We present a dataset of daily resolution climatic time series that has been compiled for the European Climate Assessment (ECA). As of December 2001, this ECA dataset comprises 199 series of minimum, maximum and/or daily mean temperature and 195 series of daily precipitation amount observed at meteorological stations in Europe and the Middle East. Almost all series cover the standard normal period 1961-90, and about 50% extends back to at least 1925. Part of the dataset (90%) is made available for climate research on CDROM and through the Internet (at http://www.knmi.nl/samenw/eca).A comparison of the ECA dataset with existing gridded datasets, having monthly resolution, shows that correlation coefficients between ECA stations and nearest land grid boxes between 1946 and 1999 are higher than 0.8 for 93% of the temperature series and for 51% of the precipitation series. The overall trends in the ECA dataset are of comparable magnitude to those in the gridded datasets.The potential of the ECA dataset for climate studies is demonstrated in two examples. In the first example, it is shown that the winter (October-March) warming in Europe in the 1976-99 period is accompanied by a positive trend in the number of warm-spell days at most stations, but not by a negative trend in the number of cold-spell days. Instead, the number of cold-spell days increases over Europe. In the second example, it is shown for winter precipitation between 1946 and 1999 that positive trends in the mean amount per wet day prevail in areas that are getting drier and wetter.Because of its daily resolution, the ECA dataset enables a variety of empirical climate studies, including detailed analyses of changes in the occurrence of extremes in relation to changes in mean temperature and total precipitation.

Daily European station series of surface air temperature and precipitation from the European Climate Assessment dataset are statistically tested with respect to homogeneity. A two-step approach is followed. First, four homogeneity tests are applied to evaluate the daily series. The testing variables used are (1) the annual mean of the diurnal temperature range, (2) the annual mean of the absolute day-to-day differences of the diurnal temperature range and (3) the wet day count (threshold 1 mm). Second, the results of the different tests are condensed into three classes: 'useful', 'doubtful' and 'suspect'. A qualitative interpretation of this classification is given, as well as recommendations for the use of these labelled series in trend analysis and variability analysis of weather extremes. In the period 1901-99, 94% of the temperature series and 25% of the precipitation series are labelled 'doubtful' or 'suspect'. In the sub-period 1946-99, 61% of the temperature series and 13% of the precipitation series are assigned to these classes. The seemingly favourable scores for precipitation can be attributed to the high standard deviation of the testing variable, and hence the inherent restricted possibilities for detecting inhomogeneities. About 65% of the statistically detected inhomogeneities in the temperature series labelled 'doubtful' or 'suspect' in the period 1946-99 can be attributed to observational changes that are documented in the metadata. For precipitation this percentage is 90%.

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