| dc.description.abstract | Texas has a spatial rainfall pattern with a decreasing gradient from east to west that greatly influences land use, vegetation, and river flow. From a hydrometeorological perspective, this variation leads to unfavorable conditions for agricultural production and water management. To minimize the risk due to extreme precipitation, Probable Maximum Precipitation (PMP) is used for designing major hydraulic structures, such as dams and reservoirs, nuclear power plants, and flood protection works. It is also used for rehabilitating old existing dams. However, the estimation of PMP is associated with uncertainties that have received significant attention in recent years, because meteorological extremes are projected to become more frequent, severe, and uncertain owing to climate change. The global-scale climatic cycles and atmospheric circulation reveal the controlling mechanisms of precipitation regimes. The main objective is to investigate into precipitation extremes and characteristics under the effect of climatic cycles and atmospheric phenomenon. The dissertation is organized into five chapters. The first chapter addresses the objectives and organization of the dissertation. The second chapter quantifies the uncertainty associated with PMP estimation and emphasizes the necessity of including the effect of climate change on PMP. The third chapter examines the impact of major Atlantic and Pacific Ocean based climatic cycles, including Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Pacific North American Pattern (PNA), and Southern Oscillation Index (SOI), on extreme precipitation in various climate zones in Texas. The fourth chapter investigates into the effect of climatic cycles and Rossby Wave on extreme precipitation. The relationship between Rossby Wave frequency and precipitation characteristics is investigated. The fifth chapter evaluates future precipitation extremes and PMP using Coupled Model Intercomparison Project Phase 5 (CMIP5) using both historical observations and future CMIP5 projections. It is concluded that extreme precipitation showed non-stationarity which affected the PMP shift during the historical period, and the global scale climatic indicators (AMO, NAO, PDO, PNA, SOI, and ESPI) can provide regional response to meteorological extreme events. These findings can help raise the community’s attention to research needs for broader insights into understanding extreme meteorological events. | en |
