Documentation

Full documentation can be found on https://retostauffer.github.io/eupp/.

Licenses

• Software license see https://github.com/retostauffer/eupp/blob/main/LICENSE
• For data license see https://github.com/retostauffer/eupp/blob/main/DATA_LICENSE

Requirements

System requirements

Software/libs	Remarks
curl	Required for downloading data
gdal	Geospatial Data Abstraction Library (req. by R package stars)
ecCodes	ECMWF ecCodes toolbox; grib_to_netcdf is called to convert GRIB to NetCDF if requested

On most up-to-date Linux systems the ecCodes tools can be installed via package manager (e.g., apt get install -y libeccodes-tools).

R packages

Shows required packages. Defined as dependencies; should be installed automatically when using github_install() (see below). The package has been developed/tested using R version 4.1.2 using the following packages/package versions:

Package name	Tested on	Remarks
httr	1.4.2	Downloading data via https
dplyr	1.0.7	dplyr::bind_rows used in one instance
stars	0.5.5	Handling/reading spatio-temporal data
digest	0.6.27	Hashing for caching

Suggested packages ...

Package name	Tested on	Remarks
sf	1.0.4	Plotting, processing data, spatial subsetting

Installation

The package is currently only available via [github](https://github.com/retostauffer/eupp). The simplest way to install:

library("remotes")
github_install("retostauffer/eupp")

This will install the current version from the main branch. Once stable, a stable release will be provided.

Available data

• Spatial extent: longitude 6E/17W, latitude 36N/67N.
• Spatial resolution: 0.25 times 0.25 degrees (rectangular_ll grid)

Surface forecast variables

• Forecast steps (in hours):
  • Hourly forecasts from +0h to +90h
  • Three-hourly intervals from +90h to +144h (6 days ahead)
  • Six-hourly intervals from +144h to +240h (10 days ahead)

Parameter name	ECMWF key	Remarks
2 metre temperature	2t
10 metre U wind component	10u
10 metre V wind component	10v
Total cloud cover	tcc
100 metre U wind component anomaly	100ua
100 metre V wind component anomaly	100va
Convective available potential energy	cape
Soil temperature level 1	stl1
Surface sensible heat flux	sshf
Surface latent heat flux	slhf
Total column water	tcw
Total column water vapour	tcwv
Volumetric soil water layer 1	swvl1
Surface net solar radiation	ssr
Surface net thermal radiation	str
Snow depth	sd
Convective precipitation	cp
Convective inhibition	cin
Surface solar radiation downwards	ssrd
Surface thermal radiation downwards	strd
Visibility	`vis	Observations not available

Pressure level forecast variables

• Forecast steps (in hours):
  • Hourly forecasts from +0h to +90h
  • Three-hourly intervals from +90h to +144h (6 days ahead)
  • Six-hourly intervals from +144h to +240h (10 days ahead)

Parameter name	Level	ECMWF key	Remarks
Temperature	850	t
U component of wind	700	u
V component of wind	700	v
Geopotential	500	z
Specific humidity	700	q
Relative humidity	850	r

Extreme forecast index variables

• Forecast ranges (in hours): 0-24, 24-48, 48-72, 72-96, 96-120, 120-144 and 144-168.

Parameter name	ECMWF key	Remarks
2 metre temperature efi	2ti
10 metre wind speed efi	10ws
10 metre wind gust efi	10fgi
cape efi	capei
cape shear efi	capesi
Maximum temperature at 2m efi	mx2ti
Minimum temperature at 2m efi	mn2ti
Snowfall efi	sfi
Total precipitation efi	tpi

FAQ

Can we get the data as NetCDF

Yes and no; the data is currently only provided as GRIB version 1. This file format can be converted to NetCDF; the package provides this functionality.

However, the conversion is done locally and requires the ecCodes tools and NetCDF libraries to be installed. Many modern UX distributions allow to install via the built in package manager (libeccodes-tools, libeccodes-bin or similar; libnetcdf-dev, ...).

The R package will then call grib_to_netcdf on your local machine.

Can we download spatial subsets?

This is not possible at the moment. The data sets are provided in the GRIB version 1 format where subsetting (neither on request nor on the local machine) is possible. When downloading as GRIB/NetCDF the CDO (climate data operation) toolbox may be one path to go.