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Data assimilation is playing an ever increasing role in weather forecasting. Implementing four- dimensional variational data assimilation (4DVAR) is part of the long term strategy of the UK Met Office.
In this case study, an idealised 4DVAR scheme, developed by a team from the Universities of Surrey and Reading working with the UK Met Office, based on the integration of Hamiltonian dynamics and nonlinearity into data assimilation, has now been taken up by the Met Office. It is being used to evaluate options for improving operational 4DVAR. The simplicity of the scheme developed by this team has facilitated careful analyses of some generic problems with the operational model. The outcome includes direct impact on the environment and indirect impact on the economy, both through improvements in weather forecasting.
Garratt's research on methods for quantifying the uncertainty surrounding macroeconomic forecasts, uncertainty which arises from not knowing the true model of the economy and from having to use inaccurate data, has been applied by Central Banks and national statistical agencies in their forecasting exercises and their analysis of policy interventions. Notably, Norges Bank (the central bank of Norway) has developed a system called the System for Averaging Models, which they use when they make macroeconomic forecasts and when they predict the effects of possible monetary policy actions, which incorporates Garratt's results.
Garratt's research provides new methods to allow for uncertainty about the 'true' model by using combinations of different possible models, when making forecasts. His research provides new procedures to take `data uncertainty' into account, when forecasts have to be based on real-time data (that is, inaccurate data which is available to the policymaker when a forecast is produced but which is revised later on). Garratt's research quantifies the effect of this uncertainty on forecasts by constructing probability density functions. Central banks and statistical agencies have applied his findings when making forecasts and undertaking policy analysis. Garratt's research has been disseminated through refereed journal articles, conference presentations, consultancy work with policy makers, and presentations to policy makers, including an invited presentation to HM Treasury.
As the realities of climate change have become more widely accepted over the last decade, decision makers have requested projections of future changes and impacts. Founded in 2002, the Centre for Analysis of Time Series (CATS) has conducted research revealing how the limited fidelity of climate models reduces the relevance of cost-benefit style management in this context: actions based on ill-founded projections (including probabilistic projections) can lead to maladaptation and poor policy choice. CATS' conclusions were noted in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) report and led in turn to the toning down of the UK Climate Projections 2009 and the 2012 UK Climate Change Risk Assessment. Members of the insurance sector, energy sector, national security agencies, scientific bodies and governments have modified their approaches to climate risk management as a direct result of understanding CATS' research. Attempts to reinterpret climate model output and design computer experiments for more effective decision support have also resulted.
Ocean circulation accounts for much of the energy that drives weather and climate systems; errors in the representation of the ocean circulation in computational models affect the validity of forecasts of the dynamics of the ocean and atmosphere on daily, seasonal and decadal time scales. Research undertaken by the University of Reading investigated systematic model errors that resulted from data assimilation schemes embedded in the key processes used to predict ocean circulation. The researchers developed a new bias correction technique for use in ocean data assimilation that alleviates these errors. This has led to significant improvements in the accuracy of the forecasts of ocean dynamics. The technique has been implemented by the Met Office and by the European Centre for Medium Range Weather Forecasting (ECMWF) in their forecasting systems, resulting in major improvements to the prediction of the weather and climate from oceanic and atmospheric models. The assimilation technique is also leading to better use of expensively acquired satellite and in-situ data and improving ocean and atmosphere forecasts used by shipping and civil aviation, energy providers, insurance companies, the agriculture and fishing communities, food suppliers and the general public. The impact of the correction procedure is also important for anticipating and mitigating hazardous weather conditions and the effects of long-term climate change.
Researchers in the Global Environmental Modelling and Earth Observation (GEMEO) group at Swansea University have used satellite data to improve weather forecasts and climate predictions. Using observations of the Earth's land surface from NASA's orbiting Moderate Resolution Imaging Spectrometer (MODIS) flying on board the Terra and Aqua satellites, Swansea University has worked directly with two leading meteorological agencies — the UK Met Office and the European Centre for Medium-Range Weather Forecasts (ECMWF) — to refine the way in which land is represented in their numerical weather prediction models. Improved weather forecasting is of clear benefit to society, facilitating day-to-day planning by the public, agriculture, commerce, utility suppliers and transport sectors, as well as preparation for extreme weather events such as floods, heat waves and droughts. The Met Office provides daily weather forecasts for the UK, while the ECMWF model is routinely used by over 30 countries for weather, aviation planning and extreme event warning. The Met Office states that the research presented here has resulted in significantly improved weather forecasts, in particular of rainfall and temperature, and more realistic climate simulations to inform the Intergovernmental Panel on Climate Change (IPCC). The ECMWF reports improvement of precipitation forecast, increasing predicted summer rainfall by 7%, and its variability, which is relevant to flood and drought forecast, increased by 30%.
A series of econometric methods and software, designed by a team of econometricians at Oxford, have been adopted as standard by a large range of governmental bodies, international agencies and businesses. The econometric methods are designed to model and forecast high-dimensional, evolving economic processes facing multiple structural shifts, while the econometric software (PcGive) implements the resulting best-practice procedures. The application of these methods have resulted in more appropriate empirical models, improved robust forecasts, and, consequently, better decision making by these bodies.
Research at Newcastle University into stochastic rainfall models and their application has transformed the practice of impact assessment of climate change and risk assessment of environmental hazards across multiple sectors. The Newcastle methods underpin the "Weather Generator", a web-based tool which has been made available since 2009 by DEFRA as part of their official UK Climate Projections (UKCP09). The tool's incorporation into this official data source means that the models generated underpin multi-sectoral risk assessment throughout the UK and subsequently have led to the adoption of stochastic methods in general, particularly in the water and insurance industries to produce more robust risk assessments.
In response to the deficiencies in bank risk management revealed following the 2008 financial crisis, one of the mandated requirements under the Basel III regulatory framework is for banks to backtest the internal models they use to price their assets and to calculate how much capital they require should a counterparty default. Qiwei Yao worked with the Quantitative Analyst — Exposure team at Barclays Bank, which is responsible for constructing the Barclays Counterpart Credit Risk (CCR) backtesting methodology. They made use of several statistical methods from Yao's research to construct the newly developed backtesting methodology which is now in operation at Barclays Bank. This puts the CCR assessment and management at Barclays in line with the Basel III regulatory capital framework.
Research conducted within the Aon Benfield UCL Hazard Centre has underpinned the development of innovative extreme weather services for the real-time monitoring of global tropical storms and European extreme weather. These services have achieved significant commercial and humanitarian impacts worldwide. Within the REF impact period these impacts included £1.319 million of income generated by sales of commercial products; 24,000 subscribers receiving free storm alerts and/or seasonal forecasts; seasonal forecasts distributed to reinsurance companies worldwide; and a contribution to lives saved in Bangladesh from tropical storm Mahasen (2013). Twenty-two international organisations have also benefited from the commercial extreme weather services; for example, they support the claims division at RSA in assessing risk, allocating resources and detecting fraudulent weather claims; and they enable the Norwegian Hull Club to alert its portfolio of over 9,200 vessels worldwide to steer clear of approaching dangerous storms.
Impact: Multi-national developments in public policy and service provision related to earthquake risk reduction, derived from the work of the International Commission on Earthquake Forecasting for Civil Protection (ICEF), established following the 2009 L'Aquila earthquake.
Significance and reach: In 2012 the Italian Department of Civil Protection allocated €1billion for seismic protection, including a multi-year programme on operational earthquake forecasting. New programmes/policies have been enacted by government bodies in the USA (2012), Russia (2012) and Japan (May 2013).
Underpinned by: Research into earthquake dynamics and predictability, undertaken at the University of Edinburgh (1996 onwards), which led to the appointment of the sole UK representative to the ICEF.