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The purpose of this paper is to describe a risk-based methodology developed to identify the severity of impacts to various types of infrastructure located within the Tennessee State Park system when exposed to extreme weather events. Infrastructure systems, composed of various assets, are central to the economic, environmental and cultural functioning of the society. Understanding the potential impacts to these assets from various threats is fundamental to prudent strategic, operational and financial decision-making. Among infrastructure, systems of interest are those managed and operated by park services. Such systems are particularly exposed to extreme weather, given the recreational activities that they provide.

This paper describes a risk-based methodology developed to identify the severity of impacts to various types of infrastructure located within the Tennessee State Park system when exposed to extreme weather events. It consists of the following steps: identifying extreme weather event types experienced in Tennessee; assessing damage to various types of park system infrastructure caused by these events; and deriving an overall impact score associated with specific types of park system infrastructure when exposed to certain types of extreme weather scenarios.

In applying this methodology, tornadic events were found to be most impactful, whereas drought and heat events had the least effect on park infrastructure. Dining and lodging infrastructure were found to incur the most damage, regardless of the weather event type.

The approach as described in this paper is transferable to other park systems as well as public sector assets in general.

Weather is often referred as an uncontrollable factor, which influences customer’s buying decisions and causes the demand to move in any direction. Such a risk usually leads to loss to industries. However, only few research studies about weather and retail shopping are available in literature. The purpose of this paper is to develop a model and to analyze the relationship between weather and retail shopping behavior (i.e. store traffic and sales).

The data set for this research study is obtained from two food retail stores and a fashion retail store located in Lower Bavaria, Germany. All these three retail stores are in same geographical location. The weather data set was provided by a German weather service agency and is from a weather station nearer to the retail stores under study. The analysis for the study was drawn using multiple linear regression with autoregressive elements (MLR-AR). The estimated coefficients of weather variables using MLR-AR model represent corresponding weather impacts on the store traffic and the sales.

The snowfall has a significant effect on the store traffic and the sales in both food and fashion retail stores. In food retail store, the risk due to snowfall varies depending on the location of stores. There are also significant lagging effects of snowfall in the fashion retail store. However, the rainfall has a significant effect only on the store traffic in the food retail stores. In addition to these effects, the sales in the fashion retail store are highly affected by the temperature deviation.

Limitations in availability of data for the weather variables and other demand influencing factors (e.g. promotion, tourism, online shopping, demography of customers, etc.) may reduce efficiency of the proposed MLR-AR model. In spite of these limitations, this study can be able to quantify the effects of weather variables on the store traffic and the sales.

This study contributes to the field of retail distribution by providing significant evidence of relationship between weather and retail business. Unlike previous studies, the proposed model tries to consider autocorrelation property, main and interaction effects between weather variables, temperature deviation and lagging effects of snowfall on the store traffic or the sales. The estimated weather impacts from this model can act as a reliable tool for retailers to explain the importance of different non-catastrophic weather events.

The current air traffic management (ATM) operational approach is changing; “time” is now integrated as an additional fourth dimension on trajectories. This notion will impose on aircraft the compliance of accurate arrival times over designated checkpoints (CPs), called time windows (TWs). This paper aims to clarify the basic requirements and foundations for the practical implementation of this functional framework.

This paper reviews the operational deployment of 4D trajectories, by defining its relationship with other concepts and systems of the future ATM and communications, navigation and surveillance (CNS) context. This allows to establish the main tools that should be considered to ease the application of the 4D-trajectories approach. This paper appraises how 4D trajectories must be managed and planned (negotiation, synchronization, modification and verification processes). Then, based on the evolution of a simulated 4D trajectory, the necessary corrective measures by evaluating the degradation tolerances and conditions are described and introduced.

The proposed TWs model can control the time tolerance within less than 100 s along the passing CPs of a generic trajectory, which is in line with the expected future ATM time-performance requirements.

The main contribution of this work is the provision of a holistic vision of the systems and concepts that will be necessary to implement the new 4D-trajectory concept efficiently, thus enhancing performance. It also proposes tolerance windows for trajectory degradation, to understand both when an update is necessary and what are the conditions required for pilots and air traffic controllers to provide this update.

The use of the 4D trajectory operational concept in the future air traffic management (ATM) system will require the aircraft to meet very accurately an arrival time over a designated checkpoint. To do this, time intervals known as time windows (TW) are defined. The purpose of this paper is to develop a methodology to characterise these TWs and to manage the uncertainty associated with the evolution of 4D trajectories.

4D trajectories are modelled using a point mass model and EUROCONTROL’s BADA methodology. The authors stochastically evaluate the variability of the parameters that influence 4D trajectories using Monte Carlo simulation. This enables the authors to delimit TWs for several checkpoints. Finally, the authors set out a causal model, based on a Bayesian network approach, to evaluate the impact of variations in fundamental parameters at the chosen checkpoints.

The initial results show that the proposed TW model limits the deviation in time to less than 27 s at the checkpoints of an en-route segment (300 NM).

The objective of new trajectory-based operations is to efficiently and strategically manage the expected increase in air traffic volumes and to apply tactical interventions as a last resort only. We need new tools to support 4D trajectory management functions such as strategic and collaborative planning. The authors propose a novel approach for to ensure aircraft punctuality.

The main contribution of the paper is the development of a model to deal with uncertainty and to increase predictability in 4D trajectories, which are key elements of the future airspace operational environment.

The purpose of the present paper is to review studies on weather index-insurance as a tool to manage the climate change impact risk on farmers and to explore the study gaps in the currently existing literature by using a systematic literature review.

This study analyzed and reviewed the 374 articles on weather index insurance (WII) based on a systematic literature search on Web of Science and Scopus databases by using the systematic literature review method.

WII studies shifted their focus on growing and emerging areas of climate change impact risk. The finding shows that the impact of climate change risk significantly influenced the viability of WII in terms of pricing and design of WII. Therefore, the cost of WII premium increases due to the uncertainty of climate change impact that enhances the probability of losses related to insured weather risks. However, WII has emerged as a risk management tool of climate insurance for vulnerable agrarian communities. The efficacy of WII has been significantly influenced by repetitive environmental disasters and climate change phenomena.

This study will be valuable for scholars to recognize the missing and emerging themes in WII.

This study will help the policy planners to understand the influence of climate change impact on WII viability.

This study is the original work of the author. An attempt has been made in the present study to systematically examine the viability of WII for insuring the climate change risk.

The purpose of this paper is to delve into an extensive analysis of different food crops, ranging from bananas, beans, brinjals, cabbages, chillies, creepers, groundnuts, mixed vegetables, pineapples and tomatoes, over three decades. To maintain an ever-increasing population level, much stress is exerted on the production of food crops. However, till date, very little is known about how climate change is influencing the production of food crops in Mauritius, an upper-income developing country found in the Indian Ocean and highly vulnerable to climate risks.

Based on the interactions between production of crops, harvest area for crops and weather metrics, a vector autoregressive model (VAR) system is applied comprising production of each crop with their respective harvest area. Weather metrics are then entered into as exogeneous components of the model. The underlying rationale is that weather metrics are not caused by production or harvest area and should thereby be exogeneously treated. Should there be cointegration between the endogenous components, the vector error correction model (VECM) will be used. Diagnostic tests will also be entertained in terms of ensuring the endogeneity states of the presumed variables under investigation. The impact of harvest area on product is plain, as higher the harvest area, the higher is the production. However, a bi-directional causality can also manifest in the case that higher production leads towards lower harvest area in the next period as land is being made to rest to restore its nutrients to enable stable land productivity over time. Other dynamics could also be present. In case cointegration prevails, VECM will be used as the econometric model. The VAR/VECM approach is applied by virtue of the fact that traditional ordinary least squares (OLS) estimation approach will be biased and susceptible to trigger off unreliable results. Recourse is made towards the Johansen and Juselius (1990) technique. The Johansen and Juselius approach is based on the following VAR specification-bivariate VAR methodology. X1,t = A0 + A1,1X1,t – 1 + A1,2X1,t – 2+ […] .+ A1,p X1,t – p + A2,1X2,t – 1 + A2,2X2,t – 2+ […] .+ A2,pX2,t – p + ßjW + e1,t […] […]..(1) X2,t = B0 + B2,1X2,t – 1 + B2,2X2,t – 2+ […] .+ B2,p X2,t – p + B1,1X1,t – 1 + B1,2X2,t – 2+ […] .+ B1,pX2,t – p + ajW + e2,t […] […] […](2) X1,t is defined as the food crops production, while X2,t pertains to harvest area under cultivation for a given crop under consideration, both constituting the endogeneous components of the VAR. The exogeneous component is captured by W which consists of the nine aforementioned weather metrics, including the cyclone dummy. The subscript j under equation (1) and (2) captures these nine distinct weather metrics. In essence, the aim of this paper is to develop an econometric-based approach to sieve out the impacts of climate metrics on food crops production in Mauritius over three decades.

Results show weather metrics do influence the production of crops in Mauritius, with cyclone being particularly harmful for tomatoes, chillies and creepers. Temperature is found to trail behind bearish impacts on tomatoes and cabbages production, but positive impacts in case of bananas, brinjals and pineapples productions, whereas humidity enhances production of beans, creepers and groundnuts. Evidence is found in favour of production being mainly governed by harvest area. Overall, the study points out the need of weather derivatives in view of hedging against crop damages, let alone initiation of adaptation strategies to undermine the adverse effects of climate change.

To the best of the author’s knowledge, no study has been undertaken in Mauritius, let alone developing of an econometric model that properly integrates production, harvest area and weather metrics. Results show weather metrics do influence the production of crops in Mauritius, with cyclone being particularly harmful for tomatoes, chillies and creepers. Temperature is found to trail behind bearish impacts on tomatoes and cabbages production, but positive impacts in case of bananas, brinjals and pineapples productions, whereas humidity enhances production of beans, creepers and groundnuts. Evidence is found in favour of production being mainly governed by harvest area. Overall, the study points out the need of weather derivatives in view of hedging against crop damages, let alone initiation of adaptation strategies to undermine the adverse effects of climate change.

The purpose of this paper is to discuss the current state of FM preparedness required to deal with the risks to healthcare delivery posed by climate change‐related extreme weather events.

Selected stakeholders were invited to participate in targeted focus groups that, using the ROMS methodology, explored the status of current knowledge and preparedness of the NSW health system to deal with the expected demands imposed by increasing incidences of extreme weather events. Findings are summarised and discussed in terms of the key stakeholder objectives identified. Further areas of required research are then discussed.

The key objectives of the stakeholders were readily agreed, however a lack of information regarding the quantifiable impacts forecast to be associated with climate change constrained the development of other than generic strategies for dealing with these impacts. Further areas of research included assessment of changing demand for health services, likely physical impacts on facilities and their adequacy in coping with these, implementation strategies for augmenting coping capacity and associated costs, plus the need for integrating disaster planning and management strategies to ensure the continuity of operation of health facilities during extreme weather events.

The paper outlines the status of current knowledge regarding the likely impact of climate change‐related extreme weather events on healthcare infrastructure. It explores key issues and determines where future work should be undertaken to ensure that rigorous FM responses are available to cope with a clear and identified threat to the health of the Australian, and similar communities.

The purpose of this paper is to describe the current climate change predictions and the likely consequences for building assets, and therefore the delivery of public services, in the face of extreme weather events. Public sector asset managers need to mitigate and prepare for future events. However, current practice, as illustrated by the literature, shows that little risk assessment is currently undertaken.

This paper is based on a literature review of current climate data and best practice asset management. An extensive survey of public sector asset managers working at senior levels in their organisation was designed and distributed to gather data on the current levels of disaster and business continuity planning. The survey design sought to establish the level of risk assessment across the organisations and the integration of property management into the disaster planning process.

This paper describes the current climate change predictions and the likely consequences for building assets in the face of extreme weather events. It reveals that a significant number of public sector authorities are not preparing integrated disaster management plans nor business continuity plans. There is a need for further research into the impact on assets and the role of the public sector real estate manager in assessing the risks and developing strategies to prepare the organisation and to mitigate the effects of natural disasters and severe weather events.

This research highlights the potential for climate change to threaten property assets and particularly to compromise the delivery of public services in the event of extreme weather events. The paper highlights the need for integrated risk assessment and disaster planning, which incorporates enabling property assets. Public sector asset managers have a vital role to play in undertaking risk assessment and preparing disaster plans. This role is becoming increasingly important as climate change is predicted to have a significant effect on the frequency of extreme weather events and the occurrence of natural disasters.

In the wake of the COVID-19 pandemic, India's tourism industry has the opportunity to further grow and expand through the development and implementation of sustainable policies. The diversity of India's geography is observed in its weather which is variable both spatially and temporally throughout the year. Seasonal changes in weather influence the number of foreign tourists arrivals in India. Consequently, significant reductions in visitor numbers are observed during the monsoon season. In future decades, the changing climate has the potential to shape tourism patterns. Warmer temperatures and an increased frequency of high-intensity rainfall are the two most common predictions concerning future climate in India. It will result in a shorter winter tourism season in the northern states where the cold weather enables winter sports activities such as skiing and snowboarding. Coastal tourism along India's stretched coastline may become less attractive to tourists due to damage and disruption to coral reefs and marine wildlife. Sea-level rise and coastal erosion may push beach tourists to more desirable and scenic destinations. India's transport infrastructure is key to enabling the safe and efficient movement of tourists around the country. The current weather is already impacting the air, road and rail networks and, further challenges are highly likely due to a changing climate. There is still an opportunity for India's tourism industry to adapt through physical and policy developments. It would make India a more competitive and sustainable tourism destination.