Authors: Yun Li*, george mason university, Runxin Yang, George Mason University, Chaowei Yang, George Mason University
Topics: Geographic Information Science and Systems
Keywords: clustering, tropical cyclones, rapid intensification, spatial-temporal analysis
Session Type: Paper
Start / End Time: 8:00 AM / 9:40 AM
Room: Oak Alley, Sheraton, 4th Floor
Presentation File: No File Uploaded
Tropical cyclones(TCs) usually cause severe damages and destructions. TC intensity forecasting helps people prepare for the extreme weather and could save lives and properties. Rapid Intensifications (RI) of TCs are the major error sources of TC intensity forecasting. A large number of factors, such as sea surface temperature, wind shear, affect the RI processes of TCs. Quite a lot of work has been done to identify the combination of conditions most favorable to RI. Identifying the combination of conditions is time-consuming either using traditional statistical data analysis methods or state-of-art data mining methods since mass spatial-temporal data with hundreds of variables are collected and analyzed in the process. In this study, clustering techniques are applied to the high dimensional atmosphere and hurricane data to identify the ‘‘optimal’’ RI condition combinations.