Journal cover Journal topic
Earth System Science Data The Data Publishing Journal
Earth Syst. Sci. Data, 10, 951-968, 2018
https://doi.org/10.5194/essd-10-951-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Review article
01 Jun 2018
Historical gridded reconstruction of potential evapotranspiration for the UK
Maliko Tanguy1, Christel Prudhomme2,3,1, Katie Smith1, and Jamie Hannaford1 1NERC Centre for Ecology & Hydrology, Maclean Building, Benson Lane, Crowmarsh Gifford, Wallingford, Oxon, OX10 8BB, UK
2European Centre for Medium-Range Weather Forecasts, Shinfield Road, Reading, RG2 9AX, UK
3Department of Geography, Loughborough University, Loughborough, LE11 3TU, UK
Abstract. Potential evapotranspiration (PET) is a necessary input data for most hydrological models and is often needed at a daily time step. An accurate estimation of PET requires many input climate variables which are, in most cases, not available prior to the 1960s for the UK, nor indeed most parts of the world. Therefore, when applying hydrological models to earlier periods, modellers have to rely on PET estimations derived from simplified methods. Given that only monthly observed temperature data is readily available for the late 19th and early 20th century at a national scale for the UK, the objective of this work was to derive the best possible UK-wide gridded PET dataset from the limited data available.

To that end, firstly, a combination of (i) seven temperature-based PET equations, (ii) four different calibration approaches and (iii) seven input temperature data were evaluated. For this evaluation, a gridded daily PET product based on the physically based Penman–Monteith equation (the CHESS PET dataset) was used, the rationale being that this provides a reliable ground truth PET dataset for evaluation purposes, given that no directly observed, distributed PET datasets exist. The performance of the models was also compared to a naïve method, which is defined as the simplest possible estimation of PET in the absence of any available climate data. The naïve method used in this study is the CHESS PET daily long-term average (the period from 1961 to 1990 was chosen), or CHESS-PET daily climatology.

The analysis revealed that the type of calibration and the input temperature dataset had only a minor effect on the accuracy of the PET estimations at catchment scale. From the seven equations tested, only the calibrated version of the McGuinness–Bordne equation was able to outperform the naïve method and was therefore used to derive the gridded, reconstructed dataset. The equation was calibrated using 43 catchments across Great Britain.

The dataset produced is a 5 km gridded PET dataset for the period 1891 to 2015, using the Met Office 5 km monthly gridded temperature data available for that time period as input data for the PET equation. The dataset includes daily and monthly PET grids and is complemented with a suite of mapped performance metrics to help users assess the quality of the data spatially.

This dataset is expected to be particularly valuable as input to hydrological models for any catchment in the UK.

The data can be accessed at https://doi.org/10.5285/17b9c4f7-1c30-4b6f-b2fe-f7780159939c.


Citation: Tanguy, M., Prudhomme, C., Smith, K., and Hannaford, J.: Historical gridded reconstruction of potential evapotranspiration for the UK, Earth Syst. Sci. Data, 10, 951-968, https://doi.org/10.5194/essd-10-951-2018, 2018.
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Short summary
Potential evapotranspiration (PET) is necessary input data for most hydrological models, used to simulate river flows. To reconstruct PET prior to the 1960s, simplified methods are needed because of lack of climate data required for complex methods. We found that the McGuinness–Bordne PET equation, which only needs temperature as input data, works best for the UK provided it is calibrated for local conditions. This method was used to produce a 5 km gridded PET dataset for the UK for 1891–2015.
Potential evapotranspiration (PET) is necessary input data for most hydrological models, used to...
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