Investigating the Potentially Untapped Predictability of Tropical Cyclone Genesis in Operational Global Models

• Other Authors: Halperin, Daniel J. (authoraut), Fuelberg, Henry E. (professor co-directing dissertation), Hart, Robert E. (Robert Edward), 1972- (professor co-directing dissertation), Harper, Kristine (university representative), Chagnon, Jeffrey M. (committee member), Liu, Guosheng (committee member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Earth, Ocean, and Atmospheric Science (degree granting department)
• Format: Text
• Language: English
• Published: Florida State University
• Subjects: Meteorology; Atmospheric sciences; Harper; Pacific; North Atlantic
• Online Access: http://purl.flvc.org/fsu/fd/FSU_migr_etd-9607; http://fsu.digital.flvc.org/islandora/object/fsu%3A253078/datastream/TN/view/Investigating%20the%20Potentially%20Untapped%20Predictability%20of%20Tropical%20Cyclone%20Genesis%20in%20Operational%20Global%20Models.jpg

There is an operational need for accurate tropical cyclone (TC) genesis forecasts. Global numerical models are an important genesis guidance tool, but each model has biases. Further, the interpretation of when genesis occurs in a model forecast field can be subjective. Thus, this study seeks to create an automated, objective, statistical-dynamical TC genesis guidance tool for the North Atlantic and eastern North Pacific basins based on output from the CMC, GFS, and UKMET global models. Another goal is to determine how well important genesis processes in global models agree with those theoretically proposed. This research also attempts to identify the characteristics of successful and failed genesis forecasts. First, historical global model forecasts of TC genesis over the past decade are verified. Using this genesis forecast archive, univariable logistic regression equations are created to reveal the statistical relationships between relevant variables and genesis probability. These statistical relationships are compared to theoretical relationships between atmospheric variables and TC genesis. Results show several expected and counterintuitive statistical relationships, with some disagreement among the models. Multiple logistic regression equations then are developed to provide probabilistic genesis forecasts. Separate equations are developed for each global model, basin, and forecast window. Additionally, a consensus regression equation is developed. These equations are tested operationally during the 2014 hurricane season. Verification of the independent data indicates generally well-calibrated guidance. Homogeneous comparisons of the consensus regression equation and National Hurricane Center Tropical Weather Outlook genesis probabilities are presented. Case studies and composite analyses are conducted to gain further insight. Case studies from the following categories are selected: (1) African Easterly Wave genesis over the Main Development Region; (2) genesis from stalled frontal boundaries; (3) genesis via tropical transition; and (4) genesis over the Gulf of Mexico. Hit, miss, and false alarm events are compared. Storm centered composite analyses also are constructed to examine differences in the environments between hit and false alarm forecasts. Separate composites are made for the eastern Main Development Region (where the GFS false alarm rate is greatest) and the remainder of the North Atlantic basin. Statistically significant differences between hit and false alarm cases are found for all variables analyzed with various areal extents. Results from the case studies and composite analyses will help guide new predictors to test for inclusion into the multiple logistic regression equations. Additionally, the case study of Sean (2011) suggests that changes to the TC identification algorithm are needed to better detect subtropical to tropical transition. Real-time guidance products based on the logistic regression equations are being evaluated by hurricane specialists at the National Hurricane Center. It is possible that the products will be selected for operational implementation pending further testing and evaluation during 2015. A Dissertation submitted to the Department of Earth, Ocean, and Atmospheric Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Summer Semester 2015. June 1, 2015. forecasting, genesis, global models, hurricane, tropical cyclone, verification Includes bibliographical references. Henry E. Fuelberg, Professor Co-Directing Dissertation; Robert E. Hart, Professor Co-Directing Dissertation; Kristine C. Harper, University Representative; Jeffrey M. Chagnon, Committee Member; Guosheng Liu, Committee Member.