Ozone is one of the six “criteria” pollutants identified by the U.S. Clean Air Act Amendment of 1970 as particularly harmful to human health. Concentrations have decreased markedly across the United States over the past 50 years in response to regulatory efforts, but continuing research on its deleterious effects have spurred further reductions in the legal threshold. The South Coast and San Joaquin Valley Air Basins of California remain the only two “extreme” ozone nonattainment areas in the United States. Further reductions of ozone in the West are complicated by significant background concentrations whose relative importance increases as domestic anthropogenic contributions decline and the national standards continue to be lowered. These background concentrations derive largely from uncontrollable sources including stratospheric intrusions, wildfires, and intercontinental transport. Taken together the exogenous sources complicate regulatory strategies and necessitate a much more precise understanding of the timing and magnitude of their contributions to regional air pollution. The California Baseline Ozone Transport Study was a field campaign coordinated across Northern and Central California during spring and summer 2016 aimed at observing daily variations in the ozone columns crossing the North American coastline, as well as the modification of the ozone layering downwind across the mountainous topography of California to better understand the impacts of background ozone on surface air quality in complex terrain.

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In this study, data assimilation methods of 3-D variational analysis (3DVAR), observation nudging, and analysis (grid) nudging were evaluated in the Weather Research and Forecasting (WRF) model for a high-impact, multi-episode landfalling atmospheric river (AR) event for Northern California from 28 November to 3 December, 2012. Eight experiments were designed to explore various combinations of the data assimilation methods and different initial conditions. The short-to-medium range quantitative precipitation forecast (QPF) performances were tested for each experiment. Surface observations from the National Oceanic and Atmospheric Administration's (NOAA) Hydrometeorology Network (HMT), National Weather Service (NWS) radiosondes, and GPS Radio Occultation (RO) vertical profiles from the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) satellites were used for assimilation. Model results 2.5 days into the forecast showed slower timing of the 2 nd AR episode by a few hours and an underestimation in AR strength. For the entire event forecasts, the nongrid-nudging experiments showed the lowest mean absolute error (MAE) for rainfall accumulations, especially those with 3DVAR. Higher-resolution initial conditions showed more realistic coastal QPFs. Also, a 3-h nudging time interval and time window for observation nudging and 3DVAR, respectively, may be too large for this type of event, and it did not show skill until 60-66 h into the forecast. v ACKNOWLEDGEMENTS I want to acknowledge my advisor, Dr. Sen Chiao, for all of his endless support and advice. None of this would have been possible without him. He had an open-door policy, and he always made time to assist me even if he was busy teaching classes, helping his other graduate and undergraduate students, and doing his own research. I am forever grateful for all of his encouragement and push to give an oral presentation at the

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