Hydro-PE: gridded datasets of historical and future Penman-Monteith potential evaporation for the United Kingdom

Robinson, E. L.; Brown, Matthew; Kay, Alison L.; Lane, Rosanna; Chapman, Rhian; Bell, Victoria A.; Blyth, Eleanor

doi:10.5194/essd-2022-288

Cited by 7 publications

(4 citation statements)

References 37 publications

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“…These changes are consistent with the climate projections, which give wetter winters and drier and hotter summers(Murphy et al Fig. 5.2), and increased summer PE(Robinson et al 2022).…”

supporting

confidence: 90%

“… Daily 12km grids of PE are not directly available from the UKCP18 Regional projections. Instead they are calculated from other meteorological variables in a way which closely replicates MORECS (as in Robinson et al (2021Robinson et al ( , 2022, but using the bias-adjusted precipitation in the interception component). PE is only estimated for 12km 'land' RCM boxes; where PE is required for boxes classed as 'sea' in the RCM, it is copied from the nearest 12km 'land' box.…”

Section: Climate Projection-based Driving Datamentioning

confidence: 99%

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The UKSCAPE-G2G river flow and soil moisture datasets: Grid-to-Grid model estimates for the UK for historical and potential future climates

Kay

Bell

Davies

et al. 2023

Preprint

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Abstract. Appropriate adaptation planning is contingent upon information about the potential future impacts of climate change, and hydrological impact assessments are of particular importance. The UKSCAPE-G2G datasets were produced, as part of the NERC UK-SCAPE programme, to contribute to this information requirement. They use the Grid-to-Grid (G2G) national-scale hydrological model configured for both Great Britain and Northern Ireland (and the parts of the Republic of Ireland that drain to rivers in NI). Six separate datasets are provided, for two sets of driving data — one observation-based (1980–2011) and one climate projection-based (1980–2080) — for both river flows and soil moisture on 1 km x 1 km grids across GB and NI. The river flow datasets include grids of monthly mean flow, annual maxima of daily mean flow, and annual minima of 7-day mean flow (m3s-1). The soil moisture datasets are grids of monthly mean soil moisture content (m water / m soil), which should be interpreted as depth-integrated values for the whole soil column. The climate projection-based datasets are produced using data from the 12-member 12km regional climate model ensemble of the latest UK climate projections (UKCP18), which uses RCP8.5 emissions. The production of the datasets is described, along with details of the file format, and how the data should be used. Example maps are provided, as well as simple UK-wide analyses of the various outputs. These suggest potential future decreases in summer flows, annual minimum 7-day flows, and summer/autumn soil moisture, along with possible future increases in winter flows and annual maximum flows. References are given for published papers providing more detailed spatial analyses, and some further potential uses of the data are suggested.

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“…These changes are consistent with the climate projections, which give wetter winters and drier and hotter summers(Murphy et al Fig. 5.2), and increased summer PE(Robinson et al 2022).…”

supporting

confidence: 90%

Section: Climate Projection-based Driving Datamentioning

confidence: 99%

The UKSCAPE-G2G river flow and soil moisture datasets: Grid-to-Grid model estimates for the UK for historical and potential future climates

Kay

Bell

Davies

et al. 2023

Preprint

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“…The daily potential evapotranspiration (PET, mm d −1 ) data were computed from HadUK data by Brown et al. (2022) using the Penman‐Monteith equation derived in terms of specific humidity (Robinson et al., 2022).…”

Section: Datamentioning

confidence: 99%

Spatial Sensitivity of River Flooding to Changes in Climate and Land Cover Through Explainable AI

Slater,

Coxon,

Brunner

et al. 2024

Earth's Future

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Explaining the spatially variable impacts of flood‐generating mechanisms is a longstanding challenge in hydrology, with increasing and decreasing temporal flood trends often found in close regional proximity. Here, we develop a machine learning‐informed approach to unravel the drivers of seasonal flood magnitude and explain the spatial variability of their effects in a temperate climate. We employ 11 observed meteorological and land cover (LC) time series variables alongside 8 static catchment attributes to model flood magnitude in 1,268 catchments across Great Britain over four decades. We then perform a sensitivity analysis to assess how a 10% increase in precipitation, a 1°C rise in air temperature, or a 10 percentage point increase in urban or forest LC may affect flood magnitude in catchments with varying characteristics. Our simulations show that increasing precipitation and urbanization both tend to amplify flood magnitude significantly more in catchments with high baseflow contribution and low runoff ratio, which tend to have lower values of specific discharge on average. In contrast, rising air temperature (in the absence of changing precipitation) decreases flood magnitudes, with the largest effects in dry catchments with low baseflow index. Afforestation also tends to decrease floods more in catchments with low groundwater contribution, and in dry catchments in the summer. Our approach may be used to further disentangle the joint effects of multiple flood drivers in individual catchments.

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“…The data are available re-projected from the native climate model grid to a 12 km grid aligned with the GB national grid, for a synthetic 360 d year (30 d per month). The re-projected daily precipitation and daily minimum and maximum temperatures are used here, along with daily 12 km PE calculated from other meteorological variables available from the RCM ensemble (Robinson et al, 2021(Robinson et al, , 2023. The precipitation data are downscaled to 1 km using patterns of standard average annual precipitation , the PE data are copied down to 1 km, and the temperature data are downscaled to 1 km using elevation data and a lapse rate (as Kay, 2021).…”

Section: Climate Projectionsmentioning

confidence: 99%

Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections

Griffin,

Kay,

Sayers

et al. 2024

Hydrol. Earth Syst. Sci.

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Abstract. An event-based approach has been used to explore the potential effects of climate change on the spatial and temporal coherence of widespread flood events in Great Britain. Time series of daily mean river flow were generated using a gridded national-scale hydrological model (Grid-to-Grid) driven by a 12-member ensemble of regional climate projections from UK Climate Projections 2018 (UKCP18), for 30-year baseline (1980–2010) and future (2050–2080) time slices. From these, sets of widespread extreme events were extracted. The question of what defines a “widespread flood event” is discussed; here it was defined as an event exceeding an at-site 99.5th percentile (equivalent to 2 d per year) simultaneously over an area of at least 20 km2, with a maximum duration of 14 d. This resulted in a set of 14 400 widespread events: approximately 20 events per year, per ensemble member, per time slice. Overall, results have shown that events are more temporally concentrated in winter in the future time slice compared to the baseline. Distributions of event area were similar in both time slices, but the distribution of at-site return periods showed some heavier tails in the future time slice. Such information could be useful for adaptation planning and risk management for floods under climate change, but the potential future changes have to be interpreted in the context of some differences in event characteristics between the baseline climate-projection-driven model runs and an observation-driven model run. While the focus here is Great Britain, the methods and analyses described could be applied to other regions with hydrological models and climate projections of appropriate resolution.

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Hydro-PE: gridded datasets of historical and future Penman-Monteith potential evaporation for the United Kingdom

Cited by 7 publications

References 37 publications

The UKSCAPE-G2G river flow and soil moisture datasets: Grid-to-Grid model estimates for the UK for historical and potential future climates

The UKSCAPE-G2G river flow and soil moisture datasets: Grid-to-Grid model estimates for the UK for historical and potential future climates

Spatial Sensitivity of River Flooding to Changes in Climate and Land Cover Through Explainable AI

Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections

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