Browsing by Subject "Rainfall frequencies -- Mathematical models"
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Item Surface observations of landfalling hurricane rainbands: case studies of Hurricane Bonnie (1998) and Hurricane Dennis (1999)(Texas Tech University, 2003-05) Skwira, Gary D.This study examines the rainband-scale fluctuations of the meteorological parameters for Hurricane Bonnie (1998) and Dennis (1999). Since reliable surface observations near the locations of landfalling hurricanes are quite rare due to power and/or instrumentation failure. Wind Engineering Mobile Instrumented Tower Experiment (WEMITE) data are exploited to provide a unique look into the structure of the captured storms. The WEMITE data consists of high-resolution meteorological data—including wind speed and direction, temperature, relative humidity, and pressure— gathered from within the planetary boundary layer of landfalling hurricanes along the United States coastline. WEMITE data, along with supplemental data gathered by the National Weather Service, buoys, Coastal Marine Automated Network (CMAN) stations, dropsondes and hurricane hunter observations, are assembled and analyzed through the use of Geographic Information Systems (GIS). Furthermore, nearby Next Generation Weather Surveillance Radar (NEXRAD WSR-88D) data are used to identify and examine rainbands found within the hurricanes of interest. The observed meteorological profiles are compiled and the results are compared to previous rainband studies. The observed meteorological data suggest equivalent potential temperature minima, decreasing hurricane-relative inflow, and large-scale convergence to be commonly associated with intensifying or mature landfalling hurricane rainbands. Additionally, the results suggest larger rainbands (l00's of km long) promote updrafts and reflectivity redevelopment to the inside of their axis. The shorter bands (100 km or less in length), conversely, tend to form from one or a number of cells that are elongated into a band by strong hurricane winds with regeneration upband.Item The effects of changing water availability on the photosynthetic response of plants in the sotol-grasslands of Big Bend National Park, Texas(Texas Tech University, 2003-08) Walker, Erin MThe Hadley Climate Model 11 predicts that Big Bend National Park will receive a 25% increase in both summer and winter rainfall over the next 100 years and that seasonal rainfall patterns will shift from frequent, small storm events to fewer, large storm events. The physiological responses of sotol {Dasylirion leiophyllum) and sideoats grama (Bouteloua curtipendula) to future predicted rainfall patterns were examined over the summer of 2002 through the winter of 2003 in the sotol-grasslands of the Pine Canyon Watershed in Big Bend National Park. Stomatal conductance and photosynthesis were measured for plants that received a 25% increase in seasonal precipitation in either the summer, winter, both the summer and winter, or that received no increase in seasonal rainfall. Stomatal conductance and photosynthesis were also measured for plants that received small, frequent rainfall pulses, rainfall pulses of moderate size and frequency, and large, infrequent rainfall pulses. The 25% increase in seasonal rainfall had no effect on stomatal conductance and photosynthesis for either D. leiophyllum or B. curtipendula, but manipulating rainfall pulses size and frequency did affect the physiological response of the two species. The increase in stomatal conductance and photosynthesis for D. leiophyllum when it received larger, less frequent rainfall pulses, and the favorable response of 5. curtipendula to rainfall pulses of moderate size and frequency suggests that the response of both species is dependent on their rooting habit. Because of its shallow roots, B. curtipendula relied on numerous small pulses to maintain soil water availability in the upper-most soil layers, whereas D. leiophyllum required larger pulses that percolate into its deeper root zone. These results suggest that both species will have a favorable response to the future rainfall patterns predicted by the Hadley Climate Model II.