A large set of potential past, present and future hydro-meteorological time series for the UK
2017
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.
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