The components of the northern hemisphere cryosphere and their relationship to Atlantic tropical cyclone activity are investigated in this study. Multiple ordinary least-squares regression with a stepwise selection procedure is used to develop a new statistical forecasting scheme for 13 seasonal tropical cyclone parameters at four lead times for the period 1980-2010. Sea ice area and sea ice extent in 10 geographic regions, snow cover extent in three geographic regions and five indices reflecting major modes of climate variability were analyzed as possible predictors. Three model groups, based on predictors, were constructed and evaluated: 1) only climate mode predictors, 2) only cryosphere predictors, and 3) both cryosphere and climate mode predictors. Models using only climate mode predictors showed poor predictability of the tropical cyclone parameters across all four lead times while the models using only cryosphere predictors and those using both sets of predictors showed improved predictability. Baffin Bay and Hudson Bay sea ice area were found to be the most significant predictors, exhibiting an inverse relationship with overall tropical cyclone activity. The developed models were also compared to current operational statistical models of tropical cyclone activity. While the operational models were generally more skillful, June hindcasts of major hurricanes outperformed the operational models by as much as 20%.
Identifer | oai:union.ndltd.org:siu.edu/oai:opensiuc.lib.siu.edu:theses-2243 |
Date | 01 August 2013 |
Creators | Mack, Johannes |
Publisher | OpenSIUC |
Source Sets | Southern Illinois University Carbondale |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses |
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