Graduation Semester and Year
Fall 2025
Language
English
Document Type
Thesis
Degree Name
Master of Science in Earth and Environmental Science
Department
Earth and Environmental Sciences
First Advisor
Behzad Ghanbarian
Second Advisor
Ricardo Sanchez
Third Advisor
Arne M Wignuth
Fourth Advisor
Yu Zhang
Abstract
Extreme precipitation events (EPEs) are among the most critical weather hazards in Texas, frequently leading to floods, infrastructure damage, and costly economic losses. Therefore, analyzing the spatiotemporal patterns of EPEs is vital, particularly for improving regional climate predictions and hazard preparedness. Although the propagation of EPEs has been previously investigated using complex network theory, the evolution of their climate network has not yet studied. For this purpose, we first collected precipitation data from the NOAA AORC dataset for the 1980-1989, 1990-1999, 2000-2009, 2010-2019, and 2020-2024 periods. The EPEs were identified based on the 95th percentile of wet-day precipitation (≥ 1 mm) for the summer (JJA) and winter (DJF) seasons and each time period. The event synchronization (ES) approach was applied to quantify temporal concurrence between grid-point pairs and to detect links among nodes. The network measures degree centrality, betweenness centrality, clustering coefficient, mean geographic distance, and long-range directedness were computed to characterize spatial organization and teleconnections. To study the evolution of climate networks, complex networks were constructed for each time period, enabled detecting shifts in synchronization strength, teleconnection extent, and hub locations under changing climatic conditions across Texas. The evolution of the climate networks becomes most evident when examined across the individual time periods. As atmospheric conditions and rainfall regimes changed over the past four decades, the structure of the EPE networks also adjusted, revealing how the spatial organization and timing relationships of extremes have shifted over time. These changes reflect the influence of multi-decadal climate variability, shifts in moisture availability, and variations in storm-system behavior, all of which reshape how extreme precipitation events interact across Texas. Climate networks constructed for the 1980–1989 and 1990–1999 periods exhibited similar structural patterns, yet they differed from the networks derived for 2000–2009 and 2010–2019. The network for 2020–2024 was distinct from all others, likely because it represents only a short time window and therefore reflects short-term climate variability rather than longer-term dynamics. In contrast, the climate network constructed for the full 1980–2024 record differed from all individual-period networks, most likely because it integrates multi-decadal variability and long-term climate signals that are not captured within shorter time windows.
Keywords
Climate, Texas, Complex network theory, Network measures, Precipitation, rainfall, Noaa, evolution, weather, extreme events
Disciplines
Environmental Studies
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Kandi Ravi, Anusha, "SPATIOTEMPORAL ANALYSIS OF EXTREME PRECIPITATION EVENTS IN TEXAS" (2025). Earth & Environmental Sciences Theses. 219.
https://mavmatrix.uta.edu/ees_theses/219