Hazel Thornton

The climatological relationships between wind and solar energy supply in Britain

We use reanalysis data to investigate the daily co-variability of wind and solar irradiance in Britain, and its implications for renewable energy supply balancing. The joint distribution of daily-mean wind speeds and irradiances shows that irradiance has a much stronger seasonal cycle than wind, due to the rotational tilt of the Earth. Irradiance is weakly anticorrelated with wind speed throughout the year (−0.4≲ρ≲−0.2): there is a weak tendency for windy days to be cloudier. This is particularly true in Atlantic-facing regions (western Scotland, south-west England). The east coast of Britain has the weakest anticorrelation, particularly in winter, primarily associated with a relative increase in the frequency of clear-but-windy days. We also consider the variability in total power output from onshore wind turbines and solar photovoltaic panels. In all months, daily variability in total power is always reduced by incorporating solar capacity. The scenario with the least seasonal variability is approximately 70%-solar to 30%-wind. This work emphasises the importance of considering the full distribution of daily behaviour rather than relying on long-term average relationships or correlations. In particular, the anticorrelation between wind and solar power in Britain cannot solely be relied upon to produce a well-balanced energy supply.

Stratospheric Vacillations and the Major Warming over Antarctica in 2002

The conditions that lead to the major warming over Antarctica in late September 2002 are examined. In many respects, the warming resembled wave-2 warmings seen in the Northern Hemisphere; the winter cyclonic circulation was split into two smaller cyclones by a large amplitude planetary wave disturbance that appeared to propagate upward from the troposphere. However, in addition to this classic warming mechanism, distinctive stratospheric vacillations occurred throughout the preceding winter months. These vacillations in wave amplitude, Eliassen–Palm fluxes, and zonal-mean zonal winds are examined. By comparison with a numerical model experiment, it is shown that the vacillation is accompanied by a systematic weakening of the westerly winds over the season. This preconditions the Antarctic circulation, and it is argued that it allows anomalously strong vertical propagation of planetary waves from the troposphere into the stratosphere. By contrast, a survey of previous winters shows that stratospheric westerlies usually vary much more gradually, with vacillations only occurring for short periods of time, if at all, in a given winter. Similar vacillations in a numerical model of the stratosphere only occur if the forcing amplitude is above a certain value. However, the level of winter-mean wave activity entering the stratosphere during 2002 is not unprecedented, and there is still some uncertainty over the cause of the onset and persistence of the vacillation and, ultimately, the major warming.

Assessing the potential impact of climate change on the UK’s electricity network

We investigate how weather affects the UK’s electricity network, by examining past data of weather-related faults on the transmission and distribution networks. By formalising the current relationship between weather-related faults and weather, we use climate projections from a regional climate model (RCM) to quantitatively assess how the frequency of these faults may change in the future. This study found that the incidences of both lightning and solar heat faults are projected to increase in the future. There is evidence that the conditions that cause flooding faults may increase in the future, but a reduction cannot be ruled out. Due to the uncertainty associated with future wind projections, there is no clear signal associated with the future frequency of wind and gale faults, however snow, sleet and blizzard faults are projected to decrease due to a reduction in the number of snow days.

European wind variability over 140 yr

Abstract. We present initial results of a study on the variability of wind speeds across Europe over the past 140 yr, making use of the recent Twentieth Century Reanalysis data set, which includes uncertainty estimates from an ensemble method of reanalysis. Maps of the means and standard deviations of daily wind speeds, and the Weibull-distribution parameters, show the expected features, such as the strong, highly-variable wind in the north-east Atlantic. We do not find any clear, strong long-term trends in wind speeds across Europe, and the variability between decades is large. We examine how different years and decades are related in the long-term context, by looking at the ranking of annual mean wind speeds. Picking a region covering eastern England as an example, our analyses show that the wind speeds there over the past ~ 20 yr are within the range expected from natural variability, but do not span the full range of variability of the 140-yr data set. The calendar-year 2010 is however found to have the lowest mean wind speed on record for this region.

The role of temperature in the variability and extremes of electricity and gas demand in Great Britain

The daily relationship of electricity and gas demand with temperature in Great Britain is analysed from 1975 to 2013 and 1996 to 2013 respectively. The annual mean and annual cycle amplitude of electricity demand exhibit low frequency variability. This low frequency variability is thought to be predominantly driven by socio-economic changes rather than temperature variation. Once this variability is removed, both daily electricity and gas demand have a strong anti-correlation with temperature (r elec = −0.90 , r gas = −0.94). However these correlations are inflated by the changing demand–temperature relationship during spring and autumn. Once the annual cycles of temperature and demand are removed, the correlations are and . Winter then has the strongest demand–temperature relationship, during which a 1 °C reduction in daily temperature typically gives a ~1% increase in daily electricity demand and a 3%–4% increase in gas demand. Extreme demand periods are assessed using detrended daily temperature observations from 1772. The 1 in 20 year peak day electricity and gas demand estimates are, respectively, 15% (range 14%–16%) and 46% (range 44%–49%) above their average winter day demand during the last decade. The risk of demand exceeding recent extreme events, such as during the winter of 2009/2010, is also quantified.

Using the Twentieth Century Reanalysis to assess climate variability for the European wind industry

We characterise the long-term variability of European near-surface wind speeds using 142 years of data from the Twentieth Century Reanalysis (20CR), and consider the potential of such long-baseline climate data sets for wind energy applications. The low resolution of the 20CR would severely restrict its use on its own for wind farm site-screening. We therefore perform a simple statistical calibration to link it to the higher-resolution ERA-Interim data set (ERAI), such that the adjusted 20CR data has the same wind speed distribution at each location as ERAI during their common period. Using this corrected 20CR data set, wind speeds and variability are characterised in terms of the long-term mean, standard deviation and corresponding trends. Many regions of interest show extremely weak trends on century timescales, but contain large multidecadal variability. Since reanalyses such as ERAI are often used to provide the background climatology for wind farm site assessments, but contain only a few decades of data, our results can be used as a way of incorporating decadal-scale wind climate variability into such studies, allowing investment risks for wind farms to be reduced.

Quantifying the increasing sensitivity of power systems to climate variability

Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-ofthe-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insuffcient for providing robust power system planning guidance. This suggests renewable integration studies - widely used in policy, investment and system design - should adopt a more robust approach to climate characterisation.

Future projections of temperature-related climate change impacts on the railway network of Great Britain

Great Britain’s main line railway network is known to experience various temperature-related impacts, e.g. track buckling and overhead power line sag at high ambient temperatures. Climate change could alter the frequency of occurrence of these impacts. We have therefore investigated the climate change impact on various temperature-related issues, identified during workshops with rail industry specialists, using a perturbed physics ensemble (PPE) of the Met Office’s regional climate model (RCM), HadRM3. We have developed novel approaches to combine RCM data with railway industry knowledge, typically by identifying key meteorological thresholds of interest and analysing exceedance of these out to the 2040s. We performed a statistical analysis of the projected changes for each issue, via bootstrapping of the unperturbed PPE member. Although neither the PPE nor the bootstrapping analysis samples the full range of uncertainty in the projections, they nonetheless provide complementary perspectives on the suitability of the projections for use in decision-making. Our main findings include projected increases in the summertime occurrence of temperature conditions associated with (i) track buckling, (ii) overhead power line sag, (iii) exposure of outdoor workers to heat stress, and (iv) heat-related delays to track maintenance; and (v) projected decreases in the wintertime occurrence of temperatures conditions associated with freight train failure owing to brake problems. For (i), the statistical significance varied with track condition and location; for (ii) and (iii), with location; and for (iv) and (v), projected changes were significant across Great Britain. As well as assessing the changes in climate-related hazard, information about the vulnerability of the network to past temperature-related incidents has been summarised. Combining the hazard and vulnerability elements will eventually support a climate risk assessment for the industry.

Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall

The Yangtze River has been subject to heavy flooding throughout history, and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods. Dams along the river help to manage flood waters, and are important sources of electricity for the region. Being able to forecast high-impact events at long lead times therefore has enormous potential benefit. Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services. The teleconnection from El Niño to Yangtze River basin rainfall meant that the strong El Niño in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system. This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin, building on previous work demonstrating the retrospective skill of such a forecast. A simple forecasting methodology is presented, in which the forecast probabilities are derived from the historical relationship between hindcast and observations. Its performance for 2016 is discussed. The heavy rainfall in the May–June–July period was correctly forecast well in advance. August saw anomalously low rainfall, and the forecasts for the June–July–August period correctly showed closer to average levels. The forecasts contributed to the confidence of decision-makers across the Yangtze River basin. Trials of climate services such as this help to promote appropriate use of seasonal forecasts, and highlight areas for future improvements.摘要长江历史上一直遭受着洪涝灾害的影响. 近年来的严重灾害, 如1998年的大洪水, 造成了重大的人民生命财产损失. 洪水带来的径流在沿江的大坝的控制下, 同时是该地区重要的电力来源. 因此, 能够提前对这种灾害性事件进行有效预测, 有巨大的潜在价值. 最近季节预测能力的提高表明动力气候模式可以直接进行业务化的气候服务. 长江流域降水与厄尔尼诺联系密切, 因而2015/16年冬季强厄尔尼诺事件的发生为我们提供了一个检验动力预测系统应用到长江流域夏季降水预测的宝贵机会. 因此, 在前期回报工作呈现出一定预测技巧基础上, 本文对长江流域的实时季节预测进行了实例研究. 本文使用了一种简单的预测方法, 根据历史回报和观测的关系推算出预测事件发生的概率, 进而讨论了2016的预测结果. 结果表明, 2016年5月至7月的强降水预测准确. 8月份降水异常偏低, 而模式预测的6月至8月降水准确接近气候平均的结果. 这些成功的预测结果为长江流域防洪减灾并进行决策提供了信心. 此类气候服务的展开可以促进季节预测结果的应用推广, 并有助于未来气候预测服务领域的提升.

Skill and Reliability of Seasonal Forecasts for the Chinese Energy Sector

AbstractThe skill and reliability of forecasts of winter and summer temperature, wind speed, and irradiance over China are assessed using the Met Office Global Seasonal Forecast System, version 5 (GloSea5). Skill in such forecasts is important for the future development of seasonal climate services for the energy sector, allowing better estimates of forthcoming demand and renewable electricity supply. It was found that, although overall the skill from the direct model output is patchy, some high-skill regions of interest to the energy sector can be identified. In particular, winter mean wind speed is skillfully forecast around the coast of the South China Sea, related to skillful forecasts of the El Nino–Southern Oscillation. Such information could improve seasonal estimates of offshore wind-power generation. In a similar way, forecasts of winter irradiance have good skill in eastern central China, with possible use for solar-power estimation. Skill in predicting summer temperatures, which derives from an...