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ABSTRACT This paper presents an analysis of winter climate variability based on daily mean temperature and precipitation data since 1970 in the Chic-Chocs Mountain range (located in the Gaspé Peninsula, Eastern Quebec, Canada). Mountain environments are particularly sensitive to rapid climate change and are therefore good indicators of recent global warming. The main goal of this study is to demonstrate how joint probability temperature/precipitation distributions can be used to estimate winter condition changes (trends) for six meteorological stations in the study area (the altitudinal range for the stations is from 5 to 574 m). The presence and persistence of snow cover was also estimated. Previous studies have shown a lack of evidence of significant trends in snow-cover characteristics (density, depth and snow water equivalent (SWE)) from the early 1980s to the present, despite an increase in temperature over the same period. A reanalysis of these data sets in addition to the use of a combination of temperature and precipitation data categorized into four modes (warm/wet, warm/dry, cold/wet and cold/dry) was also performed. Despite this new analysis, no clear evidence of climate change could be found in the study area over the last four decades. The results revealed that patterns and trends are quite different from one station to another, but when the environment is taken into account (valley or plateau, coastal versus inland) some apparent patterns emerge. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper investigates winter (DJF) precipitation variability over East Anglia at the daily and 2 d timescales using rain gauge data from 134 sites. The first three principal components (PCs) explain 80.2% (82.0%) of the variance in daily (2 d totals). Precipitation displays higher spatial coherence in winter, with the first three PCs of summer daily totals (Neal and Phillips, 2009, International Journal of Climatology 29: 1661-1679) explaining only 72.3% of the variance. The winter PCs for both 24- and 48-h timescales display precipitation maxima in South Essex (PC 1), NE Norfolk (PC 2), and NW Cambridgeshire (PC 3). The rainfall maximum over South Essex is more important in winter than in summer. Lamb Weather Types and synoptic charts are used to explain the causes of the PCs. A precipitation regionalization is also produced. Discharge for 11 rivers is then modelled as a linear function of the rainfall patterns (as represented by the PC scores). With the exception of the River Babingley, whose discharge is not significantly related to the PCs, these models explain on average 26.5% of the variance. For most rivers, there are significant relationships between discharge and precipitation that fell up to 4 d ago on average. In general, East Anglian river flows show persistence over 6-8 d. [ABSTRACT FROM AUTHOR]