We will describe the development of a high-resolution, gridded forecast guidance product for warm season cloud-to-ground (CG) lightning in Florida. Four warm seasons of analysis data from the 20-km Rapid Update Cycle (RUC) and lightning data from the National Lightning Detection Network are used to examine relationships between observed atmospheric parameters and the spatial and temporal patterns of CG lightning over Florida. The most important RUC-derived parameters then are used in a perfect prognosis (PP) technique to develop equations producing 3-hourly spatial probability forecasts for one or more CG flashes, as well as the probability of exceeding various flash count percentile thresholds. Binary logistic regression is used to develop the equations for one or more flashes, while a negative binomial (NB) model is used to predict the amount of lightning, conditional on one or more flashes occurring. When applied to the dependent sample of RUC analyses, the equations show forecast skill over a model containing only persistence and climatology (L-CLIPER). We also evaluate the lightning forecast scheme when applied to output from three mesoscale models during an independent test period (the 2006 warm season). The evaluation is performed using output from NCEP's 13-km RUC, the NCEP 12-km NAM-WRF, and local runs of WRF for a domain over South Florida that were initialized with NCEP 1/12th degree sea-surface temperatures (SST) and data from the Local Analysis and Prediction System (LAPS) (WRF-LAPS). During the most active lightning period (1800-2059 UTC), the three models forecast between 80-90% of the lightning events having one or more flashes, and between 30-60% of the events with flash counts meeting or exceeding the 95th percentile. Of the three mesoscale models, WRF-LAPS generally produces the best verification scores during 1800-2059 UTC. Forecasts from all three mesoscale models generally show positive skill with respect to L-CLIPER and persistence through the 2100-2359 UTC period, demonstrating that the PP scheme is model independent. Although the exact timing and placement of forecast lightning is not perfect, there generally is good agreement between the forecasts and their verification, with most of the observed lightning occurring within the higher forecast probability contours. / A Dissertation Submitted to the Department of Meteorology in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. / Spring Semester, 2007. / March 22, 2007. / Weather Research, Rapid Update Cycle, Negative Binomial, Logistic Regression, Perfect Prognosis, Lightning Forecasting, Forecasting Model / Includes bibliographical references. / Henry E. Fuelberg, Professor Directing Dissertation; James B. Elsner, Outside Committee Member; Paul H. Ruscher, Committee Member; Jon E. Ahlquist, Committee Member; Robert Hart, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_176280 |
| Contributors | Shafer, Phillip Edmond, 1979- (authoraut), Fuelberg, Henry E. (professor directing dissertation), Elsner, James B. (outside committee member), Ruscher, Paul H. (committee member), Ahlquist, Jon E. (committee member), Hart, Robert (committee member), Department of Earth, Ocean and Atmospheric Sciences (degree granting department), Florida State University (degree granting institution) |
| Publisher | Florida State University, Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource, computer, application/pdf |
| Rights | This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). The copyright in theses and dissertations completed at Florida State University is held by the students who author them. |
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