A wavelet analysis is conducted to investigate daily variability (DV, timescales of less than 3 days), weekly (weather) variability (WV, timescales of 5 days up to 2 months), and seasonal variability (SV, timescales of 8 to 17 months) in five temperature series from Europe and China and two westerly indices for the European/North Atlantic sector back to the 18th century. DV exhibits local features so that it is sensitive to any inhomogeneity in each series. Analysis of DV shows the potential for further homogenization of the data and suggests that for the present study, daily series are only truly homogeneous back to the 19th century. WV is responsible for extremes of large-scale cold/warm variations in the daily series and explains about 80% of the total variance. WV is found to be significantly weaker in northern Europe by 7-10% during warming periods, especially for winter and autumn, but summer temperature correlates positively with WV, with a maximum coefficient of 0.52 for central England. This indicates that for warming periods, WV is reduced in the cold season, but is potentially increased in the warm season. The principal timescale of weather, about 16 days in Europe and 11 days in China, does not exhibit significant trends. Changes in SV from cold to warm periods often result in weaker seasonal cycles, with an unprecedented reduction of up to 3°C at St. Petersburg during the warm period since 1988. The analysis of the westerly indices supports the recent unusually anomalous seasonal cycles, with stronger winter westerlies over the northern Atlantic and Europe. The trends in WV of the westerly indices coincide with the temperature data, implying they are responsible for the large-scale changes over northern Europe.