Historical gridded reconstruction of potential evapotranspiration for the UK

Abstract

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.Published by Copernicus Publications.

Historic hydrological droughts 1891–2015: systematic characterisation for a diverse set of catchments across the UK

“…The rainfall data are described in Hollis et al (2019) and available from the UK Met Office (2018, 2019). The hydrological model required daily rainfall and potential evapotranspiration (PET) as inputs, the latter of which was calculated using newly recovered temperature data (Tanguy et al, 2018). The hydrological model employed was the GR4J daily lumped rainfall-runoff model (Perrin et al, 2003), implemented using the "airGR" R package version 1.0.2 (Coron et al, 2017) as described by Smith et al ( , 2019.…”

“…More recently, there has been a shift towards stochastic approaches to test the resilience of systems to droughts that are worse than those observed in the recent past (Anderton et al, 2015;Water UK, 2016). These approaches recognise the need to go beyond the envelope of past variability, not just in the context of climate change but given short observational records, wherein it may be expected that "record-breaking" events will occur due to chance alone (as has been described for flooding events, for example in Thompson et al, 2017, andProsdocimi, 2018). However, these stochastic approaches still require benchmarking against historic data, and where longer historic data are available the increased sample size increases the confidence in synthetic events generated using historical training data.…”

CAMELS-GB: Hydrometeorological time series and landscape attributes for 671 catchments in Great Britain

“…For example, there can be significant variability in the calculation of PET, depending on the methods and 530 assumptions used (e.g. Tanguy et al, 2018) and here we have used a PET estimate where canopy interception is not accounted for. Interception is an important component of the water cycle in GB, which experiences a large amount of low to moderate rainfall intensities (Blyth et al, 2019), thus using the CHESS PETI estimate instead would increase the aridity index above one in some locations.…”

Reassessing the observational evidence for nitrogen deposition impacts in acid grassland: Spatial Bayesian linear models indicate small and ambiguous effects on species richness

“…total acid deposition is given by SEA04 as total N plus total S; likewise, total N is normally calculated as reduced N plus oxidised N), for this reason, we only consider total N deposition and total S deposition as pollutant covariates in our models (Table 1). For SEA04 model 2, four of the available climate variables chosen to match the analysis of Stevens et al (2004) had very high pairwise linear correlations (all with r > 0.75); these variables (mean annual potential evapotranspiration (PET), mean annual daily maximum and minimum temperatures, 1996-2006, all from the MARS dataset (see ; and mean annual potential evapotranspiration from Tanguy et al (2018)) were combined using PCA and the first two principle components of this ordination used in their place (Table 1). PET data were unavailable for 3 sites (15 plots) in SEA04 (all on Lundy Island, England, 51° 10′ 57.82″ N, 4° 40′ 11.46″ W), and these values were imputed as the mean PET value across the remainder of the SEA04 dataset prior to PCA.…”