Abstract:The climatology of tropical cyclones is an immediate research need, specifically to better understand their long-term patterns and elucidate their future in a changing climate. One important pattern that has recently been detected is the poleward shift of the lifetime maximum intensity (LMI) of tropical cyclones. This study further assessed the recent spatial changes in the LMI of tropical cyclones, specifically those of tropical storm strength or stronger in the North Atlantic and northern West Pacific basins. Analyses of moving decadal means suggested that LMI locations migrated south in the North Atlantic and north in the West Pacific. In addition to a linear trend, there is a cyclical migration of LMI that is especially apparent in the West Pacific. Relationships between LMI migration and intensity were explored, as well as LMI location relative to landfall. The southerly trend of LMI in the North Atlantic was most prevalent in the strongest storms, resulting in these storms reaching their LMI farther from land. The relationship between intensity and LMI migration in the West Pacific was not as clear, but the most intense storms have been reaching LMI closer to their eventual landfall location. This work adds to those emphasizing the importance of understanding the climatology of the most intense hurricanes and shows there are potential human impacts resulting from any migration of LMI.
In this paper, we present a suite of visualization techniques for sensor-based transportation system data at different scales to facilitate the exploration of interconnected traffic dynamics at intersections and highways. These techniques are designed for analyzing multivariate traffic data from radar-based highway sensors and camera-based intersection sensors recording turn movements and vehicle speed, in the Chattanooga Metropolitan Area, with the capability of (a) revealing multiscale mobility patterns using different levels of data aggregation (e.g., individual sensor for microscale, multiple sensors along a corridor for mesoscale, and a larger number of sensors across the region for macroscale visualization) at different intervals (e.g., 5-min intervals, time of day, full day, and day-of-the-week), and (b) exploring the spatial variation of multiple traffic-related variables (e.g., volumes, speeds, turn movements, and traffic light colors) provided by the sensors. We close with a case study to demonstrate the effectiveness of our multiscale and multivariate visualization techniques. At microscale, we focused on intersection data from a shopping district around Shallowford Road in East Chattanooga. For mesoscale visualization, we studied the Shallowford Road corridor and an adjacent stretch of I-75. At macroscale, we included highway data from the Chattanooga Metropolitan Area. All visualizations were integrated into a web-based situational awareness tool to promote user access and interaction. At a minimum, each visualization provides the option for selecting dates for real-time (depending on sensor availability) and historical data, and additional information on hovering, though most provide more detailed information, including different views of the selected data, or interactive highlights.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.