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This paper evaluates several daily precipitation products over western and central Europe, identifies and documents their respective strengths and shortcomings, and relates these to uncertainties associated with each of the products. We analyze one gauge-based, three satellite-based, and two reanalysis-based products using high-density rain gauge observations as reference. First, we assess spatial patterns and frequency distributions using aggregated statistics. Then, we determine the skill of precipitation event detection from these products with a focus on extremes, using temporally and spatially matched pairs of precipitation estimates. The results show that the quality of the datasets largely depends on the region, season, and precipitation characteristic addressed. The satellite and the reanalysis precipitation products are found to have difficulties in accurately representing precipitation frequency with local overestimations of more than 40%, which occur mostly in dry regions (all products) as well as along coastlines and over cold/frozen surfaces (satellite-based products). The frequency distributions of wet-day intensities are generally well reproduced by all products. Concerning the frequency distributions of wet-spell durations, the satellite-based products are found to have clear deficiencies for maritime-influenced precipitation regimes. Moreover, the analysis of the detection of extreme precipitation events reveals that none of the non-station-based datasets shows skill at the shortest temporal and spatial scales (1 day, 0.25°), but at and above the 3-day and 1.25° scale the products start to exhibit skill over large parts of the domain. Added value compared to coarser-resolution global benchmark products is found both for reanalysis and satellite-based products. [ABSTRACT FROM AUTHOR]

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971-2000) and future A1B scenario (2021-2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of −2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly. [ABSTRACT FROM AUTHOR]

To advance understanding of hydroclimatological processes, this paper links spatiotemporal variability in gridded European precipitation and large-scale mean sea-level pressure (MSLP) time series (1957–2002) using monthly concurrent correlation. Strong negative (positive) correlation near Iceland and (the Azores) is apparent for precipitation in northwest Europe, confirming a positive North Atlantic Oscillation (NAO) association. An opposing pattern is found for southwest Europe, and the Mediterranean in winter. In the lee of mountains, MSLP correlation is lower reflecting reduced influence of westerlies on precipitation generation. Importantly, European precipitation is shown to be controlled by physically interpretable climate patterns that change in extent and position from month to month. In spring, MSLP–precipitation correlation patterns move and shrink, reaching a minimum in summer, before expanding in the autumn, and forming an NAO-like dipole in winter. These space–time shifts in correlation regions explain why fixed-point NAO indices have limited ability to resolve precipitation for some European locations and seasons. Editor Z.W. Kundzewicz; Associate editor A. Montanari Citation Lavers, D., Prudhomme, C., and Hannah, D.M., 2013. European precipitation connections with large-scale mean sea-level pressure (MSLP) fields. Hydrological Sciences Journal, 58 (2), 310–327. [ABSTRACT FROM AUTHOR]

Satellite-derived high-resolution precipitation products (HRPP) have been developed to address the needs of the user community and are now available with 0.25° × 0.25° (or less) subdaily resolutions. This paper evaluates a number of commonly available satellite-derived HRPPs covering northwest Europe over a 6-yr period. Precipitation products include the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), the Climate Prediction Center (CPC) morphing (CMORPH) technique, the CPC merged microwave technique, the Naval Research Laboratory (NRL) blended technique, and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) technique. In addition, the Geosynchronous Operational Environmental Satellite (GOES) precipitation index (GPI) and the European Centre for Medium-Range Weather Forecasting (ECMWF) operational forecast model products are included for comparison. Surface reference data from the European radar network is used as ground truth, supported by the Global Precipitation Climatology Centre (GPCC) precipitation gauge analysis and gauge data over the United Kingdom. Measures of correlation, bias ratio, probability of detection, and false alarm ratio are used to evaluate the products. Results show that satellite products generally exhibit a seasonal cycle in correlation, bias ratio, probability of detection, and false alarm ratio, with poorer statistics during the winter. The ECMWF model also shows a seasonal cycle in the correlation, although the results are poorer during the summer, while the bias ratio, probability of detection, and false alarm ratio are consistent through all seasons. Importantly, all the satellite HRPPs underestimate precipitation over northwest Europe in all seasons. [ABSTRACT FROM AUTHOR]

Abstract: Understanding climate patterns, with their decisive influence on plant distribution and development, is crucial to understanding the history of vegetation patterns in Europe during the Miocene. This paper presents the detailed analyses of several precipitation parameters, including monthly precipitation of the wettest, driest and warmest months, for five Miocene stages. In conjunction with seasonality of temperature, those parameters provide a meaningful measure of continentality and can help to document Miocene climate changes and patterns and their possible influence on vegetation. Climate reconstructions provided here are entirely based on palaeobotanical material. In total, 169 Miocene floras were selected, including 14 Burdigalian, 41 Langhian, 40 Serravallian, 36 Tortonian, and 38 Messinian localities. All floras were analysed using the Coexistence Approach. The analysis of several precipitation parameters, the statistical inter-correlation of results, and the comparison with modern patterns provides a comprehensive account on Miocene precipitation. Miocene climatic changes after the Mid Miocene Climatic Optimum (MMCO) are evidenced in our data set by three major factors, i.e. (1) increasing seasonality of temperature, (2) changes in the annual distribution of precipitation towards a precipitation peak in summer, and (3) a late increase of longitudinal gradients of precipitation parameters. Evidence of continental climate in Eastern Europe first appears during the Messinian. In addition to changes in temperature, shifts in the annual distribution of precipitation may have played a major role in post-Langhian climate changes. However, the most significant climatic transformations occurred later, from the end of Miocene through to the present. Several authors have described patterns of vegetation development in Europe that are in good agreement with our finding of the first evidence for continental climate in Eastern Europe during the Messinian. Our data do not support an onset of opening of vegetation during the Tortonian or even earlier, as has been described for some parts of Eastern and Southern Europe. Possibly either non climatic parameters influenced such an early development, or our data lack the required resolution and/or spatial coverage to fully decipher the influence of continentality on vegetation and to correlate climate and vegetation statistically. Nevertheless, climatic data that quantify continentality can provide a sound basis for explaining the expansion of grassland in Eurasia. [Copyright &y& Elsevier]

This paper presents an analysis of the precipitation climate signal in Europe emerging from a simulation of heterogeneous regional climate models (RCMs) using five observational datasets as the reference for present day climate conditions. Current climate simulations, as well as those from the A2 family of scenarios from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES-A2), from eight RCMs involved in the Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE) project have been cross-compared with data from the Climate Research Unit (CRU), the Global Precipitation Climatology Project (GPCP), the Global Precipitation Climatology Centre (GPCC), the Climate Prediction Center (CPC), and the CPC Merged Analysis of Precipitation (CMAP) databases for Europe. The RCMs used are HIRHAM, the Climate High Resolution Model (CHRM), the Rossby Centre Atmosphere–Ocean (RCAO) model, the GKSS Climate Version of the Local Model (CLM), the Hadley Center RCM (HadRM3H), the Atmospheric Hydrostatic Regional Model (REMO), the Prognostic Model at the Mesoscale (PROMES), and the regional coupled ocean–atmosphere–ice model (RACMO). The comparison shows that the climate signal has to be interpreted depending on the reference data used. Although each validation dataset has its own relative merits and shortcomings, it is known that all of the datasets present variable uncertainties and error sources, which impedes consideration of a single dataset as the only valid representation of actual precipitation. Hence, it is suggested that a robust joint estimate of changes in future precipitation might include the uncertainties of both the RCMs and those of the observational datasets. After accounting for the difference between observed and simulated precipitation in the present climate, the analysis of such joint estimates reveals significant agreement in the climate signal for most of Europe. This lends confidence to the idea that the RCMs are able to correctly simulate future changes in precipitation. [ABSTRACT FROM AUTHOR]

This paper examines variability in surface climate and the relationship with two circulation indices using recently produced 200-250 year long European daily and monthly climatic series. Assessments are made of the influence of circulation indices (zonal over western Europe and average pressure over central Europe) on regional temperature, precipitation and drought series for northern and central Europe. Changes in the circulation are shown to be very important during the winter in northern Europe, but only over western and central Europe in summer. Circulation indices in winter, however, only explain up to 25% of surface-climate variability and, except for the British Isles, do not explain any decadal and longer timescale variability in summer. Extreme temperatures and growing-season and frost-season durations and degree-day series are calculated for four sites (Central England, Stockholm, Uppsala and St. Petersburg). Degree-day counts are shown to be very strongly correlated (r > 0.9) to average extended summer ('growing' season, May to September) and extended winter ('frost' season, October to April) temperatures. Durations of the growing and frost seasons are only weakly correlated (r ∼ 0.2-0.4) with the appropriate extended seasonal temperatures or degree-day counts. Warmer growing/frost seasons, therefore, need not necessarily be longer/shorter. Counts of extremely warm days in each year are more highly correlated with the growing-season mean temperature than with coldseason temperature. Similarly, counts of extremely cold days in each year are more highly correlated with cold-season temperature than with growing-season temperature. Both the growing-season temperature and the corresponding degree-day counts clearly show warmer temperatures over all series in Fennoscandia before 1860. Over central Europe, and for the Central England temperature series, growing seasons now are of similar warmth to those before 1860. Annually averaged temperatures across the three regions indicate long-term warming which is, however, almost entirely the result of warming during the October to April period. [ABSTRACT FROM AUTHOR]