K. Sakai, N. Sakamoto, and K. Koyamada (Japan)
weather phenomena, low-pressure area, scalar field,critical point
The weather phenomena has been received attention from the ancient days and the data sets obtained from real-world measurements have been accumulating and being used for weather forecast as well as for understanding the weather phenomena. Nowadays the weather experts have surmised the association between the low-pressure area behavior and the weather changing phenomena in a local area. On the other hand, the massive amount of weather observation and measurement data sets has already accumulated and it will probably continue eternity. Thus, the massive data sets are going to be multiplied in the early future. If only the weather experts can analyze those data sets, the analyzed data sets will not accompany this increase and almost all data sets will be stored without being analyzed. By these reason, to overcome this problem, we propose critical point-based method for weather analysis which facilitates the understanding of the weather phenomena. By using this method, even a non-expert could make a specific weather analysis and obtain required information from it. We developed an evaluation module by using visualization software called AVS/Express to analyze weather-shifting phenomena by using critical points (CP). We evaluated this module by using a weather data set and we could verify that the critical points facilitate the understanding of the weather phenomena being analyzed.
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