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Long Term Ground Based Precipitation Data Analysis: Spatial And Temporal Variability, Luciano Rodriguez
Long Term Ground Based Precipitation Data Analysis: Spatial And Temporal Variability, Luciano Rodriguez
Computational and Data Sciences (PhD) Dissertations
This dissertation evaluates response variables (classifiers) on various models applied to the detection of El Niño Southern Oscillation (ENSO) on California’s seven climate divisions by using modeled and gauge (in-situ/ground) precipitation measurements and various climate indices. Three scientific studies were conducted as part of this research for evaluation of spatial and temporal ENSO events from modeled and gauge data using: 1) Wavelets 2) Autoregressive-moving-average (ARMA) model / Empirical Mode Decomposition (EMD) 3) Vector Generalized Linear Model (VGLM). This dissertation aims to propose and evaluate a methodology for developing a model to measure ENSO events accurately. The hypothesis is that precipitation …