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The weather largely affects economic activity, and thus, companies vulnerable to weather risk need to plan ahead to cope with unexpected weather changes, just as they do for changes in interest rates, oil prices, or foreign exchange rates to stabilize their earning stream. Weather derivatives can be a useful tool for weather risk management.

This paper focuses on pricing one of the most popular weather derivatives -HDD/CDD options- and estimating the market price of weather risk (MPR). Historical data are used to construct the stochastic process of temperature, while the current market prices of Chicago and New York HDD futures options are used to extract the implied MPR. The Monte-Carlo Simulation Method is proposed to estimate the price of weather derivatives numerically. In addition, the approximate closed form formula for the options is provided modifying the Alaton, Djehiche, and Stillberg (2002) model. Finally, option price sensitivity to changes in MPR is analyzed to show the important role of the MPR in the weather option pricing model.

Five factors are a prerequisite for tourism: Ability to travel and motivation to travel on the demand side, and attractiveness, amenities and accessibility on the side of the destination. Concerning the attractiveness of a destination, the factor weather is of particular importance. Until now, there is a lack of empirical data, showing if and how weather affects holiday destination preferences.

The purpose of this study is to demonstrate the use of weather derivatives to hedge firm exposure to previously unmanageable risk events caused by natural phenomenon such as excessive rainfall.Design/methodology/approach – The paper adopts a case study approach to meet the objectives above, focusing on golf courses in the Midwest USA, which provide perfect examples of businesses with seasonal cash flows.Findings – It is shown that a firm can reduce its revenue volatility by up to 80 per cent. Weather derivatives are important additions to firm portfolios of risk management tools. Purchasing weather derivatives will improve the owner's ability to forecast revenues and assure expenditure coverage, both important goals for a small business owner.Practical implications – Many firms find the uneven revenue streams associated with their industry to be difficult to manage. One of the primary risks faced by firms is exposure to weather phenomena. With the introduction of weather derivatives, firms can now hedge their exposure to climatologic events. The application for weather derivatives is quite limitless. Weather derivatives are a relatively new product, and most firms are either unaware of their existence or believe them to be complicated. It is an industry that may experience explosive growth in the coming years.Originality/value – This paper demonstrates the use of derivatives to hedge exposure to climatic events.

One of the sectors most affected by the variable weather events caused by climate change and global warming is the aviation sector. Especially in aircraft accidents, weather events increasing with climate change and global warming are effective. The purpose of this study is to determine how much the change in weather conditions caused by global warming and climate changes affect the aircraft in the world between the years 2010 and 2022.

In this study, it was investigated which weather events were more effective in aircraft crashes by determining the rates of air events and aircraft crashes in aircraft crashes with a passenger capacity of 12 or more that occurred between 2010 and 2022.

It is clearly seen that increasing weather conditions with global warming and climate change increase the effect of weather conditions in aircraft crashes.

The difference of this study from other studies is the evaluation of the data of the past 12 years, in which the increasing consequences of global warming and climate change have been felt more. It also reveals the necessity of further research on the effects of weather conditions on aircraft.

The climate in Mendoza is significantly different from the climate in most global wine-making regions. This paper aims to explore the relationship between the quality of the Malbec wine from the Mendoza region and its weather.

This study uses a multivariate regression model with fixed effects to assess how weather variations relate to wine quality. The Wine Spectator ratings are used as a measure of wine quality and to build a longitudinal data set of Malbec wine ratings from 1995 to 2020. The weather is described with several variables based on temperature, rainfall, humidity and cloudiness data from the Mendoza region. The model controls for wineries which are treated as fixed effects.

The results of this study indicate that the weather has a modest explanatory power when it comes to the quality of Mendoza’s Malbec. Additionally, the analyses show that the wineries are more important than the weather to explain quality differences in the wines. These findings are in agreement with previous studies carried out in regions with stable weather such as California and Australia.

The quality of Mendoza’s Malbec depends more on the winery of origin than the year-to-year weather variations. Therefore, consumers should focus more on the winery and less on the vintage when making purchasing decisions. Additionally, given the relevance of the winery in relation to quality, the findings of this study indicate that future research efforts should focus on directly linking the wine ratings to quality-drivers behind the winery effects.

To the best of the authors’ knowledge, this is the first study that explores the relationship between wine quality assessed through wine ratings and the weather in the Mendoza (Argentina) region. Most such studies have been done in connection with northern hemisphere wines.

The authors investigate whether an index-based weather insurance (WII) product can complement or replace existing traditional crop yield insurance for mitigating farmers' financial risks, with an application to blueberry growers in British Columbia (BC).

A hybrid model combining expected utility (EU) and prospect values is developed to analyse farmers' demand for WII.

While weather data are used to investigate supply elements, a hybrid model combining EU theory and prospect theory (PT) is developed to analyse farmers' demand for WII. On the supply side, a quality index is constructed and the relationship between the quality index and key weather parameters is quantified using a partial least squares structural model. The authors then model weather parameters via time-series analysis and statistical distributions to provide reasonable estimates for calculating actuarially sound insurance premiums for a rainfall indexed, insurance product. This model indicates that decreases in the proportion of a blueberry grower's total revenue and revenue volatility will decrease the possibility that they participate in WII. At the same time, an increase in the value loss aversion coefficient and WII's basis risk further leads to less demand for WII. In short, a grower may decide not to participate in WII at an actuarially fair premium due to the combined effects of the above factors. Overall, while the supply analysis enables us to demonstrate that WII can potentially help in mitigating farmers' financial risks, it turns out that, on the demand side, blueberry growers are unwilling to pay for such a product without large government subsidies.

The authors argue that the demand for insurance may be affected by the level and the volatility of a berry grower's total revenue. Hence, the authors propose a hybrid expression that assumes a farmer seeks to maximize the total utility function to capture the rational and intuitive parts of a farmer's decision-making process. The EU represents rationality and the prospect value represents the intuitive component. Meanwhile, the authors investigate the possibility of using key weather parameters to construct a berry quality index – one that could be applied to other agricultural areas for studying the relationship between weather conditions and product quality.

This article is about reference books that can answer questions about the typical weather for a city in the United States or the actual weather on a given day in the past.

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.

Purpose of the study is to further expand insights into how weather impacts attendance at sporting events. With the NFL having only eight home games a year per team, it is more of an event than other North American sports. We explore this in terms of how sensitive fans are to weather, by not only looking at traditional factors, but also other weather variables available through Accuweather. In addition, the authors explore team success, outcome uncertainty and other factors as determinants of demand.

The method includes Tobit model of attendance in terms of percent of capacity in the National Football League. Model includes factors such as outcome uncertainty, team success, etc. but mainly focuses on weather. Weather factors studied include traditional variables such as temperature and precipitation, and also includes cloud cover, barometric pressure, wind speed and humidity. Different model specifications are included to explore results. Key findings allow for differences between games played outdoors versus indoors.

In terms of control variables, team success, new stadiums and stadium age play a significant role in attendance in terms of percentage of capacity. Outcome uncertainty does not appear to be important, and fans desire the opposite when the home team is an underdog. The main results concern the weather. When only traditional weather variables are included, precipitation plays a key role. With further expansion of the weather variables, it appears that cloud cover offers some additional information beyond precipitation. In addition, barometric pressure plays a minor, but statistically significant role as it relates to attendance in terms of capacity.

Including deeper and richer weather data helps to further explain attendance at sporting events. With the NFL, this may be limited by it being such as event due to the scarcity of games in a season. In addition, the weather variables are not truly independent, although they are not as correlated as may be anticipated on the surface. Use of different types of weather variables in models of attendance may help to deepen our understanding of factors influencing consumer decisions. These factors may play larger roles in sports with wider variance in attendance during the season.

The practical implications are that other weather-related variables besides temperature and precipitation may offer insight into consumer decisions related to attendance at sporting events. Cloud cover gives insights into anticipated poor weather in addition to it directly leading to less of a sunny day to be outdoors at an event. Barometric pressure has been shown to influence headaches and joint pain and may also influence consumer decisions to venture out to sporting events.

As data becomes more widely available in general, it's possible to add additional insights into factors influencing various forms of decision-making. In this study, we show that more information on weather can shed insights into consumer decisions as it relates to attending events such as sports. These decisions likely differ based upon whether the event is held outdoors or indoors. With more entertainment choices as substitutes, it is important to identify key factors which influence consumer decisions to help better structure events in the future.

Weather variables beyond temperature and precipitation are included in a Tobit model for NFL attendance using percentage of capacity as the dependent variable. These weather variables are cloud cover, wind speed, humidity, and barometric pressure. Cloud cover and barometric pressure were found to have some significant effects on percentage of capacity. When included, precipitation itself is no longer found to be significant, but precipitation interacted with games played in domes retains statistical significance as there are key differences between games held outdoors versus indoors.

The purpose of this study is to examine the level of automation in Nigerian meteorological stations.

It involves a descriptive survey of the assessment of the use of information and communication technology (ICT) in data storage and dissemination in Nigerian meteorological stations. Questionnaires were used as the major instruments of data collection while interviews were still used to gather some peculiar data. Questionnaires were sent to each of the 46 meteorological stations and 11 to weather stations in some Nigerian universities. Out of the 57 questionnaire only 15 were returned and used for the study. The results are presented in tables and analysis using simple percentages.

The results showed a low level of automation because only two of the meteorological and weather stations in Nigeria are automated. The study also revealed that CLICOM software is very effective in weather information management. Similarly, the result showed that the CLICOM software is highly useful in the making of weather maps, charts and for quick dissemination of weather data, map and other information to students, university and public libraries who request such information. The reasons for the low level of automation were attributed to a lack of funds, faulty equipment and obsolete computer systems. It is therefore highly recommended for the Nigerian government to make funding available for the automation of the Nigerian meteorological stations and weather stations in Nigerian universities to ease data management and dissemination of weather information in Nigeria.

This research and its findings will assist the Nigerian meteorological service agencies in quick dissemination and retrieval of weather information to airports, university and research libraries and to the public in general.