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By reviewing recent literature, it is noticeable that considerable attention has been given to the relationship between all Atlantic hurricanes and those that make landfall in the USA. However, less research has been done regarding landfall frequency and identifying spatial areas that are statistically more likely to produce landfalling hurricanes. The purpose of this paper is to provide a better prediction method for US landfalling hurricanes.

This work is based on the hypothesis that landfall variations along the US coast can be better explained in terms of hurricane origination points over more susceptible areas on the North Atlantic Ocean. Simulation techniques are used to spatially quantify the landfall probability.

Results indicate the existence of a landfall corridor in the Atlantic Basin, which explains some of the variances observed in the landfall process. Two different hypotheses of climate are examined. A long‐term assumption is based on the historical data from 1940 to 2010. The second assumption is based on the Atlantic Multidecadal Oscillation. Since 1995, we are in a warm phase and we assume that sea surface temperatures remain warmer than the long‐term average over the next several years. Results indicate that the average increase on landfall frequency is about 13 per cent.

This paper is the first paper that introduces the concept of landfall origination corridor. It spatially identifies the differences between long term and warm phase of the atmosphere in terms of US landfall occurrence using hurricane origination points.

Climate change during the next century is likely to significantly influence forest ecosystems in the western United States, including indirect effects on forest and shrubland fire regimes. Further exacerbation of fire hazards by the warmer, drier summers projected for much of the western U.S. by climate models would compound already elevated fire risks caused by 20th century fire suppression. This has potentially grave consequences for the urban–wildland interface in drier regions, where residential expansion increasingly places people and property in the midst of fire-prone vegetation. Understanding linkages between climate variability and change, therefore, are central to our ability to forecast future risks and adapt land management, allocation of fire management resources, and suburban planning accordingly. To establish these linkages we review previous research and draw inferences from our own retrospective work focused on 20th century climate–fire relationships in the U.S. Pacific Northwest (PNW). We investigated relationships between the two dominant modes of climate variability affecting the PNW, which are Pacific Decadal Oscillation (PDO) and El Niño/Southern Oscillation (ENSO), and historic fire activity at multiple spatial scales. We used historic fire data spanning most of the 20th century for USDA Forest Service Region 6, individual states (Idaho, Oregon, and Washington), and 20 national forests representative of the region's physiographic diversity. Forest fires showed significant correlations with warm/dry phases of PDO at regional and state scales; relationships were variable at the scale of individual national forests. Warm/dry phases of PDO were especially influential in terms of the occurrence of very large fire events throughout the PNW. No direct statistical relationships were found between ENSO and forest fires at regional scales, although relationships may exist at smaller spatial scales. However, both ENSO and PDO were correlated with summer drought, as estimated by the Palmer Drought Severity Index (PDSI), and PDSI was correlated with fire activity at all scales. Even moderate (±0.3°C decadal mean) fluctuations in PNW climate over the 20th century have influenced wildfire activity based on our analysis. Similar trends have been reported for other regions of the western U.S. Thus, forest fire activity has been sensitive to past climate variability, even in the face of altered dynamics due to fire suppression, as in the case of our analysis. It is likely that fire activity will increase in response to future temperature increases, at the same or greater magnitude as experienced during past climate variability. If extreme drought conditions become more prevalent we can expect a greater frequency of large, high-intensity forest fires. Increased vulnerability to forest fires may worsen the current fire management problem in the urban–wildland interface. Adaptation of fire management and restoration planning will be essential to address fire hazards in areas of intermingled exurban development and fire-prone vegetation. We recommend: (1) landscape-level strategic planning of fire restoration and containment projects; (2) better use of climatic forecasts, including PDO and ENSO related predictions; and (3) community-based efforts to limit further residential expansion into fire-prone forested and shrubland areas.

A reliable forecast of hurricane activity in the Atlantic Basin has the potential to help mitigate the economic losses caused by hurricanes. One of the difficult problems is to make reasonable annual forecast of catastrophe losses based on the short record of historical observations. Atmospheric conditions tend to influence tropical cyclone development. Considering the complex interactions among climatological factors, prediction of future hurricane activity is challenging. In this study, the authors are attempting to predict the number of Atlantic hurricanes for a given year based on two different approaches.

In part I, an autoregressive integrated moving average (ARIMA) is used to model a long‐run behavior of Atlantic hurricane frequency. The authors present a comparison of CSU's forecast with ARIMA model. Part II focuses on the relationship between the climate signals and hurricane activity and introduces a new approach in including climate indices into the prediction model. In this part, principal components analysis (PCA) is used to identify possible patterns in historical data based on six climate indices measured prior to hurricane season. The objective is to reduce the data set to a smaller set while most of the variability observed in the real data is captured. The variances observed in an orthogonal system indicate the order of contribution of each mode shape.

Results from part I suggest that CSU's forecast model, in general, is superior to results obtained by ARIMA. In part II, the correlation between mode (shapes) and the number of Atlantic hurricanes per year is examined. The resulting relationships show that, for the time interval of 1990 through 2011, PCA‐based approach provides better estimates compared to CSU's forecast.

The paper presents a unique prediction approach which is simple, relatively accurate and easy to apply. The results of this study show that complex statistical analyses/models do not necessarily provide better forecasts.

Increasing demographic diversity within societies and workforces causes challenges with regard to the innovation performance of companies. By definition, innovation communities nowadays are composed of members with diverse function background and age diversity. The challenging question is how to manage diverse corporate innovation communities. The purpose of this paper is to find out which factors determine the success of corporate innovation communities in times of demographic shifts.

The empirical field to answer the research question are three corporate innovation communities in companies of different industries and size. Multiple case study methodology is applied to gather and analyse the data.

The study presents an empirically derived framework to structure success factors of diverse corporate innovation communities chronologically in the three phases of preparation, execution and finalization of a community work process. The success factors are described in detail and finally a time sequential guideline for those who are responsible for community management in demographic change is provided.

It is contributed to the literature on innovation communities and it is shown that innovation communities are not only an instrument to solve innovation tasks but are also a promising means to tackle other challenges of recent demographic changes. As limitation must be considered, that the analysed innovation communities only received corporate support for a short period of time and the supporting organizations operate in manufacturing industries in Germany only.

The paper highlights that managers need to be aware that diversity in corporate innovation communities per se does not lead to success. Furthermore, a guideline of success factors for managers of diverse corporate innovation communities is presented which highlights important aspects that managers need to consider during the community work process.

Due to demographic shifts in Germany and other European countries, societies in general and workforces in particular have modified. Most pervasive shifts take place with regard to age structures and diversity. Implications how manager could handle diversity successfully are therefore of high relevance for societies.

This study provides a theoretical understanding of the implications of organizational and age diversity on corporate innovation community management. Extant authors have already focussed on success factors in innovation communities and diverse settings isolated, but have not merged these issues.

In general, the insurance industry accepts large risks due to the frequency and severity of extreme events. Because of the short record on hazard data for such events, a large amount of uncertainty has to be dealt with. Given this large uncertainty it is important to better quantify the hazard parameters that are defined as inputs to the catastrophe models. The purpose of this paper is to evaluate the hurricane risk from loss point of view in the USA for both long‐term and warm phase conditions using a simulation‐based stochastic model.

A Poisson process is used to simulate the occurrence of events for both conditions. The generated event‐sets were used along with vulnerability and cost models to estimate the loss to an insurance industry portfolio. The paper discusses the statistics of events categorized by the Saffir‐Simpson Hurricane Wind Scale, annualized and return period losses and compares the results for both assumed long‐term and warm phase climate states.

The analysis shows that the population of landfall data for the two climate conditions is not statistically different. However, if we accept that a difference in the frequency of landfall occurrence between the two assumptions exists, the increase in average annual loss is about 17 per cent.

This paper provides insights to the difference between the two states of atmosphere from the point of view of insured losses for hurricanes and is one of the first papers that offers conclusion on the uncertainty associated with the warm phase data.

The purpose of this paper is to analyze the bulk energy transport processes in the build chamber environment before and during laser sintering (LS) to provide a basis for effective and accurate thermal control for the LS process. This leads to improved mechanical properties and geometrical tolerances for LS products and may be applied to optimize operation cycle times for the LS process.

Computational models with two levels of complexity were built to explore the heat transfer mechanisms in the LS process. In a one-dimensional model (1D), the powder performed as a semi-infinite solid and heater flux to the powder surface was modeled with a heater control law. A two-dimensional (2D) fluid/solid finite element model of the build chamber and powder bins provided insight into the thermal processes in the build chamber.

Numerical 1D simulations were verified with measurements from sensors embedded in the build chamber powder bed. Using a 2D model, computed powder surface temperatures during the warm up and build phases were verified with an infrared camera. Convective currents in the build chamber and non-uniformities in the distribution of temperature over the radiant heater surface were found to be substantial contributors to non-uniformities in the powder bed surface temperature.

Limited heat sources were analyzed. No three-dimensional model was built. Assumptions to decrease the part bed temperature difference were not tested.

These simulation and experimental results may be used to enhance thermal control and operation efficiency during the LS process and to improve LS product mechanical properties.

In the southern hemisphere, the Antarctic continent is also experiencing a net loss in ice from the extensive glaciers and ice sheets that cover it. However, the connection between changes in Antarctic ice sheets and the global warming trend are much more uncertain than in the Arctic. The complex of changes in the Antarctic climate and the ice sheets are described in a later section of this chapter.

THE requirements of commercial efficiency impose a life of 12 to 15 years, coupled with a high rate of utilization, on civil aircraft. This puts very special conditions for the construction of the airframe, as well as on the testing of its reliability and safety in service.

The purpose of this paper is to numerically model convective drying of a two‐dimensional iron ore pellet subjected to turbulent flow.

Simulations of the iron ore pellet drying process are carried out with commercial computational fluid dynamics software. The moisture distribution inside the pellet is calculated from a diffusion equation and drying due to evaporation at the surface is taken into account.

The results show an initial warm up phase with a succeeding constant rate drying period. Constant drying rate will only be achieved if the surface temperature is constant. The falling rate period will subsequently start at the forward stagnation point when the minimum moisture content is reached, while other parts of the surface still provide enough moisture to allow surface evaporation. The phases will thus coexist for a period of time.

Owing to the complex physical processes involved in iron ore pellet drying, some parameters in the model are based on estimations. The effective diffusivity should, for example, in the future be investigated more thoroughly. It is also important to extend the model so that the falling rate drying period is also included. The model is at present undergoing further validation.

The simulations can provide detailed information on some key fluid dynamics and physical processes that an iron ore pellet undergoes during drying.

The simulations enhance the understanding of iron ore pellet drying and the model provides a complement to experimental investigations when optimizing the drying process.