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The purpose of this paper is to propose an improved reinsurance pricing framework, which includes a crop yield forecasting model that integrates weather variables and crop production information from different geographically correlated regions using a new credibility estimator, and closed form reinsurance pricing formulas. A yield restatement approach to account for changing crop mix through time is also demonstrated.

The new crop yield forecasting model is empirically analyzed based on detailed farm-level data from Manitoba, Canada, covering 216 crop varieties from 19,238 farms from 1996 to 2011. As well, corresponding weather data from 30 stations, including daily temperature and precipitation, are considered. Algorithms that combine screening regression, cross-validation and principal component analysis are evaluated for the purpose of achieving efficient dimension reduction and model selection.

The results show that the new yield forecasting model provides significant improvements over the classical regression model, both in terms of in-sample and out-of-sample forecasting abilities.

The empirical analysis is limited to data from the province of Manitoba, Canada, and other regions may show different results.

This research is useful from a risk management perspective for insurers and reinsurers, and the framework may also be used to develop improved weather risk management strategies to help manage adverse weather events.

This is the first paper to integrate a credibility estimator for crop yield forecasting, and develop a closed form reinsurance pricing formula.

The purpose of this paper is to compare the ability of popular temperature models, namely, the models given by Alaton et al., by Benth and Benth, by Campbell and Diebold and by Brody et al., to forecast the prices of heating/cooling degree days (HDD/CDD) futures for New York, Atlanta, and Chicago.

To verify the forecasting power of various temperature models, a statistical backtesting approach is utilised. The backtesting sample consists of the market data of daily settlement futures prices for New York, Atlanta, and Chicago. Settlement prices are separated into two groups, namely, “in‐period” and “out‐of‐period”.

The findings show that the models of Alaton et al. and Benth and Benth forecast the futures prices more accurately. The difference in the forecasting performance of models between “in‐period” and “out‐of‐period” valuation can be attributed to the meteorological temperature forecasts during the contract measurement periods.

In future studies, it may be useful to utilize the historical data for meteorological forecasts to assess the forecasting power of the new hybrid model considered.

Out‐of‐period backtesting helps reduce the effect of any meteorological forecast on the formation of futures prices. It is observed that the performance of models for out‐of‐period improves consistently. This indicates that the effects of available weather forecasts should be incorporated into the considered models.

To the best of the author's knowledge this is the first study to compare some of the popular temperature models in forecasting HDD/CDD futures. Furthermore, a new temperature modelling approach is proposed for incorporating available temperature forecasts into the considered dynamic models.

Climate change continues to pose a serious challenge to mankind. Given their socio-economic and vulnerable situations, resource-poor farmers will be hard hit and likely to be the most affected group in Africa – a continent that will bear the full brunt of inclement weather conditions. The purpose of this paper is to address the questions of how local farmers read and predict the weather, and how best they can collaborate with weather scientists in adapting to climate change and variability in the Okavango Delta of Botswana.

A multi-stage sampling procedure was employed in sampling a total of 592 households heads (both men and women) in eight rural communities in the Okavango Delta, Botswana.

Analysis indicates that about 80 per cent of the farmers had a good knowledge of weather forecasting. In a knowledge validation workshop organised and implemented in early August 2012, farmers and scientists identified a nine-point agenda and strategies for addressing the challenges posed by climate change to community well-being and agricultural production. Knowledge sharing, installation of community weather stations and local-level capacity building are amongst the strategies identified.

The research is only limited to the Okavango Delta, Botswana.

The paper emanates from original field research. The outcome of the paper provides pertinent information for policy formulation on how best to enhance small farmers’ adaptation to climate change.

After many years’ practice and experiments, it was found that quantitative analysis systems with unequal quantitative effect cannot be extended into that with equal quantitative effect. While it is related to such epistemological viewpoints as irregularity and continuity systems, an infrastructural form comparison has shown universally scientific and methodological characteristics. In combination with evolution of weather systems, our infrastructural analysis involves applications of super low temperatures, reversed information order, rolling currents infrastructure in reversal weather change and long‐term weather forecasting.

The purpose of this paper is to propose a multi-variable analysis (MVA) model for predicting potential delays in the delivery of subsea inspection, maintenance and repair (IMR) services.

Based on data from 351 subsea IMR service jobs executed between 2006 and 2008, a MVA model is proposed for predicting the potential delays in the delivery of IMR services in different plausible scenarios.

A model for predicting the delays in IMR service delivery, based on four practical variables that are readily available during the planning phase, was developed and tested. The factors contributing to delays in petroleum subsea IMR services based on importance are: water depth, weather, job complexity, job uncertainty as well as job complexity mix.

The MVA model is developed based on analyzing subsea IMR service jobs performed in the petroleum industry from 2006-2008. The model can be used in the planning stage to predict potential delays in service delivery based on practical variables available.

The research proposes a MVA model for predicting delays in service delivery. The model is useful for predicting potential delays in service delivery and for improving the plan based on model analysis results.

Blown up theory is very important in modern forecasting science, and will result in revolution not only in forecasting theories but also in applied theories and applied methods. Moreover, the blown‐up theory will involve re‐thinking and re‐formulation of some concepts in traditional theories. This article is a record of dialogue between Professor OuYang and the author on some important issues. It is believed that this record will not only benefit us greatly, but also be inductive for young generations in developing their way of thinking and research directions.

The purpose of this paper is to present an overview of weather derivatives markets and to highlight the importance of the contributing factors for weather risk management such as weather sensitivity, weather forecast, and economic growth. In this paper, the prospective of using weather derivatives in Portugal and why Portugal should use such instruments as well as the potential of Portugal's enterprises are presented.

This paper attempts to distinguish the reasons for the appearance of a weather derivatives market and the growth potential of the European weather market.

Successful development of a Portuguese weather derivatives market will require three things. For the successful development of weather derivatives market, a legal and economic framework is needed, as well as the development of new weather products, training of qualified specialists for working with these instruments and attracting companies interested in hedging their profits. A combination of these factors will help growth and will accelerate the development of a weather derivatives market in Portugal.

The paper identifies some conditions that could allow the progress of the weather derivatives market in Portugal.

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.

The objective of this research is to examine the performance of weather routing service in the North Pacific Ocean based on a global container shipping company.

The data comprise two passages: one that departs from the port of Taipei to the port of Los Angeles (TPE-LAX) and another that departs from the port of Tacoma to the port of Kaohsiung (TCM-KSG). A weather routing service was utilized to compare the differences of the distance, sailing time and fuel consumed among different voyages.

Results indicated that the average speed of vessel in winter is faster than in summer. The vessels consumed much more fuel in the winter than they did in the summer. In terms of the distance of the passage, the results show that the ships' sailing distance across the North Pacific Ocean in the summer was shorter than it was in the winter.

Due to the difficultly of practical data collection, relatively few sailing records were employed in this study. It is suggested that additional sailing records should be collected, which adopt weather routing recommendations, to more comprehensively analyze sailing performance in future research.

The study's findings offer valuable guidance to different stakeholders in the maritime industry (e.g. seafarers, marine hull and machinery companies, Protection and Indemnity Club (P&I), ocean container carriers and freight forwarders) to clarify their responsibilities in order to achieve desired sailing outcomes.

To the best of the authors' knowledge, the current study is the first research to utilize practical sailing data to provide objective evidence of sailing performance based on a weather routing service, which can assist various stakeholders to make optimal decisions.

The purpose of this paper is to examine knowledge-creating interaction in developing an innovation in a multidisciplinary research community with hermeneutic phenomenology, to understand how previous experiences and future prospects shape the process and to examine the circumstances, which support or limit knowledge creation.

The approach of this study is phenomenological and the empirical case study has been conducted using ethnography. The data consist of field notes, videos, interviews and documents of a BCDC energy consortium, developing energy weather forecast (EWF) in a new type of research environment.

The results indicate that the role of actual interactive events was crucial in the development of EWF. Hermeneutic approach illustrated that the roots of that event were in the past experiences of the participants and the circumstances, which promoted the development of the innovation, but the acknowledgment of the future prospects was crucial in finalizing the process. The role of a leader organizing the interaction and collaborative work was also substantial.

The results of this study could be used to plan and organize knowledge creation processes in organizations, especially in universities and research communities, striving to create multidisciplinary research environments and practices.

This study proposes a new approach based on hermeneutic phenomenology to examine it in a unified way, by focusing on the key aspects of elements affecting knowledge-creating interaction.