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The EuroCORDEX-UK project supplements the UK national climate projections (UKCP18) using information from the international CORDEX initiative. Results, reports and data are available from this page.
Enabling the use and producing improved understanding of EuroCORDEX data over the UK
About the EuroCORDEX-UK project
The 2018 UK Climate Projections (UKCP18) provide information about the future climate of the UK at coarse (60km), medium (12km) and local (2.2km) spatial resolutions. The medium-resolution projections are proving beneficial in understanding future climate risks to the UK. However, they were driven by a relatively small subset of global climate models and so may not sample the full range of uncertainty that is consistent with current scientific knowledge.
This research project extends the UKCP18 suite of climate projections by augmenting them with information from a broader range of high-resolution climate simulations, obtained from the EuroCORDEX downscaling experiment. The additional projections provide a more comprehensive sampling of uncertainty in high-resolution UK climate projections. In turn, this offers the potential to develop better informed strategies for adapting to, and mitigating the effects of, future weather and climate.
As well as providing access to additional climate projections for the UK, the project aims to provide insights into the physical plausibility of the various simulations; to assess the value added by considering high-resolution information; to identify the dominant sources of uncertainty in future projections of a variety of weather indices; and to assess the extent to which the existing UKCP ensemble provides a decision-relevant characterisation of this uncertainty. To achieve these challenging objectives, the project takes a multidisciplinary approach combining expertise in climate modelling, modern statistics and uncertainty quantification, and software engineering.
The project ran from October 2019 until January 2023, and was funded under the UK Climate Resilience Programme.
Meet the team
 | Raquel Alegre: Raquel is a Senior Research Software Developer in UCL’s Research Software Development Group, with expertise in software engineering. She is responsible for the provision of efficient data architecture and professional coding outputs for the project. |
 | Clair Barnes: Clair is a Research Fellow in the UCL Department of Statistical Science, with expertise in data science and in the statistical analysis of climate model ensembles. She is responsible for some methodological development and for much of the analysis and data processing within the project. |
 | Chris Brierley: Chris is a Professor in the UCL Department of Geography. He is a climate scientist with expertise in the climate of both the past and the future, and in understanding uncertainty in future projections. He is Co-Investigator for the project and has oversight of aspects relating to the understanding and representation of physical processes in the models and project outputs. |
 | Richard Chandler: Richard is a Professor in the UCL Department of Statistical Science. He has extensive experience of developing and applying statistical methods for the environmental sciences. Particular interests include uncertainty analysis along with the analysis of time series and space-time data, with application areas including hydrology and the impacts of climate change. He is the Principal Investigator for the project. |
 | Amanda Ho-Lyn. Amanda is a web application developer in UCL's Research Software Development Group. She is responsible for the user interface and functionality of the project's interactive plot explorer. |
 | Ed Lowther. Ed is a Senior Research Data Scientist at UCL's Centre for Advanced Research Computing. His focus on this project has been to parallelise key components of its research software so that analysis can be run efficiently on many subsets of the source data using UCL's high-performance computing infrastructure. He also built a simple website to facilitate interrogation of the results of this work. |
 | Jamie Quinn. Jamie is a software engineer in UCL's Research Software Development Group, with interests in the climate, geophysical fluids and how software can be used to combat the climate crisis. He has been responsible for contributing some of the group's climate index calculations into the python package xclim. |
Reports and publications
Here are links to technical reports arising from the work carried out during the project, as well as conference presentations and peer-reviewed publications
Technical reports
These technical reports are available to download in PDF format, and should be cited as indicated.
- Barnes, C.R., R.E. Chandler and C.M. Brierley: Indices to be used in comparison of UKCP18 and EuroCORDEX ensembles. Technical report, UK Climate Resilience Programme project CR20-3 Enabling the use and producing improved understanding of EuroCORDEX data over the UK, March 2021 (revised July 2022). Available from https://www.ucl.ac.uk/statistics/sites/statistics/files/ukcordex-indices_v08.pdf.
- As part of the project, pre-computed values of many climate indices have been computed from the various climate model outputs across the UK. This report documents the indices that are available. The indices can be visualised using the accompanying EuroCORDEX-UK plot explorer.
- Barnes, C.R., R.E. Chandler and C.M. Brierley: Comparison of EuroCORDEX output with UKCP18 regional ensemble. Technical report, UK Climate Resilience Programme project CR20-3 Enabling the use and producing improved understanding of EuroCORDEX data over the UK, January 2022 (revised July 2022). Available from https://www.ucl.ac.uk/statistics/sites/statistics/files/evaluation_of_ukcordex_vs_ukcp18_v2.pdf.
- This report summarises the results of analyses designed (a) to compare and characterise several collections of future climate projections for the UK under Representation Concentration Pathway (RCP) 8.5, derived from multiple climate models; and (b) to evaluate the skill of the models upon which the projections are based.
- Chandler, R.E., C.R. Barnes and C.M. Brierley: Decision-relevant characterisation of uncertainty in UK climate projections. Technical report, UK Climate Resilience Programme project CR20-3 Enabling the use and producing improved understanding of EuroCORDEX data over the UK, July 2023. Available from https://www.ucl.ac.uk/statistics/sites/statistics/files/projectionuncertainty.pdf.
- This report describes the postprocessing of information from climate model ensembles, to provide probabilistic projections of future national and regional temperature and precipitation for the UK.
Conference presentations
- Identifying patterns of spatial variability within the EuroCORDEX ensemble (Session CL4.3, EGU General Assembly, Vienna, May 2022)
- Controls on projected climate extremes in two regional ensembles for the UK (Session CL5.3.3, EGU General Assembly, Vienna, May 2022 )
- Regridding and interpolation of climate data for impacts modelling – some cautionary notes (Session HS7.1, EGU General Assembly, Vienna, May 2022)
Peer-reviewed publications
- Chandler, R. E., C. R. Barnes, and C. M. Brierley (2024). Characterizing Spatial Structure in Climate Model Ensembles. J. Climate, 37, 1053–1064, doi: 10.1175/JCLI-D-23-0089.1.
- Barnes, C.R., R.E. Chandler and C.M. Brierley (2024). A comparison of regional climate projections with a range of climate sensitivities. Journal of Geophysical Research: Atmospheres, 129, e2023JD038917. doi: 10.1029/2023JD038917.
Data and software resources
As well as augmenting the existing UKCP18 archive, the project has produced a wide range of downloadable summaries of various climate indices over the UK. The augmented archive and computed summaries are available from the links below, along with software resources.
Data and summaries
- Augmented UKCP18 archive. This contains future climate projections and historical runs from a large number of global circulation models (GCMs) and regional climate models (RCMs), from the EuroCORDEX and CMIP5 ensembles. The outputs have all been cropped to the region used for the UKCP18 projections, and regridded to the UKCP18 grid. Details of this processing can be found in the help pages for the plot explorer (see below). The data are hosted by the Centre for Environmental Data Analysis (CEDA).
- EuroCORDEX-UK plot explorer. This analysis and visualisation tool is designed to allow rapid exploration of the EuroCORDEX-UK projections. Users can select climate indices, seasons and time periods of interest and can compare the various model outputs, produce maps of projections and historical biases in these indices, and quantify the dominant sources of variation and uncertainty within the projections. The plots and underlying data are downloadable directly from the plot explorer.
- Visualisations of postprocessed national and regional temperature and precipitation series. This link allows exploration of probabilistic projections obtained via statistical postprocessing of the various ensembles. The postprocessing methodology accounts for the structure of the ensembles and their relation to the real climate system (including systematic discrepancies), and attempts to provide a defensible characterisation of uncertainty. The methodology is described in Chandler et al. (in preparation - see above).
Software resources
The xclim library. xclim is a python library of functions to compute climate indices from observations or model simulations. EuroCORDEX-UK team members contributed new routines in versions 0.29.0 and 0.32.0 of the library.
TimSPEC: Time Series Postprocessing of Ensembles for Climate. This is an R package for analysing time series of climate projections, aiming to provide defensible assessments of uncertainty. It implements the methodology described in the technical report Decision-relevant characterisation of uncertainty in UK climate projections.
Example script for Ensemble Principal Pattern (EPP) analysis of simple and structured ensembles. This script reproduces the results reported in Chandler, Barnes & Brierley (2024) "Characterizing Spatial Structure in Climate Model Ensembles" (J. Climate 37(3), 1053-1064).
