Philip E. Bett

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.

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.

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.

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...

Skillful Seasonal Forecasts of Summer Surface Air Temperature in Western China by Global Seasonal Forecast System Version 5

Variations of surface air temperature (SAT) are key in affecting the hydrological cycle, ecosystems and agriculture in western China in summer. This study assesses the seasonal forecast skill and reliability of SAT in western China, using the GloSea5 operational forecast system from the UK Met Office. Useful predictions are demonstrated, with considerable skill over most regions of western China. The temporal correlation coefficients of SAT between model predictions and observations are larger than 0.6, in both northwestern China and the Tibetan Plateau. There are two important sources of skill for these predictions in western China: interannual variation of SST in the western Pacific and the SST trend in the tropical Pacific. The tropical SST change in the recent two decades, with a warming in the western Pacific and cooling in the eastern Pacific, which is reproduced well by the forecast system, provides a large contribution to the skill of SAT in northwestern China. Additionally, the interannual variation of SST in the western Pacific gives rise to the reliable prediction of SAT around the Tibetan Plateau. It modulates convection around the Maritime Continent and further modulates the variation of SAT on the Tibetan Plateau via the surrounding circulation. This process is evident irrespective of detrending both in observations and the model predictions, and acts as a source of skill in predictions for the Tibetan Plateau. The predictability and reliability demonstrated in this study is potentially useful for climate services providing early warning of extreme climate events and could imply useful economic benefits.摘要我国西部地区夏季气温的变化对水循环, 生态系统和农作物产量都有着重要影响. 本文利用英国气象局的GloSea5预测系统, 评估了我国西部气温的季节预测技巧和可靠性. 研究发现, 模式对我国西部地区近地面气温的预测技巧较高. 对应气候模式的预测结果与观测的时间相关系数在西部大部分地区超过了0.6, 包括西北和青藏高原地区. 这些高预测技巧有两个重要的物理来源:西太平洋地区海温的年际变化和热带太平地区海温的趋势变化. 其中, 近二十年来热带太平洋的海温趋势, 包括热带西太的增暖和东太的偏冷, 对我国西北地区气温的预测技巧贡献显著. 而青藏高原地区气温的高预测技巧主要受到西太平洋海温年际变化的影响. 西太平洋海温可以影响海洋性大陆地区的对流, 调制青藏高原地区环流年际变化, 进而对地表气温产生重要影响. 这个调制过程在观测和模式中都得到了很好的表现, 为青藏高原气温预测提供了重要的技巧来源. 本研究所展示的可预测性和可靠性度有助于我国气候服务业务的开展, 可以为极端气候事件提供有效的前期预警, 并进一步保护人民的生命和经济财产损失.