CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological and other applications

Keller, Virginie; Tanguy, Maliko; Prosdocimi, Ilaria; Terry, Julie A.; Hitt, Olivia; Cole, Steven J.; Fry, Matthew; Morris, D.; Dixon, Harry

doi:10.5194/essd-7-143-2015

Cited by 111 publications

(109 citation statements)

References 21 publications

(18 reference statements)

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“…Soil moisture exhibits a few relevant characteristics: first, it exhibits memory of typically a few weeks to months (e.g. Koster and Suarez, 2001) and, therefore, one may want to ensure that this memory is not lost in the stitching processthis may be particularly critical in the case of droughts. Second, the temporal evolution of soil moisture is mainly driven by precipitation minus evapotranspiration (P −E), i.e.…”

Section: Generation Of Continuous Time Series From Single Yearsmentioning

confidence: 99%

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

Guillod

Jones

Dadson

et al. 2018

Hydrol. Earth Syst. Sci.

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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 riskbased 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 , (ii) five nearfuture scenarios (2020-2049) and (iii) five far-future scenarios . 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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Section: Generation Of Continuous Time Series From Single Yearsmentioning

confidence: 99%

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

Guillod

Jones

Dadson

et al. 2018

Hydrol. Earth Syst. Sci.

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“…P was retrieved from the 1 km gridded CEH-GEAR dataset (Keller et al, 2015;Tanguy et al, 2016) between 1961 and 2015 for the UK. ETp according to Penman-Monteith for FAO-defined well-watered grass was 5 retrieved from the 1 km gridded CHESS-PE dataset (Robinson et al, , 2017 between 1961 and 2015 for catchments in Great Britain.…”

Section: Datamentioning

confidence: 99%

Benchmarking Ensemble Streamflow Prediction skill in the UK

Harrigan¹,

Smith²,

Parry³

et al. 2017

Preprint

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Abstract. Skilful hydrological forecasts at sub-seasonal to seasonal lead times would be extremely beneficial for decisionmaking in water resources management, hydropower operations, and agriculture, especially during drought conditions. Ensemble Streamflow Prediction (ESP) is a well-established method for generating an ensemble of streamflow forecasts in 10 the absence of skilful future meteorological predictions, instead using Initial Hydrological Conditions (IHCs), such as soil moisture, groundwater, and snow, as the source of skill. We benchmark when and where the ESP method is skilful across a diverse sample of 314 catchments in the UK and explore the relationship between catchment storage and ESP skill. The GR4J hydrological model was forced with historic climate sequences to produce 51-member ensemble of streamflow hindcasts. We evaluated forecast skill seamlessly from lead times of 1-day to 12-months initialised at the first of each month over a 50-year 15 hindcast period from 1965-2015. Results show ESP was skilful against a climatology benchmark forecast in the majority of catchments across all lead times up to a year ahead, but the degree of skill was strongly conditional on lead time, forecast initialisation month, and individual catchment location and storage properties. UK-wide mean ESP skill decays exponentially as a function of lead time with mean squared error skill scores across the year of 0.839, 0.303, and 0.179 for 1-day, 1-month, and 3-month lead times, respectively. However, skill was not uniform across all initialisation months. For lead times up to 1-20 month, ESP skill was higher than average when initialised in summer and lower in winter, whereas for longer seasonal and annual lead times skill was highest when initialised in autumn and winter months and lowest in April. ESP is most skilful in the south and east of the UK, where slower responding catchments with higher soil moisture and groundwater storage are mainly located; correlation between catchment Baseflow Index (BFI) and ESP skill was very strong ( = 0.896 at 1-month lead time). This is in contrast to the more highly responsive catchments in the north and west which are generally not skilful 25 at seasonal lead times. Overall, this work provides a scientifically defensible justification for when and where use of such a relatively simple forecasting approach is appropriate in the UK and creates a low cost benchmark against which potential skill improvements from more sophisticated hydro-meteorological ensemble prediction systems can be judged.Hydrol. Earth Syst. Sci. Discuss., https://doi

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“…This database provides all the required surface variables to run JULES (precipitation, input longwave and shortwave radiation, air temperature, specific humidity, 25 wind speed and pressure) at 1 km 2 spatial resolution for Great Britain and daily time resolution. The precipitation data in CHESSmet are gridded estimates of daily rainfall from gauge stations (CEH-GEAR; Keller et al, 2015;Tanguy et al, 2014), whereas the rest of the variables are interpolated from the observation-based coarser resolution MORECS dataset (Hough and Jones, 1997;Thompson et al, 1981), taking into account topographic information to disaggregate to the finer scale (Robinson et al, 2017b). …”

Section: Ancillary and Driving Data 10mentioning

confidence: 99%

“…5 The island of Great Britain represents an ideal platform to tackle the runoff generation in LSMs as it presents diverse climatic, topographic and geological characteristics within its area, and has a comprehensive set of river flow gauge stations: National River Flow Archive (NRFA), UK. The differences in precipitation are high and show a clear west-east and north-south contrast, with yearly means above 10 mm d -1 in western Scotland and below 2 mm d -1 in the southeast of England (CEH-GEAR dataset; Keller et al, 2015). Furthermore, regional precipitation regimes in the island are also very contrasting, with regional mean monthly 10 precipitation varying between 3 and 5 mm d -1 in Scotland and Wales, whereas in the English lowlands (Southeast) the mean monthly precipitation varies between 1.5 and 2.5 mm d -1 (Robinson et al, 2017b).…”

Section: Introductionmentioning

confidence: 99%

Improving river flow generation over Great Britain in a land surface model required for coupled land-atmosphere interactions

Torre

Blyth

Weedon

2018

Preprint

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Abstract. Land surface models (LSMs) represent terrestrial hydrology in weather and climate modelling operational systems and research studies. Using river flow observations from gauge stations, we study the capability of the Joint UK Land Environment Simulator (JULES) LSM to simulate river flow over 13 catchments in Great Britain, each representing different climatic and topographic characteristics at the 1 km 2 spatial resolution. A series of tests, carried out to identify where the model results are 10 sensitive to the scheme and parameters chosen for runoff production, suggests that different catchments require different parameters and even different runoff schemes to produce the best results. From these results, we introduce a new topographical parametrization that produces the best daily river flow results (in terms of Nash-Sutcliffe efficiency and mean bias) for all 13 catchments. The new parametrization introduces a dependency on terrain slope, constraining surface runoff production to wet soil conditions over flatter regions (like the Thames catchment; Nash-Sutcliffe efficiency above 0.8), whereas over steeper regions the model produces surface 15 runoff for every rainfall event regardless of the soil wetness state. This new parametrization improves the model capability in regional (Great Britain wide) assessments. The new choice of parameters is reinforced by examining the amplitude and phase of the modelled versus observed river flows, via cross-spectral analysis for time scales longer than daily.

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CEH-GEAR: 1 km resolution daily and monthly areal rainfall estimates for the UK for hydrological and other applications

Cited by 111 publications

References 21 publications

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

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

Benchmarking Ensemble Streamflow Prediction skill in the UK

Improving river flow generation over Great Britain in a land surface model required for coupled land-atmosphere interactions

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