Analysis of North Atlantic Tropical Cyclone Intensify Change Using Data Mining ...
Tropical cyclones (TC), especially when their intensity reaches hurricane scale, can become a costly natural hazard. Accurate prediction of tropical cyclone intensity is very difficult because of inadequate observations on TC structures, poor understanding of physical processes, coarse model resolut...
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Format: | Thesis |
Language: | English |
Published: |
George Mason University
2010
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Online Access: | https://dx.doi.org/10.13021/mars/6970 https://mars.gmu.edu/handle/1920/5832 |
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author | Tang, Jiang |
author_facet | Tang, Jiang |
author_sort | Tang, Jiang |
collection | DataCite |
description | Tropical cyclones (TC), especially when their intensity reaches hurricane scale, can become a costly natural hazard. Accurate prediction of tropical cyclone intensity is very difficult because of inadequate observations on TC structures, poor understanding of physical processes, coarse model resolution and inaccurate initial conditions, etc. This study aims to tackle two factors that account for the underperformance of current TC intensity forecasts: (1) inadequate observations of TC structures, and (2) deficient understanding of the underlying physical processes governing TC intensification. To tackle the problem of inadequate observations of TC structures, efforts have been made to extract vertical and horizontal structural parameters of latent heat release from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data products. A case study of Hurricane Isabel (2003) was conducted first to explore the feasibility of using the 3D TC structure information in predicting TC intensification. ... |
format | Thesis |
genre | North Atlantic |
genre_facet | North Atlantic |
id | ftdatacite:10.13021/mars/6970 |
institution | Open Polar |
language | English |
op_collection_id | ftdatacite |
op_doi | https://doi.org/10.13021/mars/6970 |
publishDate | 2010 |
publisher | George Mason University |
record_format | openpolar |
spelling | ftdatacite:10.13021/mars/6970 2025-04-27T14:33:19+00:00 Analysis of North Atlantic Tropical Cyclone Intensify Change Using Data Mining ... Tang, Jiang 2010 https://dx.doi.org/10.13021/mars/6970 https://mars.gmu.edu/handle/1920/5832 en eng George Mason University Data mining Tropical cyclone intensity Apriori algorithm SHIPS Rapid intensification Dissertation Other Thesis thesis 2010 ftdatacite https://doi.org/10.13021/mars/6970 2025-04-02T14:42:33Z Tropical cyclones (TC), especially when their intensity reaches hurricane scale, can become a costly natural hazard. Accurate prediction of tropical cyclone intensity is very difficult because of inadequate observations on TC structures, poor understanding of physical processes, coarse model resolution and inaccurate initial conditions, etc. This study aims to tackle two factors that account for the underperformance of current TC intensity forecasts: (1) inadequate observations of TC structures, and (2) deficient understanding of the underlying physical processes governing TC intensification. To tackle the problem of inadequate observations of TC structures, efforts have been made to extract vertical and horizontal structural parameters of latent heat release from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data products. A case study of Hurricane Isabel (2003) was conducted first to explore the feasibility of using the 3D TC structure information in predicting TC intensification. ... Thesis North Atlantic DataCite |
spellingShingle | Data mining Tropical cyclone intensity Apriori algorithm SHIPS Rapid intensification Tang, Jiang Analysis of North Atlantic Tropical Cyclone Intensify Change Using Data Mining ... |
title | Analysis of North Atlantic Tropical Cyclone Intensify Change Using Data Mining ... |
title_full | Analysis of North Atlantic Tropical Cyclone Intensify Change Using Data Mining ... |
title_fullStr | Analysis of North Atlantic Tropical Cyclone Intensify Change Using Data Mining ... |
title_full_unstemmed | Analysis of North Atlantic Tropical Cyclone Intensify Change Using Data Mining ... |
title_short | Analysis of North Atlantic Tropical Cyclone Intensify Change Using Data Mining ... |
title_sort | analysis of north atlantic tropical cyclone intensify change using data mining ... |
topic | Data mining Tropical cyclone intensity Apriori algorithm SHIPS Rapid intensification |
topic_facet | Data mining Tropical cyclone intensity Apriori algorithm SHIPS Rapid intensification |
url | https://dx.doi.org/10.13021/mars/6970 https://mars.gmu.edu/handle/1920/5832 |