Recent trends in weather and seasonal cycles: An analysis of daily data from Europe and China

A wavelet analysis is conducted to investigate daily variability (DV, times cales 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 1 7 months) in five temperature series from Europe and China and two westerly indices for the European/North Atlantic sector back to-the 18th century. D V exhibits local features so that it is sensitive to any inhomogeneity in e ach series. Analysis of DV shows the potential for further homogenization o f the data and suggests that for the present study, daily series are only t ruly homogeneous back to the 19th century. WV is responsible for extremes o f large-scale cold/warm variations in the daily series and explains about 8 0% of the total variance. WV is found to be significantly weaker in norther n Europe by 7-10% during warming periods, especially for winter and autumn, but summer temperature correlates positively with WV, with a maximum coeff icient 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 war m season. The principal timescale of weather, about 16 days in Europe and 1 1 days in China, does not exhibit significant trends. Changes in SV from co ld to warm periods often result in weaker seasonal cycles, with an unpreced ented reduction of up to 3 degreesC at St. Petersburg during the warm perio d since 1988. The analysis of the westerly indices supports the recent unus ually anomalous seasonal cycles, with stronger winter westerlies over the n orthern Atlantic and Europe. The trends in WV of the westerly indices coinc ide with the temperature data, implying they are responsible for the large- scale changes over northern Europe.