stored on the Climate Data Store in several different categories, so different people with different needs may access different data types depending on their research. In ERA5Reanalysis, we defined these datasets as ERA5Dataset Types.

When defining an ERA5Dataset container, we also indicate the start and end dates of the dataset that we want to work on.

ERA5Reanalysis.ERA5Dataset — Type
ERA5Dataset

Abstract supertype for ERA5 reanalysis datasets.

All ERA5Dataset Types contain the following fields:

  • e5dID : The module ID, that also acts as a prefix to filenames
  • eroot : The specified directory in which to save the data
  • start : The date for which downloads/analysis begins
  • stop : The date for which downloads/analysis finishes
  • dtext : Is it the preliminary back extension from 1950-1978?
Note

The ERA5MonthlyHour subType also has the field hours that specifies the hour(s) of day for which monthly data is downloaded

Available Modules in ERA5Reanalysis.jl

The following datasets are currently supported by ERA5Reanalysis.jl:

  • Hourly reanalysis data (ERA5Hourly)
  • Monthly reanalysis data, which is further broken down in
    • Monthly-averaged data (ERA5Monthly)
    • Monthly-averaged hourly data (i.e. a monthly average of the diurnal cycle) (ERA5MonthlyHour)
ERA5Reanalysis.ERA5Hourly — Type
ERA5Hourly <: ERA5Dataset

Specifies that the dataset to be analyzed contains hourly data. All fields are the same as that specified in the ERA5Dataset docstring.

ERA5Reanalysis.ERA5Monthly — Type
ERA5Monthly <: ERA5Dataset

Specifies that the dataset to be analyzed contains monthly-mean data. All fields are the same as that specified in the ERA5Dataset docstring.

Missing docstring.

Missing docstring for ERA5MonthlyHour. Check Documenter's build log for details.

There are other potential modules that could be incorporated into ERA5Reanalysis.jl, such as

  • ERA5-Land data
  • Ensemble model averages, individual members, and standard deviations

Functions to create ERA5Datasets

There are two functions used to create ERA5Datasets:

  • ERA5Hourly(), which creates the ERA5Hourly subtype
  • ERA5Monthly(), which creates either the ERA5Monthly or ERA5MonthlyHour subtypes depending on inputs
ERA5Reanalysis.ERA5Hourly — Method
ERA5Hourly(;
    start :: TimeType,
    stop  :: TimeType,
    path  :: AbstractString = homedir(),
) -> ERA5Hourly <: ERA5Dataset

A function that creates an ERA5Hourly module. All possible hours are downloaded, and data is saved month-by-month.

Keyword Arguments

  • path : The specified directory in which to save the data
  • start : The date for which downloads/analysis begins, automatically rounded to the nearest month
  • stop : The date for which downloads/analysis finishes, automatically rounded to the nearest month
ERA5Reanalysis.ERA5Monthly — Method
ERA5Monthly(;
    start :: TimeType,
    stop  :: TimeType,
    path  :: AbstractString = homedir(),
    hours :: Bool = false,
) -> ERA5Monthly <: ERA5Dataset or ERA5MonthlyHour <: ERA5Dataset

A function that creates an ERA5Monthly or ERA5MonthlyHour module depending on the input arguments of hours. Data is saved year-by-year.

Keyword Arguments

  • path : The specified directory in which to save the data
  • start : The date for which downloads/analysis begins, automatically rounded to the nearest year
  • stop : The date for which downloads/analysis finishes, automatically rounded to the nearest year
  • hours : If false, download monthly-averaged data. If true, download monthly-averaged data for each hour