European precipitation connections with large-scale mean sea-level pressure (MSLP) fields

To advance understanding of hydroclimatological processes, this paper links spatiotemporal variability in gridded European precipitation and large-scale mean sea-level pressure (MSLP) time series (1957–2002) using monthly concurrent correlation. Strong negative (positive) correlation near Iceland and (the Azores) is apparent for precipitation in northwest Europe, confirming a positive North Atlantic Oscillation (NAO) association. An opposing pattern is found for southwest Europe, and the Mediterranean in winter. In the lee of mountains, MSLP correlation is lower reflecting reduced influence of westerlies on precipitation generation. Importantly, European precipitation is shown to be controlled by physically interpretable climate patterns that change in extent and position from month to month. In spring, MSLP–precipitation correlation patterns move and shrink, reaching a minimum in summer, before expanding in the autumn, and forming an NAO-like dipole in winter. These space–time shifts in correlation regions explain why fixed-point NAO indices have limited ability to resolve precipitation for some European locations and seasons

The Spatial Coherence of European Droughts – Final Report

Drought can cause serious problems across much of Europe. Many droughts are localised and short, but others are widespread and cause environmental and social effects that cross international boundaries. Some of the most important UK droughts were also significant droughts across much of Europe. Intuitively, it would seem that there may be considerable potential for developing improved drought monitoring and forecasting tools by examining the spatial coherence of droughts on a continental scale. This project has considered the potential for developing new approaches to forecasting drought by asking the following research questions: • Is there any systematic time lag between the onset and development of droughts in different parts of Europe? • Can the onset and development of droughts in some parts of Europe provide an early warning for the development of droughts in other parts of Europe, and in particular, in the UK? • Can these relationships be used to build reliable and robust operational tools for UK drought forecasting? The method, which draws on a unique archive of flow and rainfall data from across much of Europe, involved the following steps. 1. Calculate a normalised deficiency index for each site – a measure of drought that allows comparison between locations with different climatological and hydrological regimes, and between different seasons 2. Group catchments with similar drought characteristics into regions 3. Develop standardised flow and rainfall deficiency indices for these regions 4. Analyse relationships between regions and develop statistical models to predict drought. Twenty-four homogenous regions were identified across Europe; catchments within these groups frequently experience simultaneous streamflow deficiencies. Four distinct geographical regions emerged in the UK. A further group, comprising very slow-responding catchments (Base Flow Index > 0.8), was identified in southeast England. For each of these regions, time series of regional streamflow and rainfall deficits were defined and a catalogue of regional drought severity developed, spanning 1901 – 2005 for meteorological droughts, and 1961 – 2005 for hydrological droughts. This enabled a characterisation of major drought periods, in terms of duration, seasonality and spatial coherence in the various regions. This drought catalogue is a major deliverable of this project, and will be of considerable practical utility for drought management and future research in the UK and in Europe. For major post-1961 streamflow droughts, a comprehensive description of the extent and spatio-temporal development of the drought was provided. A standalone publication has been produced, which illustrates the evolution of streamflow and rainfall anomalies, along with climatic drivers and large-scale atmospheric circulation anomalies for major droughts (e.g. 1975 – 76; 1988 – 1992). From an appraisal of these events, it is clear that most droughts appear to have different characteristics, in terms of their duration, spatial coherence and seasonality. For example, a contrast was found between the 1976 drought, which was spatially consistent across much of Europe and was combined with a rainfall deficiency the preceding winter and a heat wave in the summer, and the 1995-1997 drought, which was interspersed by wet episodes and had little long-lasting spatial coherence over Europe. In most historical events, the UK experienced drought simultaneously with other European regions, or earlier; there was little evidence of any systematic lag time which could be readily exploited in the development of early warning systems for the UK based on conditions in other parts of Europe. An exploratory data analysis was then carried out, to determine whether there are relationships in the drought indicators which could be exploited to develop forecasting tools. Correlation analysis, multidimensional scaling and statistical modelling were applied to find relationships, which were generally fairly weak. Low correlations exist between regional drought deficiency time series of different regions, and the correlation patterns for hydrological and meteorological droughts are similar, albeit slightly higher for the latter. Correlations with the rest of Europe are stronger in winter than in summer for northern and western Britain, but are of similar magnitude all year round for southeast England. Although a relationship was identified between the length of a UK drought and the number of regions contemporaneously experiencing drought elsewhere in Europe, it was found that this relationship was not statistically significant. Following these exploratory analyses, statistical models were built for each UK region, which predict the number of drought months that may occur in the next 6 months. Predictions are based on streamflow deficiencies in other European regions, so the models essentially predict ‘drought from drought’ – i.e. they use the spatial coherence of anomalies to derive forecasts for the UK based on deficiencies on the continent. The models forecast droughts in groundwater-dominated catchments in southeast England reasonably well. In northwest Britain, however, the predictive capability is poor. Importantly, the models have some significant benefits when compared to previous seasonal forecasting studies – in particular, the approach is based on large regions, rather than being ‘tuned’ to particular catchments, and they enable forecasting of winter anomalies rather than just summer flows. Furthermore, the models perform reasonably well at forecasting the cessation of drought conditions. These attributes mean that the models could potentially be of high utility during long, multi-season drought events, to determine whether a drought is likely to intensify or to diminish. Whilst the predictive capacity is modest in some regions, the models clearly have potential for application in UK drought management, although there are also important practical considerations – in particular, the need for timely data supply from across Europe – which would need to be examined in further research before they could evolve into an operational tool. Further analysis concentrated on attempting to explain observed patterns of spatial coherence, by linking drought indicators to large scale modes of atmospheric variability (e.g. the North Atlantic Oscillation and the East Atlantic-West Russia pattern). In some regions and some seasons, these predictors clearly play an important role in determining the spatial coherence of droughts. Whilst their predictive capability is relatively weak at present, there is undoubtedly scope for refining these relationships into tools for monitoring and providing indicative forecasts. An advantage of this approach is that some climatological indicators are routinely forecast (although the modest skill levels are a further obstacle to application at present). The regional drought indicators are shown to be powerful tools for illustrating the dynamics of rainfall and streamflow deficiencies. They could therefore find application in UK and European drought monitoring systems. Again, there would be important practical limitations to consider, and further research would be needed to optimise the indicators for use in monitoring. However, they could potentially fill an important gap; existing monitoring European drought monitoring systems lack a streamflow component, whilst UK approaches (e.g. CEH’s monthly Hydrological Summaries) consider runoff deficiencies but do not use any metrics tailored specifically to drought

Probabilistic estimates of climate change impacts on UK water resources

Climate change will increase temperatures and change rainfall across the UK. In turn, this will modify patterns of river flow and groundwater recharge, affecting the availability of water. There have been many studies of the impact of climate change on river flows in the UK, but coverage has been uneven and methods have varied. Consequently, it has been very difficult to compare different locations and hard to identify appropriate adaptation responses

Low flow response surfaces for drought decision support: a case study from the UK

Droughts are complex natural hazards, and planning future management is complicated by the difficulty of projecting future drought and low flow conditions. This paper demonstrates the use of a response surface approach to explore the hydrological behavior of catchments under a range of possible future conditions. Choosing appropriate hydrological metrics ensures that the response surfaces are relevant to decision-making. Examples from two contrasting English catchments show how low flows in different catchments respond to changes in rainfall and temperature. In an upland western catchment, the Mint, low flows respond most to rainfall and temperature changes in summer, but in the groundwater dominated catchment of the Thet, changes in spring rainfall have the biggest impact on summer flows. Response surfaces are useful for understanding long-term changes, such as those projected in climate projections, but they may also prove useful in drought event management, where possible future conditions can be plotted onto the surface to understand the range of conditions the manager faces. Developing effective response surfaces requires considerable involvement and learning from catchment decision-makers at an early stage, and this should be considered in any planned application

Assessing the impact of climate change and extreme value uncertainty to extreme flows across Great Britain

Floods are the most common and widely distributed natural risk, causing over £1 billion of damage per year in the UK as a result of recent events. Climatic projections predict an increase in flood risk; it becomes urgent to assess climate change impact on extreme flows, and evaluate uncertainties related to these projections. This paper aims to assess the changes in extreme runoff for the 1:100 year return period across Great Britain as a result of climate change using the Future Flows Hydrology database. The Generalised Extreme Value (GEV) and Generalised Pareto (GP) models are automatically fitted for 11‐member ensemble flow series available for the baseline and the 2080s. The analysis evaluates the uncertainty related to the Extreme Value (EV) and climate model parameters. Results suggest that GP and GEV give similar runoff estimates and uncertainties. From the baseline to the 2080s, increasing estimate and uncertainties is evident in east England. With the GEV the uncertainty attributed to the climate model parameters is greater than for the GP (around 60% and 40% of the total uncertainty, respectively). This shows that when fitting both EV models, the uncertainty related to their parameters has to be accounted for to assess extreme runoffs

Historical gridded reconstruction of potential evapotranspiration for the UK

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

Bias correction of daily precipitation simulated by a regional climate model: a comparison of methods

Quantifying the effects of future changes in the frequency of precipitation extremes is a key challenge in assessing the vulnerability of hydrological systems to climate change but is difficult as climate models do not always accurately simulate daily precipitation. This article compares the performance of four published techniques used to reduce the bias in a regional climate model precipitation output: (1) linear, (2) nonlinear, (3) γ -based quantile mapping and (4) empirical quantile mapping. Overall performance and sensitivity to the choice of calibration period were tested by calculating the errors in the first four statistical moments of generated daily precipitation time series and using a cross-validation technique. The study compared the 1961–2005 precipitation time series from the regional climate model HadRM3.0-PPE-UK (unperturbed version) with gridded daily precipitation time series derived from rain gauges for seven catchments spread throughout Great Britain. We found that while the first and second moments of the precipitation frequency distribution can be corrected robustly, correction of the third and fourth moments of the distribution is much more sensitive to the choice of bias correction procedure and to the selection of a particular calibration period. Overall, our results demonstrate that, if both precipitation data sets can be approximated by a γ -distribution, the γ -based quantilemapping technique offers the best combination of accuracy and robustness. In circumstances where precipitation data sets cannot adequately be approximated using a γ -distribution, the nonlinear method is more effective at reducing the bias, but the linear method is least sensitive to the choice of calibration period. The empirical quantile mapping method can be highly accurate, but results were very sensitive to the choice of calibration time period. However, it should be borne in mind that bias correction introduces additional uncertainties, which are greater for higher order moments

Scoping study for precipitation downscaling and bias-correction

Various methods exist for correcting biases in climate model precipitation data. This study has investigated four of these bias-correction methods, here called linear, non-linear, gamma and empirical, and extensively tested their performance and suitability for biascorrecting daily precipitation outputs from a Regional Climate Model (RCM) for use as inputs to hydrological models over six test regions spanning the Great Britain. The RCM daily precipitation data were taken from the unperturbed variant of the Met Office Hadley Centre Regional Model Perturbed Physics Ensemble (HadRM3-PPE-UK), and observed daily precipitation data were taken from the Continuous Estimation of River Flows gridded precipitation dataset. Spatial downscaling (re-gridding) and correction of the fraction of rain-days were undertaken as pre-processing steps before the bias-correction procedure, which translated the RCM data from a 0.22° grid sca le to the 1 km grid scale of the observed dataset. Re-sampling tests were used to assess the performance of the bias-correction methods in terms of the first four statistical moments, and cumulative distribution functions (cdfs) were produced to compare the distribution of the bias-corrected precipitation with respect to the observed and pre-processed RCM precipitation. We found that whilst the first and second moments of the precipitation frequency distribution can be corrected robustly, correction of the third and fourth moments of the distribution is much more sensitive to the choice of biascorrection procedure and to the selection of a particular calibration period. Overall, our results demonstrate that, if both precipitation datasets can be approximated by a gamma distribution, the gamma-based quantile-mapping technique offers the best combination of accuracy and robustness. In circumstances where precipitation datasets cannot adequately be approximated using a gamma distribution, the non-linear method is more effective at reducing the bias but the linear method is least sensitive to the choice of calibration period. The empirical quantile mapping method can be highly accurate, but results were very sensitive to the choice of calibration time period. Examination of the seasonal variation of the non-linear bias-correction factors showed that the bias-correction applied to the HadRM3 daily precipitation varied with season, location, topography and precipitation intensity, suggesting that the method is capable of reproducing many features of the complex spatial and temporal patterns of UK daily precipitation. Taking the known limitations into account this study concluded that the gamma-based quantile-mapping technique is the most suitable for bias-correcting daily HadRM3 precipitation for use in hydrological modelling in the UK

Evaluation of global impact models' ability to reproduce runoff characteristics over the central United States

The central United States experiences a wide array of hydrological extremes, with the 1993, 2008, 2013, and 2014 flooding events and the 1988 and 2012 droughts representing some of the most recent extremes, and is an area where water availability is critical for agricultural production. This study aims to evaluate the ability of a set of global impact models (GIMs) from the Water Model Intercomparison Project to reproduce the regional hydrology of the central United States for the period 1963–2001. Hydrological indices describing annual daily maximum, medium and minimum flow, and their timing are extracted from both modeled daily runoff data by nine GIMs and from observed daily streamflow measured at 252 river gauges. We compare trend patterns for these indices, and their ability to capture runoff volume differences for the 1988 drought and 1993 flood. In addition, we use a subset of 128 gauges and corresponding grid cells to perform a detailed evaluation of the models on a gauge-to-grid cell basis. Results indicate that these GIMs capture the overall trends in high, medium, and low flows well. However, the models differ from observations with respect to the timing of high and medium flows. More specifically, GIMs that only include water balance tend to be closer to the observations than GIMs that also include the energy balance. In general, as it would be expected, the performance of the GIMs is the best when describing medium flows, as opposed to the two ends of the runoff spectrum. With regards to low flows, some of the GIMs have considerably large pools of zeros or low values in their time series, undermining their ability in capturing low flow characteristics and weakening the ensemble's output. Overall, this study provides a valuable examination of the capability of GIMs to reproduce observed regional hydrology over a range of quantities for the central United States

Demonstrating the utility of a drought termination framework: prospects for groundwater level recovery in England and Wales in 2018 or beyond

During prolonged droughts, information is needed about when and how the extreme event is likely to terminate. A drought termination framework based on historical data comprising current rate and historical ensemble approaches is presented here for assessing the prospects of groundwater level recovery. The current rate approach is evaluated across all initialisation months in the historical record and provides reasonable estimates for the duration of recovery from relatively severe groundwater level deficiencies in some slowly responding boreholes. The utility of the framework is demonstrated through a near-real-time application to 30 groundwater boreholes in England and Wales from October 2017 onwards. Recovery during winter 2017/18 was considered unlikely, as some aquifers required increases in groundwater levels that have occurred seldom, if ever before, in long historical records. Data to February 2018 confirmed the success of these pre-winter outlooks. Recovery by mid- to late-2018 or beyond was more likely; slow rates of recovery by October 2017 and increasing return periods of effective rainfall required for recovery over timeframes in the summer half-year underlined the importance of winter rainfall and suggested that the historical ensemble may underestimate the duration of recovery. There was moderate confidence for a delay in recovery beyond the end of 2018 in some slowly responding Chalk boreholes in south-central and eastern England. There is considerable potential for the transferability of the drought termination framework beyond the UK wherever there are sufficient historical data. The two approaches provide limited information in distinctly different circumstances and their relevance and value may differ in space and time, suggesting their complimentary use as the most robust way to incorporate information on the prospects for groundwater level recovery into existing seasonal forecasting services, supporting decision-making by water managers during prolonged droughts