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ERA-NUTS: meteorological time-series based on C3S ERA5 for European regions (1980-2021)
<p><strong># ERA-NUTS (1980-2021)</strong></p> <p>This dataset contains a set of time-series of meteorological variables based on <a href="https://climate.copernicus.eu/climate-reanalysis">Copernicus Climate Change Service (C3S) ERA5 reanalysis</a>. The data files can be downloaded from here while notebooks and other files can be found on the <a href="https://github.com/energy-modelling-toolkit/era-nuts-code">associated Github repository</a>.</p> <p>This data has been generated with the aim of providing hourly time-series of the <strong>meteorological variables</strong> commonly used for power system modelling and, more in general, studies on energy systems.</p> <p>An example of the analysis that can be performed with ERA-NUTS is shown <a href="https://youtu.be/zVeF8Dv6jlE">in this video</a>.</p> <p><strong>Important</strong>: <em>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 <a href="mailto:matteo.de-felice@ec.europa.eu">sending an email</a> or opening an Issue in the <a href="https://github.com/energy-modelling-toolkit/era-nuts-code">associated Github repository</a>.</em></p> <p><strong>## Data</strong><br> The time-series have hourly/daily/monthly frequency and are aggregated following the <a href="https://ec.europa.eu/eurostat/web/nuts/background">NUTS 2016 classification</a>. 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).</p> <p>This dataset contains NUTS0/1/2 time-series for the following variables obtained from the <strong>ERA5 reanalysis data</strong> (in brackets the name of the variable on the Copernicus Data Store and its unit measure):</p> <p> - <strong>t2m</strong>: 2-meter temperature (`2m_temperature`, Celsius degrees)<br> - <strong>ssrd</strong>: Surface solar radiation (`surface_solar_radiation_downwards`, Watt per square meter)<br> - <strong>ssrdc</strong>: Surface solar radiation clear-sky (`surface_solar_radiation_downward_clear_sky`, Watt per square meter)<br> - <strong>ro</strong>: Runoff (`runoff`, millimeters)<br> - <strong>sd</strong>: Snow depth (`sd`, meters)<br> <br> There are also a set of derived variables:<br> - <strong>ws10</strong>: Wind speed at 10 meters (derived by `10m_u_component_of_wind` and `10m_v_component_of_wind`, meters per second)<br> - <strong>ws100</strong>: Wind speed at 100 meters (derived by `100m_u_component_of_wind` and `100m_v_component_of_wind`, meters per second)<br> - <strong>CS</strong>: Clear-Sky index (the ratio between the solar radiation and the solar radiation clear-sky)<br> - <strong>RH</strong>: Relative Humidity (computed following Lawrence, BAMS 2005 and Alduchov & Eskridge, 1996)<br> - <strong>HDD</strong>/<strong>CDD</strong>: Heating/Cooling Degree days (derived by 2-meter temperature the <a href="https://ec.europa.eu/eurostat/cache/metadata/en/nrg_chdd_esms.htm">EUROSTAT definition</a>.</p> <p>For each variable we have <strong>367 440 hourly samples</strong> (from 01-01-1980 00:00:00 to 31-12-2021 23:00:00) for <strong>34/115/309 regions</strong> (NUTS 0/1/2).<br> <br> The data is provided in two formats:</p> <p> - 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.<br> - Comma Separated Value ("single index" format for all the variables and the time frequencies and "stacked" only for daily and monthly)<br> <br> All the CSV files are stored in a zipped file for each variable.</p> <p><strong>## Methodology</strong></p> <p>The time-series have been generated using the following workflow:</p> <p> 1. The NetCDF files are downloaded from the Copernicus Data Store from the <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=form">ERA5 hourly data on single levels from 1979 to present</a> dataset<br> 2. The data is read in R with the <a href="http://www.meteo.unican.es/climate4R">climate4r</a> packages and aggregated using the function `/get_ts_from_shp` from <a href="https://github.com/matteodefelice/panas">panas</a>. 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.<br> 3. The derived variables (wind speed, CDD/HDD, clear-sky) are computed and all the CSV files are generated using R<br> 4. The NetCDF are created using `xarray` in Python 3.8.</p> <p><strong>## Example notebooks</strong></p> <p>In the folder `notebooks` on the <a href="https://github.com/energy-modelling-toolkit/era-nuts-code">associated Github repository</a> 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 <a href="https://github.com/kavvkon/enlopy">enlopy</a> package.</p> <p>There are currently two notebooks:</p> <p> - <strong>exploring-ERA-NUTS</strong>: it shows how to open the NetCDF files (with Dask), how to manipulate and visualise them.<br> - <strong>ERA-NUTS-explore-with-widget</strong>: explorer interactively the datasets with [<a href="https://jupyter.org/">jupyter</a>]() and <a href="https://ipywidgets.readthedocs.io/en/stable/">ipywidgets</a>.</p> <p>The notebook `exploring-ERA-NUTS` is also available rendered as HTML.<br> <br> <strong>## Additional files</strong></p> <p>In the folder `additional files`on the <a href="https://github.com/energy-modelling-toolkit/era-nuts-code">associated Github repository</a> 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.</p> <p><strong>## License</strong></p> <p>This dataset is released under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY-4.0 license</a>.</p> <p><strong>## Changelog</strong></p> <p><strong>2022-04-08 </strong>Added Relative Humidity (RH)<br> <strong>2022-03-07 </strong>Added the missing month in CDD/HDD <br> <strong>2022-02-08 </strong>Updated the wind speed and temperature data due to missing months. </p> <p> </p>
EOOffshore: New European Wind Atlas (NEWA) Data for the Irish Continental Shelf Region
<p><a href="https://eooffshore.github.io/">EOOffshore</a> is a <a href="https://www.seai.ie/">Sustainable Energy Authority of Ireland (SEAI)</a> funded <a href="https://www.seai.ie/data-and-insights/seai-research/research-projects/details/building-upon-copernicus-earth-observation-services-to-augment-wind-measurement-coverage-of-the-oredp-offshore-renewable-energy-assessment-areas">project</a>, which commenced in June 2020 in the <a href="https://www.ucd.ie/physics/">School of Physics</a> in <a href="https://www.ucd.ie/">University College Dublin (UCD)</a>. It presents a case study that demonstrates the utility of the <a href="https://pangeo.io/">Pangeo</a> software ecosystem in the development of offshore wind speed and power density estimates, increasing wind measurement coverage of offshore renewable energy assessment areas in the <a href="https://www.marine.ie/Home/site-area/irelands-marine-resource/real-map-ireland">Irish Continental Shelf (ICS)</a> region. It has involved the creation of a new <a href="https://eooffshore.github.io/datasets.html">wind data catalog</a> for this region, consisting of a collection of analysis-ready, cloud-optimized (ARCO) datasets featuring up to 21 years of available in situ, reanalysis, and satellite observation wind data products.</p> <p>The <a href="https://www.neweuropeanwindatlas.eu/">New European Wind Atlas (NEWA)</a> provides wind statistics covering onshore Europe, 100km offshore over European seas, and the complete North and Baltic Seas, based on <a href="https://map.neweuropeanwindatlas.eu/about">30 years of mesoscale simulations</a>. These catalog data sets contain 2009-2018 products for the ICS region, provided by the <a href="https://map.neweuropeanwindatlas.eu/">NEWA Map Layers and Datasets</a> website, featuring variables at multiple heights (metres above surface level). They were used in the EOOffshore project outputs presented (<a href="https://meetingorganizer.copernicus.org/EGU22/EGU22-2746.html"><em>Scalable Offshore Wind Analysis With Pangeo</em></a>) at the <a href="https://meetingorganizer.copernicus.org/EGU22/session/42046"><em>Meeting Exascale Computing Challenges with Compression and Pangeo</em></a> <a href="https://www.egu22.eu/">2022 EGU General Assembly</a> session.</p> <ul> <li><em>eooffshore_ics_newa_celticsea.zarr.tar.gz</em> <ul> <li>Data set for a North Celtic Sea area of interest.</li> </ul> </li> <li><em>eooffshore_ics_newa_irishsea.zarr.tar.gz</em> <ul> <li>Data set for an Irish Sea area of interest.</li> </ul> </li> <li><em>eooffshore_ics_newa_m3.zarr.tar.gz</em> <ul> <li>Data set for the area surrounding the <a href="http://www.marine.ie/Home/site-area/data-services/real-time-observations/irish-weather-buoy-network-imos">Irish Weather Buoy Network - M3 buoy</a> coordinates.</li> </ul> </li> <li><em>eooffshore_ics_newa_m4.zarr.tar.gz</em> <ul> <li>Data set for the area surrounding the <a href="http://www.marine.ie/Home/site-area/data-services/real-time-observations/irish-weather-buoy-network-imos">Irish Weather Buoy Network - M4 buoy</a> coordinates.</li> </ul> </li> </ul> <p>Description and example usage of the NEWA data sets in EOOffshore:</p> <ul> <li><a href="https://eooffshore.github.io/NEWA_ICS_Wind_Data.html">NEWA Wind Data for Irish Continental Shelf region</a></li> <li><a href="https://eooffshore.github.io/Offshore_Wind_AOI.html">Offshore Wind in Irish Areas Of Interest</a></li> <li><a href="https://eooffshore.github.io/Comparison_Wind_Power.html">Comparison of Offshore Wind Speed Extrapolation and Power Density Estimation</a></li> </ul> <p>As requested by the <a href="https://map.neweuropeanwindatlas.eu/about">NEWA Terms of use</a>, the following attribution is declared:</p> <ul> <li>Data [2009 - 2018] obtained from the New European Wind Atlas (NEWA), a free, web-based application developed, owned and operated by the NEWA Consortium. For additional information see <a href="http://www.neweuropeanwindatlas.eu/">www.neweuropeanwindatlas.eu</a>.</li> </ul>
Data repository for the publication "Economic Interests Cloud Hazard Reductions in the European Regulation of Substances of Very High Concern"
<p>This repository contains the data and scripts associated with the article “Economic Interests Cloud Hazard Reductions in the European Regulation of Substances of Very High Concern“, written by Jessica Coria, Erik Kristiansson and Mikael Gustavsson.</p>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Sweden
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Portugal
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Lithuania
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - United Kingdom (Northern Ireland)
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund</li> </ul> <p>Disclaimer: In accordance with the Agreement on the Withdrawal of the United Kingdom from the EU, and in particular with the Protocol on IE/NI, the EU requirements on data sampling are also applicable to Northern Ireland.</p>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Italy
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Croatia
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Romania
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Finland
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Spain
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Estonia
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Denmark
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Greece
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Luxembourg
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Germany
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Belgium
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Ireland
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the 2021 Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - France
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2021, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
ScienceDex guides
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OpenNeuro
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