Master of Science (MS)
Geography and Anthropology
An automated synoptic weather classification system, based on the weather types devised by Robert Muller for Louisiana, is presented in this thesis and an application of the classification system to precipitation variability in Louisiana is demonstrated. The automated classification presented here is a hybrid classification system that uses sea level pressure composites for each Muller weather type as seeds in a correlation procedure to classify daily NCEP/NCAR Reanalysis sea level pressure patterns. The resulting hybrid classification is automated, objective, and has value in describing the surface weather variability in Louisiana. In the second part of this research project, the newly developed hybrid classification system is used to establish relationships between synoptic weather types and precipitation variability in Louisiana. Weather types that produce precipitation in Louisiana are identified and, using linear regression models, the frequency of rainy weather types is used to predict seasonal rainfall for each of the nine Louisiana climate divisions. Averaged among all climate divisions, synoptic weather type frequency accounts for 25% of the interannual precipitation variability in winter, 14% in spring, 19% in summer, and 25% in fall. While the models are better at predicting the decadal scale variability and trends during fall and winter, these results indicate that synoptic frequency alone is insufficient to describe precipitation variability in Louisiana. Future work will need to identify additional predictors. However, the automated hybrid classification system presented in this study can be used for many additional applications in historical and future climate research for Louisiana.
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Billiot, Amanda Michelle, "A Hybrid Procedure for Classifying Synoptic Weather Types for Louisiana with an Application to Precipitation Variability" (2013). LSU Master's Theses. 965.