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Hydrol. Earth Syst. Sci., 22, 611-634, 2018
https://doi.org/10.5194/hess-22-611-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
25 Jan 2018
A large set of potential past, present and future hydro-meteorological time series for the UK
Benoit P. Guillod1,a,b, Richard G. Jones2,3, Simon J. Dadson3, Gemma Coxon4, Gianbattista Bussi3, James Freer4, Alison L. Kay5, Neil R. Massey1, Sarah N. Sparrow6, David C. H. Wallom6, Myles R. Allen1, and Jim W. Hall1 1Environmental Change Institute, University of Oxford, Oxford, UK
2Met Office Hadley Centre, Exeter, UK
3School of Geography and the Environment, University of Oxford, Oxford, UK
4Geographical Sciences, University of Bristol, Bristol, UK
5Centre for Ecology and Hydrology, Wallingford, UK
6Oxford e-Research Centre, University of Oxford, Oxford, UK
acurrently at: Institute for Environmental Decisions, ETH Zurich, Zurich, Switzerland
bcurrently at: Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Abstract. Hydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900–2006), (ii) five near-future scenarios (2020–2049) and (iii) five far-future scenarios (2070–2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months) and shorter-duration high precipitation (1–30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions, highlighting the need for appropriate adaptation measures. Overall, the presented dataset is a useful tool for assessing the risk associated with drought and more generally with hydro-meteorological extremes in the UK.

Citation: Guillod, B. P., Jones, R. G., Dadson, S. J., Coxon, G., Bussi, G., Freer, J., Kay, A. L., Massey, N. R., Sparrow, S. N., Wallom, D. C. H., Allen, M. R., and Hall, J. W.: A large set of potential past, present and future hydro-meteorological time series for the UK, Hydrol. Earth Syst. Sci., 22, 611-634, https://doi.org/10.5194/hess-22-611-2018, 2018.
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Short summary
Assessing the potential impacts of extreme events such as drought and flood requires large datasets of such events, especially when looking at the most severe and rare events. Using a state-of-the-art climate modelling infrastructure that is simulating large numbers of weather time series on volunteers' computers, we generate such a large dataset for the United Kingdom. The dataset covers the recent past (1900–2006) as well as two future time periods (2030s and 2080s).
Assessing the potential impacts of extreme events such as drought and flood requires large...
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