Professor, Statistics and Statistician
- Tel: 951-827-2041
- Email: email@example.com
Spectral Analysis of Spatial/Temporal Weather Variations
One environmental focus of Dr. Lii's research is directed toward developing a general theory on multidimensional (spatial/temporal) spectral analysis methodology for the study of fire weather/climate variations, with the goal of applying this methodology to the analysis of U.S. fire climate fields. This research project includes development of a computerized procedure that implements the multidimensional spectral analysis methodology.
A dearth of satisfactory statistical methods for analyzing spatial and temporal variations in climate data impairs the ability of researchers to describe the long-term characteristics of climate, which is particularly important in global change research. Dr. Lii is pursuing one promising statistical approach, which is a multidimensional extension of spectral analysis (when the data set is gathered by a random sampling scheme rather then gathered on a regular grid), as applied in time series problems.
The goal of this research is to identify spatial and temporal variations in data -- monthly fire weather variables in the contiguous United States -- on continuous spectra. The spectra thus summarize the preferred frequencies, if any, in the data. Monthly mean temperature, relative humidity, windspeed, or a combination thereof are available for 127 weather stations, and monthly temperature and precipitation are available for over 1200 stations. The choice of dataset will be influenced by the computational requirements of the methods.