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Dataset Open Access

# ERA-NUTS: meteorological time-series based on C3S ERA5 for European regions (1980-2020)

# ERA-NUTS (1980-2020)

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 359 424 hourly samples (from 01-01-1980 00:00:00 to 31-12-2020 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 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 3.8.

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 (6.7 GB)
Name Size
era-nuts-CDD-nuts0-daily.nc
md5:65f6b417e888d8be6c9a744900c6d5ce
1.1 MB
era-nuts-CDD-nuts1-daily.nc
3.5 MB
era-nuts-CDD-nuts2-daily.nc
9.2 MB
era-nuts-CDD.zip
md5:2e3aa4170efe2c8d010a9b2c37af9c03
24.2 MB
era-nuts-CS-nuts0-hourly.nc
md5:85fa16f6a1ba54c8f5c4684b3515fc98
27.3 MB
era-nuts-CS-nuts1-hourly.nc
md5:11db6a35a056b1687f28c559036a8040
85.6 MB
era-nuts-CS-nuts2-hourly.nc
md5:69ef1f820f9001f45fed65f3690044a2
225.0 MB
era-nuts-CS.zip
1.1 GB
era-nuts-HDD-nuts0-daily.nc
1.1 MB
era-nuts-HDD-nuts1-daily.nc
md5:b24d9d3b820eb892ba738de8e286399a
3.5 MB
era-nuts-HDD-nuts2-daily.nc
md5:763143b17de9aecde8d8862d816919c8
9.2 MB
era-nuts-HDD.zip
md5:a9277f4296658e714922e28cc00a4c34
116.2 MB
era-nuts-ro-nuts0-hourly.nc
md5:e3bc6b3e040b74571d1201467bfc612a
27.3 MB
era-nuts-ro-nuts1-hourly.nc
md5:c9a0a8b5bf3973249b63bf4c65a56f56
85.6 MB
era-nuts-ro-nuts2-hourly.nc
md5:a78f65b4d035efa00a65f6e74756ca40
225.0 MB
era-nuts-ro.zip
md5:19c6f3998cea060d4cb39c4c410b6987
131.0 MB
era-nuts-sd-nuts0-hourly.nc
md5:eac7990e9163fc34a7ae12f0c48ef8ae
27.3 MB
era-nuts-sd-nuts1-hourly.nc
md5:dc414e8538fc5b10eb8d8466110c3196
85.6 MB
era-nuts-sd-nuts2-hourly.nc
md5:195c95e3334c67acac3f4399e6025dfd
225.0 MB
era-nuts-sd.zip
md5:551151d97c4fa5017f28a051984dbdcd
140.5 MB
era-nuts-ssrd-nuts0-hourly.nc
md5:322322587ac046c3180fa875945abab5
27.3 MB
era-nuts-ssrd-nuts1-hourly.nc
md5:c57735c5e4ac1b44a6a780e50a29097b
85.6 MB
era-nuts-ssrd-nuts2-hourly.nc
md5:10c8e8ba1b3662192397d2ef227e3966
225.0 MB
era-nuts-ssrd.zip
680.5 MB
era-nuts-ssrdc-nuts0-hourly.nc
md5:cc1d58d1412a8343ffaa4a36126d5594
27.3 MB
era-nuts-ssrdc-nuts1-hourly.nc
md5:f89fbc309f1e98811d767af38a332b2c
85.6 MB
era-nuts-ssrdc-nuts2-hourly.nc
md5:95478e60e468155c37afb9ff5c955e30
225.0 MB
era-nuts-ssrdc.zip
md5:ef88116503a7f30f8d9a7d5b7dcf038c
340.6 MB
era-nuts-t2m-nuts0-hourly.nc
27.3 MB
era-nuts-t2m-nuts1-hourly.nc
md5:48bc9808cb44b11b28eccef642f84711
85.6 MB
era-nuts-t2m-nuts2-hourly.nc
md5:a38a8216997a1aa2b25e5f6c2b9b7d24
225.0 MB
era-nuts-t2m.zip
md5:24dce54f354aa40d6de2cdc2e9396708
392.1 MB
era-nuts-ws10-nuts0-hourly.nc
md5:27d6d8998dde37320f02014ec749dca8
27.3 MB
era-nuts-ws10-nuts1-hourly.nc
md5:991dfeeb5f5b1863b4b6b95774c607ef
85.6 MB
era-nuts-ws10-nuts2-hourly.nc
md5:a3fc6e848df9482d1b67d566382a59b2
225.0 MB
era-nuts-ws10.zip
md5:e95f291fa5930f9e5c8dbc0e91813646
700.0 MB
era-nuts-ws100-nuts0-hourly.nc
md5:d63a6eef55caf2441b74d1a76e78d7ee
27.3 MB
era-nuts-ws100-nuts1-hourly.nc
85.6 MB
era-nuts-ws100-nuts2-hourly.nc
md5:85ebb859dbe7a66fc8ce14cef0e717ed
225.0 MB
era-nuts-ws100.zip
md5:1649d0532466209f638df4eefd82e247
358.9 MB
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