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A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June-August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90 degrees W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950-2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability...
Abstract (from http://link.springer.com/article/10.1007%2Fs00382-015-2517-1): Daily precipitation variability as observed from weather stations is heavy tailed at most locations around the world. It is thought that diversity in precipitation-causing weather events is fundamental in producing heavy-tailed distributions, and it arises from theory that at least one of the precipitation types contributing to a heavy-tailed climatological record must also be heavy-tailed. Precipitation is a multi-scale phenomenon with a rich spatial structure and short decorrelation length and timescales; the spatiotemporal scale at which precipitation is observed is thus an important factor when considering its statistics and extremes....
Abstract (from http://iopscience.iop.org/article/10.1088/1748-9326/10/12/124023/meta): Temperature variability in the Southwest US is investigated using skew-normal probability distribution functions (SN PDFs) fitted to observed wintertime daily maximum temperature records. These PDFs vary significantly between years, with important geographical differences in the relationship between the central tendency and tails, revealing differing linkages between weather and climate. The warmest and coldest extremes do not necessarily follow the distribution center. In some regions one tail of the distribution shows more variability than does the other. For example, in California the cold tail is more variable while the warm...