Exploring Potential Applications of Quikscat Surface Winds and Gps Radio Occultation Data to Tropical Cyclone Initialization and Prediction

• Other Authors: Kimball, Andrew R. (authoraut)
• Format: Others
• Language: English; English
• Published: Florida State University
• Subjects: Meteorology
• Online Access: http://purl.flvc.org/fsu/fd/FSU_migr_etd-2922

Two emerging datasets, QuikSCAT surface winds and Global Positioning System (GPS) radio occultation (RO) vertical soundings, have the potential to improve tropical cyclone (TC) initialization and, in turn, improve TC prediction. QuikSCAT surface wind with high horizontal resolution and GPS RO temperature and moisture profiles with high vertical resolution can observe TC environments where conventional observations are lacking or non-existent, substantially enhancing the current observation network. These data may be beneficial in the initialization of structures of weak TCs into NWP models, which currently is a major challenge of the present bogus data assimilation (BDA) schemes. This work explores the potential utility of these data in TC observations by selecting a large number of cases for the North Atlantic (NATL) basin for the 1999-2004 hurricane seasons for QuikSCAT and 2001-2003 hurricane seasons for GPS RO. Data coverage, close proximity to the TC center, and observations within +/-3 h of comparison data times were criteria for case selections. QuikSCAT-derived parameters important in BDA (i.e., maximum wind, radius of maximum wind, and the 34-kt radius) were compared with those from the National Hurricane Center (NHC) and the Hurricane Research Division (HRD). GPS RO vertical soundings of bending angle and refractivity were compared with soundings derived from the National Centers for Environmental Prediction (NCEP) dataset and dropsondes. Results from this study show that both datasets have great promise for improving TC initialization and prediction. These comparisons revealed some quality issues in the data that are exasperated in TC environments because of high incidence of rainfall (QuikSCAT) and high ambient water vapor content in the lower troposphere (GPS RO). These data quality concerns need to be addressed before assimilation of these data can be undertaken. Noticeable errors and biases in these observations are found to be weather-dependent. In future work, adjoint sensitivity and four-dimensional variational (4D-Var) minimization studies will be used to assess the impact these datasets will have in hurricane prediction. === A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. === Summer Semester, 2005. === July 8, 2005. === Refractivity, NHC Parameters === Includes bibliographical references. === Xiaolei Zou, Professor Directing Thesis; Robert Hart, Committee Member; Mark Bourassa, Committee Member.