Uncertainty Analysis for Computer Model Projections of Hurricane Losses

Projecting losses associated with hurricanes is a complex and difficult undertaking that is wrought with uncertainties. Hurricane Charley, which struck southwest Florida on August 13, 2004, illustrates the uncertainty of forecasting damages from these storms. Due to shifts in the track and the rapid intensification of the storm, real-time estimates grew from 2 to 3 billion dollars in losses late on August 12 to a peak of 50 billion dollars for a brief time as the storm appeared to be headed for the Tampa Bay area. The storm hit the resort areas of Charlotte Harbor near Punta Gorda and then went on to Orlando in the central part of the state, with early poststorm estimates converging on a damage estimate in the 28 to 31 billion dollars range. Comparable damage to central Florida had not been seen since Hurricane Donna in 1960. The Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) has recognized the role of computer models in projecting losses from hurricanes. The FCHLPM established a professional team to perform onsite (confidential) audits of computer models developed by several different companies in the United States that seek to have their models approved for use in insurance rate filings in Florida. The team's members represent the fields of actuarial science, computer science, meteorology, statistics, and wind and structural engineering. An important part of the auditing process requires uncertainty and sensitivity analyses to be performed with the applicant's proprietary model. To influence future such analyses, an uncertainty and sensitivity analysis has been completed for loss projections arising from use of a Holland B parameter hurricane wind field model. Uncertainty analysis quantifies the expected percentage reduction in the uncertainty of wind speed and loss that is attributable to each of the input variables.     

The organizational formation of atmospheric science

In this paper, the history of atmospheric science is traced, from the earliest discussions from meteorologists, and the first meetings to describe this new research area. The development of atmospheric science proceeded in three phases with each phase being marked by the attempt to organize resources, and bring into the atmospheric science network, scientists from other fields. I argue here that this construction of a science provides evidence of the social nature of science as well as the importance of organizations to the creation of a science.     

Stress at work and psychological and immunological parameters in a group of Norwegian female bank employees

This study concerned the immunological correlates of stress and work. Self reported stress, emotional state, ego-strength, and defensiveness were examined in relation to measures of cellular immunity (T-cell response to Con A and number of T4 and T8 cells) and humoral immunity (concentrations of immunoglobulins and complement components in plasma) in a group of 96 Norwegian female bank employees. The analyses showed that workload, the stress factor with the highest group mean, was associated with number of T-cells, while strain due to body posture during work was related to concentrations of IgM and C3. Further, depression was significantly correlated with IgM concentration and T-cell number, and anxiety with C3 concentration. T-cell activity was the immunological parameter most consistently associated with psychological well-being, showing positive correlations with defensiveness and ego-strength and negative correlations with anxiety and depression. In conclusion, T-cell number and concentrations of IgM and C3 were sensitive to both work-related stress experience and emotional distress. Coping abilities, indicated by the MMPI Ego-strength scale and emotional distress, were reflected in T-cell activity; insufficient coping was associated with low T-cell activity.     

Community Economic Development Strategies in Rural Washington: Toward a Synthesis of Natural and Social Capital*

Abstract Routes to economic development attract considerable attention in community and rural sociology. Social scientists draw increasingly on studies of social capital and environmental surroundings as they examine the factors that facilitate and inhibit economic development. However, few empirical analyses exist that analyze the impact of the combination of social infrastructure and natural capital on different forms of economic development such as on industrial recruitment and self‐development. Using data collected from six communities in Washington State, the interaction of a community's social infrastructure and natural capital on industrial recruitment and self‐development efforts is examined. Results suggest that while natural capital positively impacts a community's successful recruitment of outside industries, it is not significant for a community's level of self‐development. However, a community's social infrastructure, measured by the existence of active civic organizations, local businesses that support local community projects, community‐wide fund‐raising capacity, and extra‐local linkages to nearby communities, state, and national agencies, positively affects both industrial recruitment and self‐development. These findings illustrate the need for communities and local activists to carefully weigh their advantages and potential shortcomings when deciding on an economic development strategy.