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Dataset Open Access

# ERA-NUTS: time-series based on C3S ERA5 for European regions

# ERA-NUTS (1980-2018)

This dataset contains a set of time-series of meteorological variables based on Copernicus Climate Change Service (C3S) ERA5 reanalysis. The data files can be downloaded from here while notebooks and other files can be found on the associated Github repository.

This data has been generated with the aim of providing hourly time-series of the meteorological variables commonly used for power system modelling and, more in general, studies on energy systems.

An example of the analysis that can be performed with ERA-NUTS is shown in this video.

Important: this dataset is still a work-in-progress, we will add more analysis and variables in the near-future. If you spot an error or something strange in the data please tell us sending an email or opening an Issue in the associated Github repository.

## Data
The time-series have hourly/daily/monthly frequency and are aggregated following the NUTS  2016 classification. NUTS (Nomenclature of Territorial Units for Statistics) is a European Union standard for referencing the subdivisions of countries (member states, candidate countries and EFTA countries).

This dataset contains NUTS0/1/2 time-series for the following variables obtained from the ERA5 reanalysis data (in brackets the name of the variable on the Copernicus Data Store and its unit measure):

- t2m: 2-meter temperature (2m_temperature, Celsius degrees)
- ssrd: Surface solar radiation (surface_solar_radiation_downwards, Watt per square meter)
- ssrdc: Surface solar radiation clear-sky (surface_solar_radiation_downward_clear_sky, Watt per square meter)
- ro: Runoff (runoff, millimeters)

There are also a set of derived variables:
- ws10: Wind speed at 10 meters (derived by 10m_u_component_of_wind and 10m_v_component_of_wind, meters per second)
- ws100: Wind speed at 100 meters (derived by 100m_u_component_of_wind and 100m_v_component_of_wind, meters per second)
- CS: Clear-Sky index (the ratio between the solar radiation and the solar radiation clear-sky)
- HDD/CDD: Heating/Cooling Degree days (derived by 2-meter temperature the EUROSTAT definition.

For each variable we have 350 599 hourly samples (from 01-01-1980 00:00:00 to 31-12-2019 23:00:00) for 34/115/309 regions (NUTS 0/1/2).

The data is provided in two formats:

- NetCDF version 4 (all the variables hourly and CDD/HDD daily). NOTE: the variables are stored as int16 type using a scale_factor of 0.01 to minimise the size of the files.
- Comma Separated Value ("single index" format for all the variables and the time frequencies and "stacked" only for daily and monthly)

All the CSV files are stored in a zipped file for each variable.

## Methodology

The time-series have been generated using the following workflow:

1. The NetCDF files are downloaded from the Copernicus Data Store from the ERA5 hourly data on single levels from 1979 to present dataset
2. The data is read in R with the climate4r packages and aggregated using the function /get_ts_from_shp from panas. All the variables are aggregated at the NUTS boundaries using the average except for the runoff, which consists of the sum of all the grid points within the regional/national borders.
3. The derived variables (wind speed, CDD/HDD, clear-sky) are computed and all the CSV files are generated using R
4. The NetCDF are created using xarray in Python 3.7.

NOTE: air temperature, solar radiation, runoff and wind speed hourly data have been rounded with two decimal digits.

## Example notebooks

In the folder notebooks on the associated Github repository there are two Jupyter notebooks which shows how to deal effectively with the NetCDF data in xarray and how to visualise them in several ways by using matplotlib or the enlopy package.

There are currently two notebooks:

- exploring-ERA-NUTS: it shows how to open the NetCDF files (with Dask), how to manipulate and visualise them.
- ERA-NUTS-explore-with-widget: explorer interactively the datasets with [jupyter]() and ipywidgets.

The notebook exploring-ERA-NUTS is also available rendered as HTML.

In the folder additional fileson the associated Github repository there is a map showing the spatial resolution of the ERA5 reanalysis and a CSV file specifying the number of grid points with respect to each NUTS0/1/2 region.

This dataset is released under CC-BY-4.0 license.

Files (5.1 GB)
Name Size
era-nuts-CDD-nuts0-daily.nc
md5:55d58b51aa2d47b375917634ae44f31a
1.1 MB
era-nuts-CDD-nuts1-daily.nc
md5:597da5f15de62210b3e15ac19d842d60
3.4 MB
era-nuts-CDD-nuts2-daily.nc
md5:c311db7c0924072d21100487958dafc9
8.9 MB
era-nuts-CDD.zip
md5:1ecb1b83a360679b51ed89f445636bae
17.2 MB
era-nuts-CS-nuts0-hourly.nc
md5:0535878e5e81b8111872a2aa407f712f
26.0 MB
era-nuts-CS-nuts1-hourly.nc
md5:48e22b2cc0c25c9e1357be35343eeff4
81.4 MB
era-nuts-CS-nuts2-hourly.nc
md5:79a32c1cca15b5e4b0e2c76e108138ee
214.0 MB
era-nuts-CS.zip
md5:12a84977c8b37b61c341cb632264f9be
861.7 MB
era-nuts-HDD-nuts0-daily.nc
md5:5af81676175f9e930d31b341b74a93b7
1.1 MB
era-nuts-HDD-nuts1-daily.nc
md5:38504a4ee67097d34652fd641b2b1b5c
3.4 MB
era-nuts-HDD-nuts2-daily.nc
md5:86beb59acd05c0f1a197351821fa3f3d
8.9 MB
era-nuts-HDD.zip
md5:585fe78f0727d2f4fab0c891ae549bdf
97.5 MB
era-nuts-ro-nuts0-hourly.nc
md5:8af18629a9b92f61fbc2b8f86696533a
26.0 MB
era-nuts-ro-nuts1-hourly.nc
md5:e43e9fc5d1ede1d136eb622ab4dbbf0e
81.4 MB
era-nuts-ro-nuts2-hourly.nc
md5:13e90cd73205aff2bcba48b6e42e17a7
214.0 MB
era-nuts-ro.zip
md5:96345fd13f19cf7cea9aea6f0c03446d
220.2 MB
era-nuts-ssrd-nuts0-hourly.nc
md5:03e5a13c4860b8c36026e0543c0cce9e
26.0 MB
era-nuts-ssrd-nuts1-hourly.nc
md5:1591a6cbd97d783c0e1aff0a506a5594
81.4 MB
era-nuts-ssrd-nuts2-hourly.nc
md5:5fa706d049a0ec4f09514f21caef8b8e
214.0 MB
era-nuts-ssrd.zip
312.6 MB
era-nuts-ssrdc-nuts0-hourly.nc
md5:39cd2bbf5343a3dc282893c11a966737
26.0 MB
era-nuts-ssrdc-nuts1-hourly.nc
md5:b8ce1040bcf01f9b5d185599181d4353
81.4 MB
era-nuts-ssrdc-nuts2-hourly.nc
md5:dd9bf448d002c48d60637276be6ded39
214.0 MB
era-nuts-ssrdc.zip
md5:32a82933ecf1372da22c0470968fb982
303.3 MB
era-nuts-t2m-nuts0-hourly.nc
26.0 MB
era-nuts-t2m-nuts1-hourly.nc
md5:08370ff96ab05e68a30402673b20d063
81.4 MB
era-nuts-t2m-nuts2-hourly.nc
md5:eae3cd594a156b0eb6c439713faed558
214.0 MB
era-nuts-t2m.zip
md5:5581ac9cd59fca7f2f9902d0e211c568
347.3 MB
era-nuts-ws10-nuts0-hourly.nc
md5:354326639e8715acef0f8ecdd0e0d6eb
26.0 MB
era-nuts-ws10-nuts1-hourly.nc
md5:e22959e646fb2e75aa56ee043b198037
81.4 MB
era-nuts-ws10-nuts2-hourly.nc
md5:6b7b324dfe6d08ec538c6d19e751c68f
214.0 MB
era-nuts-ws10.zip
md5:50625fe373a5dd5315e4fd28954f052c
300.0 MB
era-nuts-ws100-nuts0-hourly.nc
md5:1190c4e81997146a2f1d99f3f63b0be9
26.0 MB
era-nuts-ws100-nuts1-hourly.nc
md5:1974742e954c8af4838f377923563be5
81.4 MB
era-nuts-ws100-nuts2-hourly.nc
md5:cffc0e4bd5f836ccbc32ae66b77d6a5d
214.0 MB
era-nuts-ws100.zip
md5:bfe5b2098f39ab90f24c5268257ba32a
318.4 MB
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