Damage from flooding in the winter and fall seasons has been widespread in the United Kingdom (UK) and Western Europe over recent decades. Here we show that winter flood events in the UK are ...connected to Atmospheric Rivers (ARs), narrow ribbons along which a large flux of moisture is transported from the subtropics to the mid‐latitudes. Combining river flow records with rainfall measurements, satellite data and model simulations, we demonstrate that ARs occur simultaneously with the 10 largest winter flood events since 1970 in a range of British river basins, suggesting that ARs are persistently critical in explaining extreme winter flooding in the UK. Understanding the physical processes that determine the persistence of AR events will be of importance in assessing the risk of future flooding over north‐western Europe and other mid‐latitude regions.
Key Points
Linked a damaging UK flooding event with AR occurrence
Linked persistent ARs with the top 10 floods in a range of UK basins
Shown the atmospheric circulation that leads to AR occurrence in western Europe
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•Novel subsampling approach for timeseries inputs in power system models is introduced.•Allows use of multiple decades of demand & weather data in power system planning.•Method’s ...performance is superior to established timeseries reduction approaches.•Approach applicable to wide class of optimisation-based power system planning models.
Recent studies indicate that the effects of inter-annual climate-based variability in power system planning are significant and that long samples of demand & weather data (spanning multiple decades) should be considered. At the same time, modelling renewable generation such as solar and wind requires high temporal resolution to capture fluctuations in output levels. In many realistic power system models, using long samples at high temporal resolution is computationally unfeasible. This paper introduces a novel subsampling approach, referred to as importance subsampling, allowing the use of multiple decades of demand & weather data in power system planning models at reduced computational cost. The methodology can be applied in a wide class of optimisation-based power system simulations. A test case is performed on a model of the United Kingdom created using the open-source modelling framework Calliope and 36 years of hourly demand and wind data. Standard data reduction approaches such as using individual years or clustering into representative days lead to significant errors in estimates of optimal system design. Furthermore, the resultant power systems lead to supply capacity shortages, raising questions of generation capacity adequacy. In contrast, importance subsampling leads to accurate estimates of optimal system design at greatly reduced computational cost, with resultant power systems able to meet demand across all 36 years of demand & weather scenarios.
Abstract
Power system resource adequacy (RA), or its ability to continually balance energy supply and demand, underpins human and economic health. How meteorology affects RA and RA failures, ...particularly with increasing penetrations of renewables, is poorly understood. We characterize large-scale circulation patterns that drive RA failures in the Western U.S. at increasing wind and solar penetrations by integrating power system and synoptic meteorology methods. At up to 60% renewable penetration and across analyzed weather years, three high pressure patterns drive nearly all RA failures. The highest pressure anomaly is the dominant driver, accounting for 20-100% of risk hours and 43-100% of cumulative risk at 60% renewable penetration. The three high pressure patterns exhibit positive surface temperature anomalies, mixed surface solar radiation anomalies, and negative wind speed anomalies across our region, which collectively increase demand and decrease supply. Our characterized meteorological drivers align with meteorology during the California 2020 rolling blackouts, indicating continued vulnerability of power systems to these impactful weather patterns as renewables grow.
Renewable electricity is a key enabling step in the decarbonization of energy. Europe is at the forefront of renewable deployment and this has dramatically increased the weather sensitivity of the ...continent's power systems. Despite the importance of weather to energy systems, and widespread interest from both academia and industry, the meteorological drivers of European power systems remain difficult to identify and are poorly understood. The present study presents a new and generally applicable approach, targeted circulation types (TCTs). In contrast to standard meteorological weather‐regime or circulation‐typing schemes, TCTs convolve the weather sensitivity of an impacted system of interest (in this case, the electricity system) with the intrinsic structures of the atmospheric circulation to identify its meteorological drivers. A new 38 year reconstruction of daily electricity demand and renewable supply across Europe is used to identify the winter large‐scale circulation patterns of most interest to the European electricity grid. TCTs provide greater explanatory power for power system variability and extremes compared with standard meteorological typing. Two new pairs of atmospheric patterns are highlighted, both of which have marked and extensive impacts on the European power system. The first pair resembles the meridional surface pressure dipole of the North Atlantic Oscillation (NAO), but shifted eastward into Europe and noticeably strengthened, while the second pair is weaker and corresponds to surface pressure anomalies over Central Southern and Eastern Europe. While these gross qualitative patterns are robust features of the present European power systems, the detailed circulation structures are strongly affected by the amount and location of renewables installed.
Despite widespread interest, the meteorological drivers of highly renewable European power systems remain poorly understood. A new technique, targeted circulation types (TCTs), provides much greater explanatory and predictive power for power system variability and extremes compared with standard meteorological “weather regimes”. The atmospheric patterns revealed highlight the importance of a meridional surface pressure dipole with similarities to the North Atlantic Oscillation (NAO), but shifted eastward and noticeably strengthened, leading to more marked and extensive weather impacts across the European power system.
Large‐scale, quasi‐stationary atmospheric waves (QSWs) have long been known to be associated with weather extremes such as the European heatwave in 2003. There is much debate in the scientific ...literature as to whether QSW activity may increase under a changing climate, providing a strong motivation for developing a better understanding of the behaviour and drivers of QSWs. This paper presents the first steps in this regard: the development of a robust objective method for a simple identification and characterization of these waves. A clear connection between QSWs and European weather and extreme events is confirmed for all seasons, indicating that blocking anti‐cyclones are often part of a broader‐scale wave pattern.
Investigation of the QSW climatology in the Northern Hemisphere reveals that wave activity is typically strongest in midlatitudes, particularly at the exit of the Atlantic and Pacific storm track, with weaker intensities in summer. In general, the structure of individual QSW events tends to follow the climatological pattern, except in winter where the strongest and most persistent QSWs are typically shifted polewards, indicating a distinct evolution of the “strongest” QSW events. Modes of interannual variability are calculated to better understand their importance and connection to European temperatures and to identify relevant QSW patterns. This analysis highlights that European winter temperatures are strongly associated with the meridional location of QSW activity whereas high European summer temperatures are associated with increases in the overall intensity of midlatitude QSW activity.
QSWs are shown to be strongly connected to commonly used indices to describe the large‐scale atmospheric circulation (NAO, AO, Niño 3.4, PNA) but offer a more direct link to understanding their impact on regional weather events. It is therefore hoped that objective identification of QSWs will provide a useful new viewpoint for interpreting large‐scale weather alongside more traditional measures.
We apply a robust objective method for a simple identification and characterization of large‐scale, quasi‐stationary waves (QSWs) to ERA‐Interim reanalysis. This reveals a strong connection between QSWs and extreme events, as shown here for a QSW composite for the 30 warmest European temperature events. We further investigate the basic climatological features of these waves and highlight the most relevant QSW patterns for European temperature anomalies. Such patterns can further be linked to global pattern indices such as NAO, PNA, etc.
Within the warm conveyor belt of extra-tropical cyclones, atmospheric rivers (ARs) are the key synoptic features which deliver the majority of poleward water vapour transport, and are associated with ...episodes of heavy and prolonged rainfall. ARs are responsible for many of the largest winter floods in the mid-latitudes resulting in major socioeconomic losses; for example, the loss from United Kingdom (UK) flooding in summer/winter 2012 is estimated to be about $1.6 billion in damages. Given the well-established link between ARs and peak river flows for the present day, assessing how ARs could respond under future climate projections is of importance in gauging future impacts from flooding. We show that North Atlantic ARs are projected to become stronger and more numerous in the future scenarios of multiple simulations from five state-of-the-art global climate models (GCMs) in the fifth Climate Model Intercomparison Project (CMIP5). The increased water vapour transport in projected ARs implies a greater risk of higher rainfall totals and therefore larger winter floods in Britain, with increased AR frequency leading to more flood episodes. In the high emissions scenario (RCP8.5) for 2074-2099 there is an approximate doubling of AR frequency in the five GCMs. Our results suggest that the projected change in ARs is predominantly a thermodynamic response to warming resulting from anthropogenic radiative forcing.
Abstract
In 2013, the European Network of Transmission System Operators (TSOs) for electricity (ENTSO-E) created the Pan-European Climate Database (PECD), a tool that has underpinned most studies ...conducted by TSOs ever since. So far, the different versions of the PECD have used so-called modern-era ‘reanalysis’ products that represent a gridded amalgamation of historical conditions from observations. However, scientific evidence suggests, and recent European regulation requires, that power system adequacy studies should take climate change into account when estimating the future potential of variable renewable resources, such as wind, solar and hydro, and the impact of temperature on electricity demand. This paper explains the need for future climate data in energy systems studies and provides high-level recommendations for building a future-proof reference climate dataset for TSOs, not just in Europe, but also globally.
Wind power generation in Great Britain has increased markedly in recent years. However due to its intermittency its ability to provide power during periods of high electricity demand has been ...questioned. Here we characterise the winter relationship between electricity demand and the availability of wind power. Although a wide range of wind power capacity factors is seen for a given demand, the average capacity factor reduces by a third between low and high demand. However, during the highest demand average wind power increases again, due to strengthening easterly winds. The nature of the weather patterns affecting Great Britain are responsible for this relationship. High demand is driven by a range of high pressure weather types, each giving cold conditions, but variable wind power availability. Offshore wind power is sustained at higher levels and offers a more secure supply compared to that onshore. However, during high demand periods in Great Britain neighbouring countries may struggle to provide additional capacity due to concurrent low temperatures and low wind power availability.
The Mediterranean region has been identified as a climate change “hot-spot” due to a projected reduction in precipitation and fresh water availability which has potentially large socio-economic ...impacts. To increase confidence in these projections, it is important to physically understand how this precipitation reduction occurs. This study quantifies the impact on winter Mediterranean precipitation due to changes in extratropical cyclones in 17 CMIP5 climate models. In each model, the extratropical cyclones are objectively tracked and a simple approach is applied to identify the precipitation associated to each cyclone. This allows us to decompose the Mediterranean precipitation reduction into a contribution due to changes in the number of cyclones and a contribution due to changes in the amount of precipitation generated by each cyclone. The results show that the projected Mediterranean precipitation reduction in winter is strongly related to a decrease in the number of Mediterranean cyclones. However, the contribution from changes in the amount of precipitation generated by each cyclone are also locally important: in the East Mediterranean they amplify the precipitation trend due to the reduction in the number of cyclones, while in the North Mediterranean they compensate for it. Some of the processes that determine the opposing cyclone precipitation intensity responses in the North and East Mediterranean regions are investigated by exploring the CMIP5 inter-model spread.
This paper introduces a new approach to quantify the impact of forward propagated demand and weather uncertainty on power system planning and operation models. Recent studies indicate that such ...sampling uncertainty, originating from demand and weather time series inputs, should not be ignored. However, established uncertainty quantification approaches fail in this context due to the data and computing resources required for standard Monte Carlo analysis with disjoint samples. The method introduced here uses an <inline-formula><tex-math notation="LaTeX">m</tex-math></inline-formula> out of <inline-formula><tex-math notation="LaTeX">n</tex-math></inline-formula> bootstrap with shorter time series than the original, enhancing computational efficiency and avoiding the need for any additional data. It both quantifies output uncertainty and determines the sample length required for desired confidence levels. Simulations and validation exercises are performed on two capacity expansion planning models and one unit commitment and economic dispatch model. A diagnostic for the validity of estimated uncertainty bounds is discussed. The models, data and code are made available.
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