Jonathan Aylen

Forecasting the outbreak of moorland wildfires in the English Peak District

Warmer, drier summers brought by climate change increase the potential risk of wildfires on the moorland of the Peak District of northern England. Fires are costly to fight, damage the ecosystem, harm water catchments, cause erosion scars and disrupt transport. Fires release carbon dioxide to the atmosphere. Accurate forecasts of the timing of fires help deployment of fire fighting resources. A probit model is used to assess the chance of fires at different times of the year, days of the week and under various weather conditions. Current and past rainfall damp fire risk. The likelihood of fire increases with maximum temperature. Dry spells or recent fire activity also signal extra fire hazard. Certain days are fire prone due to visitors and some months of the year are more risky reflecting the changing flammability of moorland vegetation. The model back-predicts earlier fires during a hot dry summer. The impact of climate change on fire incidence is not straightforward. Risks may be reduced if wetter winters and earlier onset of spring add to plant moisture content. Yet a warm spring increases biomass and potential fuel load in summer. Climate change may cause the timing of moorland wildfires to shift from a damper and more verdant spring to drought-stressed summer.

Forecasting the behaviour of manufacturing inventory

Forecasting levels of stocks held by manufacturing industry is problematic. Stocks are the most volatile component of GDP. The data itself is subject to chronic revision. Yet, forecasting inventory changes in the supply chain is crucial for firms trying to manage output. The paper reports a successful approach to forecasting UK manufacturing stock behaviour sponsored by a leading European metals manufacturer. The model exploits the seasonality of stock build-ups and run-downs. (Existing econometric approaches rely on seasonally adjusted data.) The forecasting performance of our model is compared to alternative time series approaches. Use of raw, unadjusted data implies markedly different specifications from those in the established literature. In particular, we find no significant evidence of a structural break in UK stockholding behaviour in our sample period and the absence of cointegration between stocks and output suggests the conventional error correction approach is spurious, as well as giving poor forecasts.

Modelling the Great Lakes Freeze: forecasting and seasonality in the market for ferrous scrap

Abstract The paper offers a methodology for modelling seasonality in a volatile commodity market. It gives a practical example of the way seasonal factors can be incorporated into industrial forecasts. Recycled ferrous scrap is a widely traded commodity used in the steel and foundry industries. This paper considers the problems of forecasting scrap prices in the US market. Scrap prices display seasonal behaviour as a result of weather and patterns of industrial production. We consider various ways of modelling this seasonality, use of seasonal vector autoregression, the concept of seasonal integration and the use of dummy variables. A seasonal vector autoregression (VAR) is developed. Here the quarterly series is decomposed into four annual series, one for each quarter. We regress each of these resultant series on its own lags and lags of other series, so developing a periodic autoregressive model. A series of tests enables us to determine the type of seasonality exhibited by the data. The simplest form of seasonal adjustment using seasonal dummy variables turns out to be the best for forecasting US scrap prices. Use of the test procedure suggests that employing seasonal dummies is the correct specification in this case. Inclusion of seasonal effects usually improves the estimation and forecasting performance of time series models. Comparison of a range of alternative forecasting models suggests a periodic autoregression only forecasts satisfactorily in the short run. ARIMA models with seasonal dummies show the best performance. A long lag length is necessary to capture long run cyclical effects.

Wildfire policy and management in England: an evolving response from fire and rescue services, forestry and cross-sector groups

Severe wildfires are an intermittent problem in England. The paper presents the first analysis of wildfire policy, showing its halting evolution over two decades. First efforts to coordinate wildfire management came from local fire operation groups, where stakeholders such as fire services, land owners and amenity groups shared knowledge and equipment to tackle the problem. A variety of structures and informal management solutions emerged in response to local needs. Knowledge of wildfire accumulated within regional and national wildfire forums and academic networks. Only later did the need for central emergency planning and the response to climate change produce a national policy response. Fire statistics have allowed wildfires to be spatially evidenced on a national scale only since 2009. National awareness of wildfire was spurred by the 2011 fire season, and the high-impact Swinley Forest fire, which threatened critical infrastructure and communities within 50 miles of London. Severe wildfire was included in the National Risk Register for the first time in 2013. Cross-sector approaches to wildfire proved difficult as government responsibility is fragmented along the hazard chain. Stakeholders such as the Forestry Commission pioneered good practice in adaptive land management to build fire resilience into UK forests. The grass-roots evolution of participatory solutions has also been a key enabling process. A coordinated policy is now needed to identify best practice and to promote understanding of the role of fire in the ecosystem. This article is part of a themed issue ‘The interaction of fire and mankind’.

Living on a flammable planet: interdisciplinary, cross-scalar and varied cultural lessons, prospects and challenges.

Living with fire is a challenge for human communities because they are influenced by socio-economic, political, ecological and climatic processes at various spatial and temporal scales. Over the course of 2 days, the authors discussed how communities could live with fire challenges at local, national and transnational scales. Exploiting our diverse, international and interdisciplinary expertise, we outline generalizable properties of fire-adaptive communities in varied settings where cultural knowledge of fire is rich and diverse. At the national scale, we discussed policy and management challenges for countries that have diminishing fire knowledge, but for whom global climate change will bring new fire problems. Finally, we assessed major fire challenges that transcend national political boundaries, including the health burden of smoke plumes and the climate consequences of wildfires. It is clear that to best address the broad range of fire problems, a holistic wildfire scholarship must develop common agreement in working terms and build across disciplines. We must also communicate our understanding of fire and its importance to the media, politicians and the general public. This article is part of the themed issue ‘The interaction of fire and mankind’.

Megabytes for metals: development of computer applications in the iron and steel industry

Abstract The steel industry pioneered the use of computers for process control. By the mid 1960s, almost a fifth of the worlds process control computers were installed in the steel industry. The present paper documents the development of direct digital control with emphasis on hot strip mill control, notably the installation at Llanwern using a GE 412 computer. Early applications of computers in areas such as electric arc furnace control and order handling are identified. Archive sources, government documents, interviews, correspondence and technical papers show the leading role of steel in developing online control. Marked differences in adoption rates are identified. Two-thirds of the early steel installations were in the USA. Britain and Italy were also early adopters. Jones & Laughlin and Inland of the USA, the Steel Company of Wales and Italsider were among the leading innovators.

The power of the Durbin Watson test when the errors are PAR(1)

The Durbin Watson, DW, test for first order autocorrelation in regression residuals is among the most widely applied tests in time series analysis and econometrics. A significant test statistic indicates possible mis-specification of the underlying model as well as warning of the invalidity of traditional tests of parameter restrictions. It is important that properties of such a widespread test are well understood by users. We contribute by considering the power of the DW test where the regression errors can be described by a periodic autoregressive process of order 1, PAR(1). Increasingly, the accurate specification of seasonality is used to improve in-sample fit and out of sample forecasting efficiency in time series and econometric models. It is recognised that many seasonal data can be modelled using a periodic specification whereby parameters of the model vary with the season of the year. Seasonality in time series data can be described explicitly in the model, or captured in the error process. A PAR process for the errors is a useful modelling tool and a realistic description of the errors in a seasonal model. Considering the PAR(1) process, we show such errors display both (seasonal) autocorrelation and heteroscedasticity, even if the original data is homoscedastic. However, there is no reason to suppose the implications of PAR(1) errors should be limited to, or indeed similar to, the implications of heteroscedasticity. Thus we derive the power function of the DW test for given regressor data when a periodic process describes the errors. This power function is compared to the power function of the DW test when the errors display no periodicity. Significant differences are found. The DW test is robust if the data set includes seasonal dummy variables. Otherwise the power function is seriously distorted as the error process approaches a random walk.

Bloodhound on my Trail: Building the Ferranti Argus Process Control Computer

Abstract Digital computers for process control were developed at the end of the 1950s. They had different design objectives from computers for scientific or commercial use. The Ferranti Argus was among the first computers worldwide used for direct digital control. The Argus was invented at Ferranti’s Wythenshawe Automation Division, Manchester, by Maurice Gribble. The starting point was a prototype digital computer developed for the Blue Envoy guided missile using low power hearing aid transistors. Announced by Ferranti as the ‘process control transistor computer’ in November 1958, Argus came into civilian and military use in 1962. It was used for process control at a soda ash plant for ICI and as part of a Cold War missile guidance system for the Bloodhound Mark 2 surface-to-air missile deployed by the Royal Air Force. While a small team of engineers within Ferranti used Argus to develop digital techniques for guided missile control, another technically powerful group of civilian users led development of the Argus for direct digital control of an ICI chemical plant at Fleetwood, Lancashire. The paper shows how the computer was invented, how it was developed in military and civilian contexts by small communities of practice and how these groups coalesced, grew and dispersed. As projects shifted towards software development, teams became smaller and women programmers were given considerable responsibility. These events highlight a key transition from analogue to digital control in manufacturing industry and defence during the early 1960s. Use of direct digital control by ICI followed commercial logic. The military were forced to switch to digital computation because technical advances in radar meant analogue calculations would not be accurate enough for Bloodhound Mark 2.

Climate change and the visitor economy in the uplands

This paper presents two case studies on the impact of climate change on upland landscapes in England (footpath erosion in the Lake District National Park, and moorland wildfires in the Peak District National Park) and considers the negative implications for the visitor economy in these areas. Areas of natural beauty such as the examples presented have an important role to play in attracting visitors, and sustaining the visitor economy will therefore depend on maintaining the quality of the environment in the face of both visitor pressure and the impacts of climate change.

First Waltz: Development and Deployment of Blue Danube, Britain’s Post-War Atomic Bomb

Abstract Blue Danube was the first British atom bomb deployed during the Cold War. The article focuses on practical issues of design, production, deployment, maintenance and testing of the weapon during the 1950s. Emphasis on scientific aspects of nuclear weapons means efforts to develop a workable technology have been overlooked. Blue Danube did not follow the usual pattern of technical development: it was deployed first and tested later. The first weapons were hand-crafted prototypes delivered to the RAF for familiarization and active service, rather than a durable and reliable deterrent. As service life progressed, components were tested and the technology developed in terms of safety, fuzing and arming. Electronic circuits were modified to improve reliability within the same overall casing. So, Blue Danube is not one weapon — more a sequence of modifications in response to a succession of problems. Development of the weapon required innovations in electronics, explosives and logistics. Conventional high explosive components were as much a constraint on deployment and serviceability as the novel radioactive parts. Learning how to manufacture, use, maintain and upgrade the weapon proved as important as building the device in the first place. The bomb was at the frontiers of practical application in electronic circuitry. Protecting electronic components by potting remained an uncertain art. Like many technologies, Blue Danube was a combination of the familiar and the advanced.