[1] We analyze century-long daily temperature and precipitation records for stations in Europe west of 60°E. A set of climatic indices derived from the daily series, mainly focusing on extremes, is defined. Linear trends in these indices are assessed over the period 1901-2000. Average trends, for 75 stations mostly representing Europe west of 20°E, show a warming for all temperature indices. Winter has, on average, warmed more ($1.0°C/100 yr) than summer ($0.8°C), both for daily maximum (TX) and minimum (TN) temperatures. Overall, the warming of TX in winter was stronger in the warm tail than in the cold tail (1.6 and 1.5°C for 98th and 95th, but $1.0°C for 2nd, 5th and 10th percentiles). There are, however, large regional differences in temperature trend patterns. For summer, there is a tendency for stronger warming, both for TX and TN, in the warm than in the cold tail only in parts of central Europe. Winter precipitation totals, averaged over 121 European stations north of 40°N, have increased significantly by $12% per 100 years. Trends in 90th, 95th and 98th percentiles of daily winter precipitation have been similar. No overall long-term trend occurred in summer precipitation totals, but there is an overall weak (statistically insignificant and regionally dependent) tendency for summer precipitation to have become slightly more intense but less common. Data inhomogeneities and relative sparseness of station density in many parts of Europe preclude more robust conclusions. It is of importance that new methods are developed for homogenizing daily data.

ABSTRACT:In order to examine correspondence between different methods for circulation type classification, a dataset of classification catalogs for 12 different European regions has been created using a specially developed software package. Twenty-seven basic automatic classification methods have been applied in several variants to different input datasets describing atmospheric circulation. Together with six manual classifications a total of 33 methods are available for intercomparison.Pattern correlation, frequency time-series correlation and the adjusted Rand index have been used for comparison. Highly significant correspondence has been detected only for two clustering techniques while the remaining classification methods show surprisingly low similarity. A Monte-Carlo test with 1000 classifications of randomly defined types even shows that most of the methods are not more similar among each other than any arbitrarily chosen types.The predominant dissimilarity between the methods is interpreted to be a result of a lack of inherent structures of the input data. Only simulated annealing clustering and self-organizing maps get nearly identical results because they can optimally fit the partitioning to the outer shape of the data cloud in the phase space. Also methods based on pre-defined types come to very different results because small changes in the definition of thresholds may lead to large differences in the partitioning.It is concluded that because of the missing inner structure of the data there is no clear statistical reason to prefer any of the examined methods. For practice in synoptic climatology this means that finding a suited classification for a certain purpose may require a broad comparison of methods. The software package cost733class for development, comparison and evaluation of classifications which was developed and used in this study is available at http://cost733.geo.uni-augsburg.de to facilitate this task.

The development of a daily historical European-North Atlantic mean sea level pressure dataset (EMSLP) for 1850-2003 on a 5°latitude by longitude grid is described. This product was produced using 86 continental and island stations distributed over the region 25°-70°N, 70°W-50°E blended with marine data from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS). The EMSLP fields for 1850-80 are based purely on the land station data and ship observations. From 1881, the blended land and marine fields are combined with already available daily Northern Hemisphere fields. Complete coverage is obtained by employing reduced space optimal interpolation. Squared correlations (r 2 ) indicate that EMSLP generally captures 80%-90% of daily variability represented in an existing historical mean sea level pressure product and over 90% in modern 40-yr European Centre for Medium-Range Weather Forecasts Re-Analyses (ERA-40) over most of the region. A lack of sufficient observations over Greenland and the Middle East, however, has resulted in poorer reconstructions there. Error estimates, produced as part of the reconstruction technique, flag these as regions of low confidence. It is shown that the EMSLP daily fields and associated error estimates provide a unique opportunity to examine the circulation patterns associated with extreme events across the European-North Atlantic region, such as the 2003 heat wave, in the context of historical events.

ScaleX is a collaborative measurement campaign, collocated with a long-term environmental observatory of the German Terrestrial Environmental Observatories (TERENO) network in the mountainous terrain of the Bavarian Prealps, Germany. The aims of both TERENO and ScaleX include the measurement and modeling of land surface–atmosphere interactions of energy, water, and greenhouse gases. ScaleX is motivated by the recognition that long-term intensive observational research over years or decades must be based on well-proven, mostly automated measurement systems, concentrated in a small number of locations. In contrast, short-term intensive campaigns offer the opportunity to assess spatial distributions and gradients by concentrated instrument deployments, and by mobile sensors (ground and/or airborne) to obtain transects and three-dimensional patterns of atmospheric, surface, or soil variables and processes. Moreover, intensive campaigns are ideal proving grounds for innovative instruments, methods, and techniques to measure quantities that cannot (yet) be automated or deployed over long time periods. ScaleX is distinctive in its design, which combines the benefits of a long-term environmental-monitoring approach (TERENO) with the versatility and innovative power of a series of intensive campaigns, to bridge across a wide span of spatial and temporal scales. This contribution presents the concept and first data products of ScaleX-2015, which occurred in June–July 2015. The second installment of ScaleX took place in summer 2016 and periodic further ScaleX campaigns are planned throughout the lifetime of TERENO. This paper calls for collaboration in future ScaleX campaigns or to use our data in modelling studies. It is also an invitation to emulate the ScaleX concept at other long-term observatories.

The ability of circulation type classifications (CTCs) to resolve surface climatic and environmental variables is essential with respect to their application in synoptic climatological applications. This ‘synoptic skill’ depends on several factors including inherent properties of classification methods but as well varying boundary conditions. In this contribution the relevance of the size of the spatial domain for which CTCs are derived is investigated. To this end varying automated CTCs are applied to daily gridded sea level pressure data for 1950–2010 and in each case eight spatial domains of varying size centred around 44 locations spread over the greater north Atlantic European region. For the resulting more than 7000 CTCs the synoptic skill for daily temperature and precipitation taken from the E‐OBS v4.0 data set has been estimated using varying evaluation metrics. Resulting values of evaluation metrics aggregated according to varying domain sizes reveal a distinct influence of the size of the domain on the synoptic skill of CTCs. In general highest skill appears to be achieved for domain sizes with a horizontal dimension of roughly 1300–1800 km (in west–east direction) thus covering most frequent size ranges of synoptic scale systems. However, optimal domain sizes tend to be smaller for precipitation (compared to temperature) in summer (compared to winter) and in more continental regions (compared to more oceanic regions). Distinct deviations from the overall finding of relatively small optimal domains emerge for temperatures above/below certain thresholds for which in certain locations and seasons continental scale domains yield highest synoptic skill. Finally the comparison of varying CTCs concerning the effect of the domain size for synoptic skill shows marked differences between methods and moreover clearly elucidates that differences in synoptic skill that can be attributed to varying domain sizes reach comparable magnitude than those related to differing methods.

In this contribution air temperature differences among Local Climate Zone (LCZ) categories are analysed with special consideration of varying synoptic conditions. Analyses are based upon an LCZ mapping for the urban area of Augsburg (Bavaria, Southern Germany) and hourly air temperature data from a comprehensive logger network. Quality checked air temperature measurements have been stratified according to season, hour of the day and weather situation. For resulting subsamples thermal differences among LCZs have been determined and appropriate statistical tests have been applied. Results confirm that built up LCZs feature higher temperatures than natural LCZs and that most distinct differences among LCZs appear under undisturbed synoptic conditions. With increasing cloudiness and in particular with increasing wind speed differences among LCZs diminish. But, even for strongly disturbed synoptic conditions statistical significance of the influence of LCZs on thermal characteristics could be assured. Thus, our findings provide clear evidence that detectable thermal differences among LCZs are not restricted to "ideal" synoptic conditions but occur as well under disturbed conditions. However, to assure not only the statistical but also the climatological and in particular the bioclimatological and human health related relevance of the documented differences among LCZs further studies incorporating appropriate metrics are intended. Keywords urban climate, local climate zones, urban air temperature, urban meteorological network, urban heat island

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Let H be a Krull monoid with finite class group G such that every class contains a prime divisor and let sans-serifD(G) be the Davenport constant of G. Then a product of two atoms of H can be written as a product of at most sans-serifD(G) atoms. We study this extremal case and consider the set scriptU{2,D(G)}(H) defined as the set of all l∈double-struckN with the following property: there are two atoms u,v∈H such that uv can be written as a product of l atoms as well as a product of sans-serifD(G) atoms. If G is cyclic, then scriptU{2,D(G)}(H)={2,D(G)}. If G has rank two, then we show that (apart from some exceptional cases) scriptU{2,D(G)}(H)=[2,D(G)]∖{3}. This result is based on the recent characterization of all minimal zero-sum sequences of maximal length over groups of rank two. As a consequence, we are able to show that the arithmetical factorization properties encoded in the sets of lengths of a rank 2 prime power order group uniquely characterizes the group.