7beeed0bc7fa41feb10be22ee9d10f00 English 8-bit variable size UCS Transfer Format, based on ISO/IEC 10646 dataset NERC EDS Centre for Environmental Data Analysis 01235446432 RAL Space STFC Rutherford Appleton Laboratory, Harwell Campus Didcot OX11 0QX United Kingdom support@ceda.ac.uk pointOfContact 2026-05-10T02:21:45 UK GEMINI 2.3 WGS 84 Adverse Weather Scenarios for Future Electricity Systems 2021-06-03T14:48:03 publication 2021-06-03T14:48:03 creation https://catalogue.ceda.ac.uk/uuid/7beeed0bc7fa41feb10be22ee9d10f00 7beeed0bc7fa41feb10be22ee9d10f00 NERC EDS Centre for Environmental Data Analysis This dataset contains gridded meteorological data associated with challenging periods of weather for highly-renewable UK and European electricity systems of the future collected during the Adverse Weather Scenarios for Future Electricity Systems project. This project is a collaboration between the Met Office, the National Infrastructure Commission and the Climate Change Committee. More details about the project can be found in the associated documentation. Two categories of challenging weather conditions; long duration adverse events and short duration wind ramping events, are provided. Long duration events The long duration event component of the dataset provides daily time series at 60 x 60 km spatial resolution, covering a European domain, for surface temperature, 100 m wind speed and net surface solar radiation data, representative of a selection of adverse weather scenarios. Each adverse weather scenario is contained within a time slice of data. For summer-time events, one calendar year (January - December) of data is provided, with the summer-time event occurring in the summer of that year. For winter-time events, two calendar years of data are provided, with the winter-time event occurring in the winter (October-March) intersecting the two calendar years. In all cases, the start date, duration and severity of the adverse weather event, contained within the time slice of data, are given in the NetCDF global ttributes. Three types of long-duration adverse weather scenarios are represented: winter-time wind-drought-peak-demand events, summer-time wind-drought-peak-demand events, and summer-time surplus generation events. These are provided at various extreme levels (1 in 2, 5, 10, 20 ,50 and 100-year events); and for a range of current and nominal future climate change warming levels (1.2 [current day, early 2020s], 1.5, 2, 3, and 4 degrees Celsius above pre-industrial level), representative of events impacting either just the UK, or Europe as a whole. The data provided are derived from the Met Office decadal prediction system hindcast (https://www.metoffice.gov.uk/research/approach/modelling-systems/unified-model/climate-models/depresys), according to the climate change impacts identified from UKCP18 (https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index). Short duration events The short duration event component of the dataset provides hourly time series at 4 x 4 km spatial resolution, covering a UK and surrounding offshore area domain, for 100 m wind speed, representative of a selection of wind generation ramping events. Each adverse weather scenario is contained within a time slice of data with up to one week before and one week after the day on which the event occurs (up to 15 days in total) provided. For the majority of events provided, the full 15 days are available, however for a small number of events which occur less than one week from the beginning or end of the underlying data used to derive this dataset, this is not possibly to supply, and these events are listed below. The start date and time along with the direction and magnitude of the ramp (change in wind capacity factor) contained within the time slice of data, are given in the NetCDF global attributes. The short duration wind generation ramping events are representative of events impacting five separate regions of Great Britain and surrounding offshore areas, as defined in the accompanying documentation. These regions are Scotland, the East England, West England and Wales offshore North and offshore South. The events are defined by changes in wind capacity factors occurring over different length time windows (1-hour, 3-hour, 6-hour, 12-hour and 24-hour windows). These are provided at various extreme levels (1 in 2, 5, 10, 20 ,50 and 100-year events) for the 1.2 degrees Celsius above pre-industrial level (I.e. representative of early 2020s climate) and through the analysis outlined in the accompanying documentation are though to also be representative of the 2, 3, and 4 degrees Celsius above pre-industrial level nominal future climate change warming levels. The data provided are derived from the UKCP18 local projections (https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index). The methods developed for characterising and representing these adverse weather scenarios, and the approach used to compile the final dataset are presented in the accompanying documentation. Use of this data is subject to the terms of the Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/). The following acknowledgment must be given when using the data: © Crown Copyright 2021, Met Office, funded by the National Infrastructure Commission. Dawkins, Laura Unavailable author Unavailable author Rushby, Isabel Unavailable author Unavailable author Pearce, Megan Unavailable author Unavailable author Wallace, Emily Unavailable author Unavailable author Butcher, Tom Unavailable author Unavailable author NERC EDS Centre for Environmental Data Analysis custodian 01235446432 RAL Space STFC Rutherford Appleton Laboratory, Harwell Campus Didcot OX11 0QX United Kingdom support@ceda.ac.uk custodian NERC EDS Centre for Environmental Data Analysis distributor 01235446432 RAL Space STFC Rutherford Appleton Laboratory, Harwell Campus Didcot OX11 0QX United Kingdom support@ceda.ac.uk distributor Dawkins, Laura Unavailable principal_investigator Unavailable principalInvestigator NERC EDS Centre for Environmental Data Analysis point_of_contact 01235446432 RAL Space STFC Rutherford Appleton Laboratory, Harwell Campus Didcot OX11 0QX United Kingdom support@ceda.ac.uk pointofContact NERC EDS Centre for Environmental Data Analysis publisher 01235446432 RAL Space STFC Rutherford Appleton Laboratory, Harwell Campus Didcot OX11 0QX United Kingdom support@ceda.ac.uk publisher notPlanned dataset Adverse weather scenarios future electricity systems adverse weather scenarios for future electricity systems UK Europe weather risk climate risk energy system extreme weather scenarios electricity system resilience climate change atmospheric conditions theme GEMET - INSPIRE themes, version 1.0 2008-06-01 publication otherRestrictions Public data: access to these data is available to both registered and non-registered users. otherRestrictions Under the following licence http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/, appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. grid English climatologyMeteorologyAtmosphere -30.0 40.0 30.0 75.0 1960-01-01T00:00:00 2097-12-31T00:00:00 Data are NetCDF formatted NERC EDS Centre for Environmental Data Analysis Data Center Contact 01235446432 RAL Space STFC Rutherford Appleton Laboratory, Harwell Campus Didcot OX11 0QX United Kingdom support@ceda.ac.uk distributor https://catalogue.ceda.ac.uk/uuid/7beeed0bc7fa41feb10be22ee9d10f00 CEDA Data Catalogue Page Detail and access information for the resource information http://data.ceda.ac.uk/badc/deposited2021/adverse_met_scenarios_electricity/data DOWNLOAD Download Data download https://nic.org.uk/app/uploads/MetOffice_NIC_LiteratureReview_2019.pdf Weather and Climate Related Sensitivities and Risks in a Highly Renewable UK Energy System: A Literature Review No further details. information https://nic.org.uk/app/uploads/MetOffice-Adverse-Weather-Scenarios-Discovery-Phase.pdf Adverse Weather Scenarios for Renewable Energy System Testing: Discovery Phase No further details. information https://nic.org.uk/app/uploads/MetOffice-Characterising-Adverse-Weather-Phase-2a.pdf Characterising Adverse Weather for the UK Electricity System, including addendum for surplus generation events No further details. information https://www.metoffice.gov.uk/research/approach/modelling-systems/unified-model/climate-models/depresys Met Office decadal prediction system No further details. information https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index UKCP18 climate change impacts No further details. information https://nic.org.uk/app/uploads/MetOffice_NIC_CCC_Phase2bReport.pdf Adverse Weather Scenarios for Future Electricity Systems: Developing the dataset of long-duration events No further details. information https://www.youtube.com/watch?v=Hw-OvlvSe_A Recording of the latest project user group meeting, describing the dataset and its development No further details. information https://github.com/2021-Energy-Climate-Hackathon/group_2/tree/master/ExploreData GitHub repository containing example code for visualising the dataset in Python and R No further details. information dataset Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 This dataset has been developed by the Met Office as part of the 'Adverse Weather Scenarios for Future Electricity Systems' project, commissioned by the National Infrastructure Commission, and co-lead by the Climate Change Committee. The data provided are derived from the Met Office decadal prediction system hindcast and UKCP18, according to the climate change impacts identified from UKCP18. Further information about the development of this dataset are presented in the accompanying reports. The data has been sent by the data providers to be archived at the Centre for Environmental Data Analysis (CEDA).