This study was undertaken to investigate the effects of a large city on heavy rainfall in Tokyo, Japan, based on an ensemble simulation with a large number of members. An ensemble simulation (24 members) of eight brief heavy rainfall events that occurred from 1999 to 2007 was performed. The ensemble simulation was performed using five objective analysis datasets [Japanese 25-yr Reanalysis (JRA-25), Regional Analysis (RANAL), NCEP Final Operational Global Analysis (NCEP-FNL), NCEP-Department of Energy Global Reanalysis 2 (NCEP/DOE-R2), and Global Analysis (GANAL)]. Land-use distributions of two types were prepared for numerical simulations: actual land use and virtual land use, in which all urban land use was converted to vegetation. Each member was simulated using actual land use and virtual land use. The effects of the urban area were then assessed by comparing the results of these simulations. Results indicate no large differences in the wind systems of the Kanto plain (roughly 100 km 3 100 km), where Tokyo is located, even if cities were converted entirely to vegetation. The influence of cities on wind systems of this scale was negligible. However, changes of wind convergence were found leeward of the urban area, which increased the horizontal vapor flux there. The precipitation also increased there due to the urban effects, despite the decrease in vertical vapor flux from the land surface. It is concluded that urban effects for Tokyo alter the wind characteristics leeward of the urban area and develop wind convergence and rainfall there.

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Offshore installations are exposed to several natural hazards. The greatest is severe weather caused by hurricanes and cyclones. Such storms can be devastating, causing widespread damage and financial loss. Insurance companies offer a range of products that insure against potential losses, including physical damage, control of well, sue and labour, removal of wreck, business interruption and liability. This paper describes the development of the first stochastic natural catastrophe model for the northwest Australian coastal region. It is based on Monte Carlo simulations and uses scientific and engineering knowledge alongside actual insurance claims data to evaluate aggregate storm exposures for the offshore industry in this region. The model enables quantitative assessment of cyclone risk by developing an improved database through the compilation of available meteorological data. Its development is designed to allow the sustainable and reasonably priced supply of insurance, which is essential to the further extension of exploration and production activities and investment in Australia.

Based on a questionnaire survey, this study investigates how local residents regard the strong local wind Matsubori-kaze, which occurs at Mt. Aso in Kumamoto prefecture. We distributed questionnaire sheets to students of Ozu-Higashi Elementary School, where Matsubori-kaze frequently occurs, and received 25 responses from their families. The collection rate was 71％. Application of quantification theory type III to overall replies to six questionnaires reveals that recognition of Matsubori-kaze by local residents was explained primarily according to their experiences with this strong local wind. However, duration of residence in this region was not related directly to the overall responses. The recognition of Matsubori-kaze differed between duration of residence of 31-45 years and that of 61-75 years. Analyses of key words used in responses from the respective groups reveals that the former (duration of residence of 31-45 years) had a strong adverse perception of Matsubori-kaze in the outdoors, whereas the latter (duration of residence of 61-75 years) , which was engaged mainly in agriculture, had a fatalistic acceptance of this strong local wind. Application of quantification theory type III to 56 key words that appeared in multiple questionnaire sheets reveals that these key words can be summarized as "strength and mode of Matsubori-kaze," "agricultural damage in areas with strong winds," and "surrendering to