Date of Graduation
Master of Science in Statistics and Analytics (MS)
Second Committee Member
Climate data, Log precipitation, Spatio-Temporal Analysis, Statistics, Temperature, Tree Ring
Tree ring chronology data is known to reflect regional climate due to the strong impact of rainfall and temperature. Therefore, tree ring data can be used to reconstruct historical climate in order to understand how climate changed in the past and make prediction about the future behavior of the climate. For simplicity, this research only considers the influence of precipitation on tree ring growth within the New England area. A total of 94 measurement sites are used to record tree ring width over 881 years and corresponding precipitation data are given at some locations for 121 years. We developed a spatio-temporal model to describe the response of a tree growth to precipitation on an annual timescale and introduced the general hierarchical statistical framework from data, process and parameter models. To predict climate in the past, we considered an autoregressive process in time that accounts for temporal correlation of precipitation. Based on data collected at each observed location, geospatial Kriging allows us to predict reasonable precipitation at unobserved locations in a regional perspective.
Yin, R. (2019). Spatio-Temporal Analysis of Tree Ring Chronology and Precipitation. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/3351