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The linkage between changes in air mass distribution and temperature trends from 1971 to 2010 is explored in the Hudson Bay/Foxe Basin region. Statistically significant temperature increases were found of varying spatial and temporal magnitude. Concurrent statistically significant changes in air mass frequency at the same locations were also detected, particularly in the declining frequency of dry polar (DP) air. These two sets of changes were found to be linked, and we thus conclude that the heterogeneity of the climatic warming signal in the region is at least partially the result of a fundamental shift in the concurrent air mass frequency in addition to global and regional changes in radiative forcing due to increases in long-lived greenhouse gases. [ABSTRACT FROM AUTHOR]

A common method of automated synoptic typing for climatological investigations involves data reduction by principal component analysis followed by the application of a clustering method. The number of eigenvectors kept in the principal component analysis is usually determined by a threshold value of relative variance retained, typically 85% to 95%, under the implicit assumption that varying this relative variance will not affect the resultant synoptic catalogue. This assumption is tested using daily 500-mb geopotential heights over northwest Canada during the winter period (December to February) from 1948 to 2006. Results show that the synoptic catalogue and associated surface climatological characteristics undergo changes for values of relative variance retained over 99%, indicating the typical thresholds are too low and calling into question the validity of performing principal component analysis prior to objective clustering. [ABSTRACT FROM AUTHOR]

Summary It is not clear whether different measures of dispersion of weather attributes could lead to different conclusions on the nature and direction of climatic variability. The range is commonly used as a measure of variability, while the presence of trend is typically studied on seasonal and/or annual basis. In this study, we used daily average temperature values at 15 sites spatially distributed across Canada to test for the presence of trend in variability (measured by the range, the standard deviation and the IQR) using a bootstrap method. The length of the series varied from site to site, ranging from 30 to 151 years. The analysis was undertaken for each month, each season, and the annual data. When calculating the standard deviations, estimates of the annual mean temperatures were used to make the results invariant to the presence of trend in mean. The monthly and seasonal analysis revealed the presence of either increasing or decreasing variability for some months and some seasons. The results for the annual data were not so revealing, especially at sites where some months have increasing while others have decreasing trends. The results across sites did not exhibit a clear geographic pattern. However, there were consistently increasing trends in variability at Toronto and St. John?s during non-summer months, and mostly decreasing trend in Edmonton. The significance of trend in variability using the range and the standard deviation were consistent in less than 30% of the time across sites and across the monthly, seasonal and annual aggregations. There was not much agreement between the standard deviation and the IQR either, highlighting the importance of the choice of a measure of variability. [ABSTRACT FROM AUTHOR]

The well known ENSO (El Nino-Southern Oscillation) phenomenon is quantitatively identified in terms of SST (sea surface temperature) anomalies over the equatorial central and eastern Pacific and sea level pressure difference over eastern and western regions of the equatorialPacific. The PNA (Pacific North American) atmospheric flow pattern, originally identified by Wallace and Gutzler (1981) is representativeof a certain preferred configuration of the mid-tropospheric geopotential height field in the longitudinal sector extending from the mid-Pacific to the southeastern United States. The PNA index is defined as a linear combination of normalized geopotential height anomalies atthe 700 mb level at four selected locations. Using multiple regression analysis, suitable linear combinations of predictors based on monthly values of ENSO and PNA indices are obtained which can foreshadow the summer season's weather over the crop-growing region of the Canadian prairie provinces with a lead time of 2 to 7 months. The utility of the ENSO and PNA indices for advance indication of summer weather with implications for grain yields over the Canadian prairies is further discussed. [ABSTRACT FROM AUTHOR]