Dataset Open Access

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

# ERA-NUTS (1980-2019)

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 (6.4 GB)
Name Size
era-nuts-CDD-nuts0-daily.nc
md5:8434ed7e7ab41ecaba283b56e0bef8b2
1.1 MB
era-nuts-CDD-nuts1-daily.nc
md5:41129aaaf75019aa3d3e3be49311f264
3.5 MB
era-nuts-CDD-nuts2-daily.nc
md5:0f59fd2318e366e86763e8a3bc66f285
9.2 MB
era-nuts-CDD.zip
23.6 MB
era-nuts-CS-nuts0-hourly.nc
md5:7e6c79a434496269d12a6af185d09a78
26.7 MB
era-nuts-CS-nuts1-hourly.nc
md5:431e3305c5868a4f30433427a2cb474f
83.5 MB
era-nuts-CS-nuts2-hourly.nc
md5:84d86f60953460f7c22cf98aba101d4e
219.5 MB
era-nuts-CS.zip
md5:df2c2dccb29d44c222a3f3834d705bce
1.1 GB
era-nuts-HDD-nuts0-daily.nc
md5:413c9e740b8370d03d0a2b5fb02ae846
1.1 MB
era-nuts-HDD-nuts1-daily.nc
md5:856b5cabd44317a1bcc7dd28a3ae6659
3.5 MB
era-nuts-HDD-nuts2-daily.nc
md5:3f5b729f27291b222e51279ab42881f1
9.2 MB
era-nuts-HDD.zip
md5:a805cb06f9760baa28664e26e9100085
113.4 MB
era-nuts-ro-nuts0-hourly.nc
md5:eb52ba1ff1e2d6ac635a2f10f777bcb5
26.7 MB
era-nuts-ro-nuts1-hourly.nc
md5:0f8f7673c34062c7c55684ce4c2598f7
83.5 MB
era-nuts-ro-nuts2-hourly.nc
md5:4e02cfba687868f36a60ba774f46d669
219.5 MB
era-nuts-ro.zip
md5:44ea8f0261262e55967dc575b2b6ce72
128.9 MB
era-nuts-sd-nuts0-hourly.nc
md5:b7a0c3e61ab614074c86f0e82ed651b3
26.7 MB
era-nuts-sd-nuts1-hourly.nc
83.4 MB
era-nuts-sd-nuts2-hourly.nc
md5:0f3c1eb7464d89de878158986806a335
219.5 MB
era-nuts-ssrd-nuts0-hourly.nc
md5:d20ecd8045e2084c97e6442482cb6cc0
26.7 MB
era-nuts-ssrd-nuts1-hourly.nc
md5:fe5f3b86861aee220aecb2fb318dfde3
83.5 MB
era-nuts-ssrd-nuts2-hourly.nc
md5:3fd9300dbd5af13f9fd014888dc6dcc2
219.5 MB
era-nuts-ssrd.zip
md5:0ba0af86e6244683daf0ddcc94915049
663.9 MB
era-nuts-ssrdc-nuts0-hourly.nc
md5:02fd222b5e9f3b4f629050e2464a6fb7
26.7 MB
era-nuts-ssrdc-nuts1-hourly.nc
md5:49d6b84c6420775714e97ecbe7e93752
83.5 MB
era-nuts-ssrdc-nuts2-hourly.nc
md5:2e03e6030eba538bb8302359cc7ca18c
219.5 MB
era-nuts-ssrdc.zip
md5:fe67b05e9fa0c9702142376eff9de694
332.2 MB
era-nuts-t2m-nuts0-hourly.nc
md5:2174e2047b99564a80e3d165373ee317
26.6 MB
era-nuts-t2m-nuts1-hourly.nc
md5:bdbfdb4022fa2b2ece3587d99b68d914
83.4 MB
era-nuts-t2m-nuts2-hourly.nc
219.5 MB
era-nuts-t2m.zip
md5:6f9130efc5d782d12e0b566bc6b5c96e
382.4 MB
era-nuts-ws10-nuts0-hourly.nc
26.7 MB
era-nuts-ws10-nuts1-hourly.nc
md5:57d8df31ae8fc1564b499e5e80636f18
83.4 MB
era-nuts-ws10-nuts2-hourly.nc
md5:d2fb528cc0ddbf8f60ee2c5a13227c00
219.5 MB
era-nuts-ws10.zip
md5:2d32e6fabca9b519ff3b8db3766aee12
682.7 MB
era-nuts-ws100-nuts0-hourly.nc
md5:0445e1f37a591f38f34621a43821b08e
26.7 MB
era-nuts-ws100-nuts1-hourly.nc
md5:5f83a8112a757166d92ac0a0a8231b62
83.4 MB
era-nuts-ws100-nuts2-hourly.nc
md5:f9cc00168afae57686dabbc007249607
219.5 MB
era-nuts-ws100.zip
md5:434ddf60692f7e947d3d25b81b2252bf
350.1 MB
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