Coping strategies against extreme weather events:a survey of SMEs in the UK

Small and Medium-scale Enterprises (SMEs); which generate more than one half of the employment and turnover, form an important sector of the UK economy. In fact, SMEs are considered as the backbone of the UK economy due to their significant economic and societal importance. Despite SMEs being the main drivers of the UK economy, they are also said to be the most vulnerable to the impacts from various disruptions such as Extreme Weather Events (EWEs). Consequently, increased intensity and frequency of weather extremes in the UK during the recent past has created a significant impact on the SME community. As the threat of EWEs is expected to further increase in future, the need for SMEs to implement effective coping mechanisms to manage the effects of EWEs is also increasing. This paper aims to identify and evaluate the current coping mechanisms implemented by SMEs to ensure their business continuity in the event of a weather extreme. The paper presents the findings of a questionnaire survey, conducted as part of "Community Resilience to Extreme Weather - CREW" research project, addressing this issue. It is identified that SMEs mostly rely on generic business continuity strategies as opposed to property level protection measures. The paper highlights the importance of raising the uptake of coping strategies by SMEs, as many were found without adequate coping strategies to deal with the risk of EWEs.

Utilising Intranet technologies in construction sector SMEs:building up knowledge bases for extreme weather event risk management

Intranet technologies accessible through a web based platform are used to share and build knowledge bases in many industries. Previous research suggests that intranets are capable of providing a useful means to share, collaborate and transact information within an organization. To compete and survive successfully, business organisations are required to effectively manage various risks affecting their businesses. In the construction industry too this is increasingly becoming an important element in business planning. The ability of businesses, especially of SMEs which represent a significant portion in most economies, to manage various risks is often hindered by fragmented knowledge across a large number of businesses. As a solution, this paper argues that Intranet technologies can be used as an effective means of building and sharing knowledge and building up effective knowledge bases for risk management in SMEs, by specifically considering the risks of extreme weather events. The paper discusses and evaluates relevant literature in this regard and identifies the potential for further research to explore this concept.

Effects of extreme weather events on SMEs:a literature review and synthesis

Small and Medium-scale Enterprises (SMEs), which generate more than one half of the employment (58.9%) and turnover (51.9%), form an important sector of the UK economy. Although they are the main drivers of the UK economy, they are also said to be the most vulnerable to the impacts of Extreme Weather Events (EWEs). The world in recent years has experienced a significant number of EWEs, and SMEs have suffered significant economic losses as a result. The now apparent climate change, which is mostly attributed to human interference with the environment over the past few decades, is believed to have a strong link with the increase of EWEs in the recent past. Threats of EWEs are expected to further increase due to their increased frequency and magnitude and increased vulnerability to their effects. Interestingly, EWEs seem to present businesses with various business opportunities and positive consequences as well, besides the much feared and overwhelming threats and negative consequences they present. Understanding such impacts has become a necessity to improve the resilience of SMEs so that they will be better prepared to minimise the negative consequences and maximise the positive consequences posed by EWEs. This paper attempts to bring together and evaluate the current knowledge with regard to the effects of EWEs on SMEs. The paper establishes the case for more in-depth study with this regard and concludes by stressing the need for improving the resilience of SMEs to EWEs.

Case study as a research strategy:investigating extreme weather resilience of construction SMEs in the UK

Determining an appropriate research methodology is considered as an important element in a research study; especially in a doctoral research study. It involves approach to the entire process of a research study, starting from theoretical underpinnings and spanning to data collection and analysis, and extending to developing the solutions for the problems investigated. Research methodology in essence is focused around the problems to be investigated in a research study and therefore varies according to the problems investigated. Thus, identifying the research methodology that best suits a research in hand is important, not only as it will benefit achieving the set objectives of a research, but also as it will serve establishing the credibility of the work. Research philosophy, approach, strategy, choice, and techniques are inherent components of the methodology. Research strategy provides the overall direction of the research including the process by which the research is conducted. Case study, experiment, survey, action research, grounded theory and ethnography are examples for such research strategies. Case study is documented as an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident. Case study was adopted as the overarching research strategy, in a doctoral study developed to investigate the resilience of construction Small and Medium-sized Enterprises (SMEs) in the UK to extreme weather events. The research sought to investigate how construction SMEs are affected by EWEs, respond to the risk of EWEs, and means of enhancing their resilience to future EWEs. It is argued that utilising case study strategy will benefit the research study, in achieving the set objectives of the research and answering the research questions raised, by comparing and contrasting with the alternative strategies available. It is also claimed that the selected strategy will contribute towards addressing the call for improved methodological pluralism in construction management research, enhancing the understanding of complex network of relationships pertinent to the industry and the phenomenon being studied.

SME resilience to extreme weather events:important initiatives for informing policy making in the area

Enhancing the resilience of local communities to weather extremes has gained significant interest over the years, amidst the increased intensity and frequency of such events. The fact that such weather extremes are forecast to further increase in number and severity in future has added extra weight to the importance of the issue. As a local community consists of a number of community groups such as households, businesses and policy makers, the actions of different community groups in combination will determine the resilience of the community as a whole. An important role has to be played by Small and Medium-sized Enterprises (SMEs); which is an integral segment of a local community in the UK, in this regard. While it is recognised that they are vital to the economy of a country and determines the prosperity of communities, they are increasingly vulnerable to effects of extreme weather. This paper discusses some of the exploratory studies conducted in the UK on SMEs and their ability to cope with extreme weather events, specifically flooding. Although a reasonable level of awareness of the risk was observed among the SMEs, this has not always resulted in increased preparedness even if they are located in areas at risk of flooding. The attitude and the motivation to change differed widely between SMEs. The paper presents schemas by which the SMEs can identify their vulnerability better so that they can be populated among a community of SMEs, which can be taken forward to inform policy making in this area. Therefore the main contribution the paper makes to the body of knowledge in the area is a novel way to communicate to SMEs on improving resilience against extreme weather, which will inform some of the policy making initiatives in the UK.

Coping with extreme weather:strategies of construction SMEs

Weather extremes have created a considerable impact on Small and Medium-sized Enterprises (SMEs) in the UK during the recent years, especially on SMEs in the construction sector. Evidence in relation to the recent weather extremes have demonstrated that SMEs are some of the worst impacted by the Extreme Weather Events (EWEs) and have confirmed them as a highly vulnerable section of the UK economy to the impact of extreme weather. This is of particular importance to the construction industry, as an overarching majority of construction companies are SMEs who account for the majority of employment and income generation within the industry. Whilst construction has been perceived as a sector significantly vulnerable to the impacts of EWEs, there is scant evidence of how construction SMEs respond to such events and cope with their impact. Based on the evidence emerged from case studies of construction SMEs, current coping strategies of construction SMEs were identified. Some of the strategies identified were focused at organisational level whereas others were focused at project level. Further, some of the strategies were general risk management / business continuity strategies whereas others have been specifically developed to address the risk of EWEs. Accordingly, coping strategies can be broadly categorised based on their focus; i.e. those focused at project or organisational level, and based on the risks that they seek to address; i.e. business / continuity risks in general or EWE risk specifically. By overlapping these two aspects; their focus and risks that they seek to address, four categories of coping strategies can be devised. There are; general risk management strategies focused at business level, general risk management strategies focused at project level, EWE specific strategies focused at business level, and EWE specific strategies focused at project level. It is proposed that for a construction SME to effectively cope with the impact of EWEs and develop their resilience against EWEs a rich mix of these coping strategies are required to suite the particular requirements of the business.

Making the construction industry resilient to extreme weather:lessons from construction in hot weather conditions

The construction industry is susceptible to extreme weather events (EWEs) due to most of its activities being conducted by manual workers outdoors. Although research has been conducted on the effects of EWEs, such as flooding and snowfall, limited research has been conducted on the effects of heatwaves and hot weather conditions. Heatwaves present a somewhat different risk profile to construction, unlike EWEs such as flooding and heavy snowfall that present physical obstacles to work onsite. However, heatwaves have affected the construction industry in the UK, and construction claims have been made due to adverse weather conditions. With heatwaves being expected to occur more frequently in the coming years, the construction industry may suffer unlike any other industry during the summer months. This creates the need to investigate methods that would allow construction activities to progress during hot summer months with minimal effect on construction projects. Hence, the purpose of this paper. Regions such as the Middle East and the UAE in particular flourish with mega projects, although temperatures soar to above 40̊C in the summer months. Lessons could be learnt from such countries and adapted in the UK. Interviews have been conducted with a lead representative of a client, a consultant and a contractor, all of which currently operate on UAE projects. The key findings include one of the preliminary steps taken by international construction companies operating in the UAE. This involves restructuring their entire regional team by employing management staff from countries such as Lebanon, Palestine, Iraq, and their labour force from the sub-continent such as India and Pakistan. This is not only due to the cheap wage rate but also to the ability to cope and work in such extreme hot weather conditions. The experience of individuals working in the region allows for future planning, where the difference in labour productivity during the extreme hot weather conditions is known, allowing precautionary measures to be put in place.

How good are citizen weather stations? Addressing a biased opinion

The UK is home to a dense network of Citizen Weather Stations (CWS) primarily set up by members of the public. The majority of these stations record air temperature, relative humidity and precipitation, amongst other variables, at sub-hourly intervals. This high resolution network could have benefits in many applications, but only if the data quality is well characterised. Here we present results from an intercomparison field study, in which popular CWS models were tested against Met Office standard equipment. The study identifies some common instrumental biases and their dependencies, which will help us to quantify and correct such biases from the CWS network.

Wind power forecasts using Gaussian processes and numerical weather prediction

Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use of wind energy. In this paper, we investigated a combination of numeric and probabilistic models: a Gaussian process (GP) combined with a numerical weather prediction (NWP) model was applied to wind-power forecasting up to one day ahead. First, the wind-speed data from NWP was corrected by a GP, then, as there is always a defined limit on power generated in a wind turbine due to the turbine controlling strategy, wind power forecasts were realized by modeling the relationship between the corrected wind speed and power output using a censored GP. To validate the proposed approach, three real-world datasets were used for model training and testing. The empirical results were compared with several classical wind forecast models, and based on the mean absolute error (MAE), the proposed model provides around 9% to 14% improvement in forecasting accuracy compared to an artificial neural network (ANN) model, and nearly 17% improvement on a third dataset which is from a newly-built wind farm for which there is a limited amount of training data. © 2013 IEEE.

Quantifying uncertainty in citizen weather data

The sheer volume of citizen weather data collected and uploaded to online data hubs is immense. However as with any citizen data it is difficult to assess the accuracy of the measurements. Within this project we quantify just how much data is available, where it comes from, the frequency at which it is collected, and the types of automatic weather stations being used. We also list the numerous possible sources of error and uncertainty within citizen weather observations before showing evidence of such effects in real data. A thorough intercomparison field study was conducted, testing popular models of citizen weather stations. From this study we were able to parameterise key sources of bias. Most significantly the project develops a complete quality control system through which citizen air temperature observations can be passed. The structure of this system was heavily informed by the results of the field study. Using a Bayesian framework the system learns and updates its estimates of the calibration and radiation-induced biases inherent to each station. We then show the benefit of correcting for these learnt biases over using the original uncorrected data. The system also attaches an uncertainty estimate to each observation, which would provide real world applications that choose to incorporate such observations with a measure on which they may base their confidence in the data. The system relies on interpolated temperature and radiation observations from neighbouring professional weather stations for which a Bayesian regression model is used. We recognise some of the assumptions and flaws of the developed system and suggest further work that needs to be done to bring it to an operational setting. Such a system will hopefully allow applications to leverage the additional value citizen weather data brings to longstanding professional observing networks.

A conceptual framework for understanding resilience of construction SMEs to extreme weather events

Purpose Small and Medium-sized Enterprises (SMEs), which form a significant portion in many economies, are some of the most vulnerable to the impact of Extreme Weather Events (EWEs). This is of particular importance to the construction industry, as an overarching majority of construction companies are SMEs who account for the majority of employment and income generation within the industry. In the UK, previous research has identified construction SMEs as some of the worst affected by EWEs. Design/methodology/approach Given the recent occurrences of EWEs and predictions suggesting increases in both the intensity and frequency of EWEs in the future, improving the resilience of construction SMEs is vital for achieving a resilient construction industry. A conceptual framework is first developed which is then populated and expanded based on empirical evidence. Positioned within a pragmatic research philosophy, case study research strategy was adopted as the overall research strategy in undertaking this investigation. Findings Based on the findings of two in-depth case studies of construction SMEs, a framework was developed to represent EWE resilience of construction SMEs, where resilience was seen as a collective effect of vulnerability, coping strategies and coping capacities of SMEs, characteristics of the EWE and the wider economic climate. Originality/value The paper provides an original contribution towards the overarching agenda of the resilience of SMEs, and policy making in the area of EWE risk management by presenting a novel conceptual framework depicting the resilience of medium-sized construction companies.

Weather forecasting to predict practical dynamic asset rating of overhead lines

This paper describes the potential of pre-setting 11kV overhead line ratings over a time period of sufficient length to be useful to the real-time management of overhead lines. This forecast is based on short and long term freely available weather forecasts and is used to help investigate the potential for realising dynamic rating benefits on the electricity network. A comparison between the realisable benefits in ratings using this forecast data, over the period of a year has been undertaken.

Hourly values of X, Y and Z geomagnetic components recorded at Coimbra Station (IAGA code: COI) and local geomagnetic K indices for 2007 to 2014

This study examines the performance of series of two geomagnetic indices and series synthesized from a semi-empirical model of magnetospheric currents, in explaining the geomagnetic activity observed at Northern Hemipshere's mid-latitude ground-based stations. We analyse data, for the 2007 to 2014 period, from four magnetic observatories (Coimbra, Portugal; Panagyurishte, Bulgary; Novosibirsk, Russia and Boulder, USA), at geomagnetic latitudes between 40° and 50° N. The quiet daily (QD) variation is firstly removed from the time series of the geomagnetic horizontal component (H) using natural orthogonal components (NOC) tools. We compare the resulting series with series of storm-time disturbance (Dst) and ring current (RC) indices and with H series synthesized from the Tsyganenko and Sitnov (2005, doi:10.1029/2004JA010798) (TS05) semi-empirical model of storm-time geomagnetic field. In the analysis, we separate days with low and high local K-index values. Our results show that NOC models are as efficient as standard models of QD variation in preparing raw data to be compared with proxies, but with much less complexity. For the two stations in Europe, we obtain indication that NOC models could be able to separate ionospheric and magnetospheric contributions. Dst and RC series explain the four observatory H-series successfully, with values for the mean of significant correlation coefficients, from 0.5 to 0.6 during low geomagnetic activity (K less than 4) and from 0.6 to 0.7 for geomagnetic active days (K greater than or equal to 4). With regard to the performance of TS05, our results show that the four observatories separate into two groups: Coimbra and Panagyurishte, in one group, for which the magnetospheric/ionospheric ratio in QD variation is smaller, a dominantly QD ionospheric contribution can be removed and TS05 simulations are the best proxy; Boulder and Novosibirsk,in the other group, for which the ionospheric and magnetospheric contributions in QD variation can not be differentiated and correlations with TS05 series can not be made to improve. The main contributor to magnetospheric QD signal are Birkeland currents. The relatively good success of TS05 model in explaining ground-based irregular geomagnetic activity at mid-latitudes makes it an effective tool to classify storms according to their main sources. For Coimbra and Panagyurishte in particular, where ionospheric and magnetospheric daily contributions seem easier to separate, we can aspire to use the TS05 model for ensemble generation in space weather (SW) forecasting and interpretation of past SW events.

Multi-year weather data in the remote semi-arid to arid mountain region of the Saharan flank of the Atlas Mountains

In 2001, a weather and climate monitoring network was established along the temperature and aridity gradient between the sub-humid Moroccan High Atlas Mountains and the former end lake of the Middle Drâa in a pre-Saharan environment. The highest Automated Weather Stations (AWS) was installed just below the M'Goun summit at 3850 m, the lowest station Lac Iriki was at 450 m. This network of 13 AWS stations was funded and maintained by the German IMPETUS (BMBF Grant 01LW06001A, North Rhine-Westphalia Grant 313-21200200) project and since 2011 five stations were further maintained by the GERMAN DFG Fennec project (FI 786/3-1), this way some stations of the AWS network provided data for almost 12 years from 2001-2012. Standard meteorological variables such as temperature, humidity, and wind were measured at an altitude of 2 m above ground. Other meteorological variables comprise precipitation, station pressure, solar irradiance, soil temperature at different depths and for high mountain station snow water equivalent. The stations produced data summaries for 5-minute-precipitation-data, 10- or 15-minute-data and a daily summary of all other variables. This network is a unique resource of multi-year weather data in the remote semi-arid to arid mountain region of the Saharan flank of the Atlas Mountains. The network is described in Schulz et al. (2010) and its further continuation until 2012 is briefly discussed in Redl et al. (2015, doi:10.1175/MWR-D-15-0223.1) and Redl et al. (2016, doi:10.1002/2015JD024443).

Weather forecaster at work

Inscription: Verso: Laura Cole, weather forecaster, at radar scope, U.S. weather service.