Sunday, November 11, 2007
The recent increase in the power of Atlantic tropical cyclones is attributable to greater oceanic warmth in part due to anthropogenic increases in radiative forcing from greenhouse gases. However solar activity can influence a hurricane's power as well through changes in upper tropospheric temperature. Here we report on a finding that annual U.S hurricane counts are significantly related to solar activity. The relationship results from relatively more intense tropical cyclones over the Caribbean when sunspot numbers are low. The finding is in accord with the heat-engine theory of hurricanes that predicts a reduction in the maximum potential intensity with a warming in the layer above the hurricane. An active sun warms the lower stratosphere through ozone absorption of additional ultraviolet (UV) radiation. Since the dissipation of the hurricane's energy occurs through ocean mixing and atmospheric transport, tropical cyclones can act to amplify a relatively small change in the sun's output appreciably altering the climate. Results from this study have serious implications for life and property throughout the Caribbean, Mexico, and portions of the United States. The paper is currently under review for publication.
Saturday, November 03, 2007
Relationships of hurricanes affecting the United States can be examined using the methods of network analysis. Network analysis has been used in a variety of fields to examine relational data, but has yet to be used in the study of hurricane climatology. A single hurricane can affect more than one coastal region. This can happen when the regions are small relative to the hurricane size, when the hurricane comes onshore near regional boundaries, and when the hurricane makes multiple landfalls. Thus we suggest a network that links coastal locations (termed nodes) with particular hurricanes (termed links). The topology of the network can then be examined using local and global metrics. Certain regions of the coast (like Louisiana) may have high occurrence rates, but not high values of connectivity. Regions with the highest values of connectivity should include Florida and North Carolina. Virginia which has a relatively low occurrence rate is well-positioned in the network having a relatively high value of "betweenness". Conditional networks can be constructed based on below and above average values of important climate variables. Significant differences in the connectivity of the network are likely for different phases of ENSO.