Statistical data analysis of Alberta agroclimate and global surface air temperature

This thesis discusses three topics related to climate change: agroclimatic change, error variance estimation of climate datasets, and drought monitoring. Agroclimatic change from 1901 to 2002 is assessed for the province of Alberta. The long-term temporal trends in the agroclimate of Alberta are examined and the spatial variations of the agroclimatic resources and the potential crop-growing area in Alberta are explored. The results imply that Alberta agriculture has benefited from the last century's climate change.; The error-assessment is made for the Global Historical Climatology Network data. The error variance of the surface air temperature data is computed for each 5° x 5° grid box and for each month from January 1851 to December 2001. An error variance estimation method is developed based on three parameters: the number of stations, the spatial variance, and a correlation-factor determined by using a regression. The error variance is useful for the calculation of the global or regional average of the surface temperature and its associated uncertainties.; Drought assessment and monitoring discusses the statistical indices, definitions, calculations and their application to agriculture in Alberta. Four kinds of meteorological drought indices commonly used to monitor drought events are analyzed. The drought classification of the four indices is carried out by using a percentile approach, which is based on the probability of occurrence of the drought events. Furthermore, a new drought index, PPCI, is proposed to detect drought occurrence. It can reflect the spatial patterns of the variability of the precipitation field and thus can be used to quantitatively assess the drought risk over a region.