Greater Alpine Region Research Articles

Snow water equivalent in the Alps as seen by gridded data sets, CMIP5 and CORDEX climate models

Abstract. The estimate of the current and future conditions of snow resources in mountain areas would require reliable, kilometre-resolution, regional-observation-based gridded data sets and climate models capable of properly representing snow processes and snow–climate interactions. At the moment, the development of such tools is hampered by the sparseness of station-based reference observations. In past decades passive microwave remote sensing and reanalysis products have mainly been used to infer information on the snow water equivalent distribution. However, the investigation has usually been limited to flat terrains as the reliability of these products in mountain areas is poorly characterized.This work considers the available snow water equivalent data sets from remote sensing and from reanalyses for the greater Alpine region (GAR), and explores their ability to provide a coherent view of the snow water equivalent distribution and climatology in this area. Further we analyse the simulations from the latest-generation regional and global climate models (RCMs, GCMs), participating in the Coordinated Regional Climate Downscaling Experiment over the European domain (EURO-CORDEX) and in the Fifth Coupled Model Intercomparison Project (CMIP5) respectively. We evaluate their reliability in reproducing the main drivers of snow processes – near-surface air temperature and precipitation – against the observational data set EOBS, and compare the snow water equivalent climatology with the remote sensing and reanalysis data sets previously considered. We critically discuss the model limitations in the historical period and we explore their potential in providing reliable future projections.The results of the analysis show that the time-averaged spatial distribution of snow water equivalent and the amplitude of its annual cycle are reproduced quite differently by the different remote sensing and reanalysis data sets, which in fact exhibit a large spread around the ensemble mean. We find that GCMs at spatial resolutions equal to or finer than 1.25° longitude are in closer agreement with the ensemble mean of satellite and reanalysis products in terms of root mean square error and standard deviation than lower-resolution GCMs. The set of regional climate models from the EURO-CORDEX ensemble provides estimates of snow water equivalent at 0.11° resolution that are locally much larger than those indicated by the gridded data sets, and only in a few cases are these differences smoothed out when snow water equivalent is spatially averaged over the entire Alpine domain. ERA-Interim-driven RCM simulations show an annual snow cycle that is comparable in amplitude to those provided by the reference data sets, while GCM-driven RCMs present a large positive bias. RCMs and higher-resolution GCM simulations are used to provide an estimate of the snow reduction expected by the mid-21st century (RCP 8.5 scenario) compared to the historical climatology, with the main purpose of highlighting the limits of our current knowledge and the need for developing more reliable snow simulations.

Influence of low ozone episodes on erythemal UV-B radiation in Austria

This study investigates the influence of low ozone episodes on UV-B radiation in Austria during the period 1999 to 2015. To this aim observations of total column ozone (TCO) in the Greater Alpine Region (Arosa, Switzerland; Hohenpeissenberg, Germany; Hradec Kralove, Czech Republic; Sonnblick, Austria), and erythemal UV-B radiation, available from 12 sites of the Austrian UV-B monitoring network, are analyzed. As previous definitions for low ozone episodes are not particularly suited to investigate effects on UV radiation, a novel threshold approach—considering anomalies—is developed to provide a joint framework for the analysis of extremes. TCO and UV extremes are negatively correlated, although modulating effects of sunshine duration impact the robustness of the statistical relationship. Therefore, information on relative sunshine duration (SDrel), available at (or nearby) UV-B monitoring sites, is included as explanatory variable in the analysis. The joint analysis of anomalies of both UV index (UVI) and total ozone (∆UVI, ∆TCO) and SDrel across sites shows that more than 65% of observations with strongly negative ozone anomalies (∆TCO < −1) led to positive UVI anomalies. Considering only days with strongly positive UVI anomaly (∆UVI > 1), we find (across all sites) that about 90% correspond to negative ∆TCO. The remaining 10% of days occurred during fair weather conditions (SDrel ≥ 80%) explaining the appearance of ∆UVI > 1 despite positive TCO anomalies. Further, we introduce an anomaly amplification factor (AAF), which quantifies the expected change of the ∆UVI for a given change in ∆TCO.

Urban eddy covariance measurements reveal significant missing NOx emissions in Central Europe

Nitrogen oxide (NOx) pollution is emerging as a primary environmental concern across Europe. While some large European metropolitan areas are already in breach of EU safety limits for NO2, this phenomenon does not seem to be only restricted to large industrialized areas anymore. Many smaller scale populated agglomerations including their surrounding rural areas are seeing frequent NO2 concentration violations. The question of a quantitative understanding of different NOx emission sources is therefore of immanent relevance for climate and air chemistry models as well as air pollution management and health. Here we report simultaneous eddy covariance flux measurements of NOx, CO2, CO and non methane volatile organic compound tracers in a city that might be considered representative for Central Europe and the greater Alpine region. Our data show that NOx fluxes are largely at variance with modelled emission projections, suggesting an appreciable underestimation of the traffic related atmospheric NOx input in Europe, comparable to the weekend-weekday effect, which locally changes ozone production rates by 40%.

Evolution of the breeding range of the “italian” Wagtail Motacilla flava cinereocapilla

&lt;p&gt;[The paper shows the evolution of the breeding distribution of the Ashy-headed Wagtail &lt;em&gt;Motacilla&lt;/em&gt; &lt;em&gt;flava&lt;/em&gt; &lt;em&gt;cinereocapilla&lt;/em&gt; in the period 1820-2014. Until 1880, the subspecies nested along the coast north and east of the Adriatic Sea, with some settlements (probably of poor numerical consistency) located in suitable areas of Tuscany, Sicily and Provence; after 1880 it was observed to appear regularly in the Po Valley during migration, and afterwards to occupy the area widely as a breeder. During the nineteenth century the Po Valley underwent major transformation processes with the consequent disruption of ancient agricultural rotations, and an increase of 1°C in the average temperature was also recorded in the area. Out of all the changes that occurred, besides the abundant availability of water, the biotic factor that probably favored the expansion of the subspecies in the Po valley the most is the increase in livestock and the consequent increase in the meadowlands: the first mowing of grass coincides temporally with the hatching of yellow wagtails (often nesting in neighboring fields of wheat), offering them the opportunity to increase the efficiency and effectiveness of foraging on the open ground, with likely benefits for the reproductive success. In the first half of the twentieth century the Ashy-headed Wagtail completed the occupation of the Po Valley, and in the late 1940 a new phase began, during which it settled in new areas in central and southern Italy and Sardinia, extending its distribution area in southern France; but, above all, appearing with increasing frequency and regularity during migrations north of the Alps. These northward shifts later materialized in the settlement of several reproductive groups in France, Switzerland, Germany and Austria, always along basins of rivers or near lakes. Water seems to be the catalyst for the presence of the subspecies. This further expansion phase has probably been favored by climate changes, and in particular by the rise in temperature in the Greater Alpine Region. Favoured by this situation, the subspecies has also colonized mountain areas: in France up to 350 m.a.s.l. in the department of Isère, in Switzerland up to 1700-1800 m.a.s.l. in the Upper Engadine, in Germany up to 880 m.a.s.l. at Ammer and Grunt lakes, in Austria up to 960 m.a.s.l. in Hochfilzen and in Bosnia-Herzegovina up to 720 m.a.s.l. in the plain of Livanjsko. In the Italian Alps it reached the altitude of about 900 m.a.s.l. in Venosta Valley and up to 1000 m.a.s.l. in central Apennines. Since the last decades of the twentieth century nestings have been recorded in Spain. Instead, the breeding of the subspecies in Maghreb is still uncertain.]&lt;/p&gt;&lt;p&gt; &lt;/p&gt;

EURO‐CORDEX regional climate model analysis for the Greater Alpine Region: Performance and expected future change

AbstractSimulations from 13 highly resolved regional climate models run within the Coordinated Downscaling Experiment initiative at 0.11° resolution with boundary forcings from five different Coupled Model Intercomparison Project Phase 5 global models are employed to derive future climate change signal for the Greater Alpine Region (GAR) and four smaller investigation areas. Evaluation statistics include mean temperature and precipitation, frequency of days with precipitation over 1 mm and over 15 mm, 90% quantile of the frequency distribution, and maximum number of consecutive dry days. The evaluation for the period from 1971 to 2000 indicates that the models reproduce spatial seasonal precipitation patterns. In general, the simulations underestimate the seasonal mean temperature and overestimate the mean precipitation values. In GAR the ensemble seasonal mean temperature bias ranges from −0.8 to −1.9°C. The bias in precipitation varies between +14.8% in summer and +41.6% in the winter season. Larger errors are found for other statistics and in the investigated regions. In general, no significant gains in the quality of reproduction of the observed precipitation and temperature statistics compared to previous experiments can be identified. The temperature calculations for 2071–2100 related to the period from 1971 to 2000 in the GAR area show ensemble mean increases in the seasonal mean 2 m temperature of 2.5°C in fall and winter, 2.4°C in summer, and 1.9°C in spring. In the same area, precipitation is simulated to increase up to 12.3% in winter and 5.7% in spring. Only minor changes of the ensemble mean are predicted with +2.3% in fall and −1.7% in summer.

Verification of cloudiness and radiation forecasts in the greater Alpine region

Verification of cloudiness and radiation forecasts in the greater Alpine region

Climate change signals of CMIP5 general circulation models over the Alps – impact of model selection

ABSTRACTEnsembles of regional climate models are widely used to obtain climate change signals and to evaluate associated uncertainties over a specific region. These models are forced by general circulation models (GCMs) at their lateral boundaries. The most recent multi‐model ensembles projects – ENSEMBLES and CORDEX – rely on a limited set of about 10 GCMs per greenhouse gas emission scenario. It was shown previously that in particular, RCM temperature responses tend to cluster according to their driving GCM. Therefore, it is important to better understand the relation among the driving models. In multi‐model ensembles as large as CMIP5, in which models tend to correlate due to their similar origin, model selection or weighting becomes an important issue. This study evaluates the distribution of climate change signals in the CMIP5 ensemble for temperature and precipitation over the Greater Alpine region and shows that different reasonable methods of model selection considerably influence the resulting temperature spread in the climate change signals at the end of the century relative to 1980–2009: excluding those GCMs with a poor representation of Alpine climate leads to a difference in spread of more than 1 °C compared to a selection strategy where all models are included and given the same weight. It is highlighted that the largest amount of spread can be retained with a weighting scheme based on a cluster analysis. Furthermore, we show in bivariate analyses that our understanding of the interplay between temperature and precipitation significantly depends on the model selection strategy. Hence, this work may have important implications for current and future design and analysis of multi‐model projects such as CMIP5 and CORDEX.

Climate variability and Alpine glaciers evolution in Northwestern Italy from the Little Ice Age to the 2010s

In this work, we analyze climate variability and glacier evolution for a study area in the Northwestern Italian Alps from the Little Ice Age (LIA) to the 2010s. In this area, glacier retreat has been almost continuous since the end of the LIA, and many glaciers are now extinct. We compared glaciological and climatic data in order to evaluate the sensitivity of glaciers to temperature and precipitation trends. We found that temperatures show significant warming trends, while precipitation shows no clear signal. After the 1980s, the total number of positive trends in temperature increased, particularly minimum temperature. The latter does not seem to be the only cause of glacier shrinkage but rather on acceleration of an ongoing trend documented since the end of the LIA. In some rare cases, the effects of warming trends on glacier dynamics have been accentuated by a concomitant decrease in precipitation. We hope that this study will contribute to increase the knowledge of the relationships between climate variation and glacier evolution in the Greater Alpine Region.

A new high resolution absolute temperature grid for the Greater Alpine Region back to 1780

ABSTRACTThis study presents a new gridded dataset providing absolute monthly mean temperatures across the Greater Alpine Region (GAR) of Europe at a spatial resolution of 5 arcmin (6 × 9 km in the region) from 1780 to 2008. The starting point was a set of long‐term homogenized station time series. To assure the quality of the analyses back in time, when the station density decreases, missing measurements were reconstructed by an Empirical Orthogonal Function analysis that can deal with gappy data. It is shown that the reconstructed values comprise similar statistical features to the observations and that the method produces no breaks between the reconstructions and the observations. The compound anomaly dataset was then interpolated separately for two different altitude ranges to preserve anomaly gradients between high and low elevations. This allowed for the derivation of individual anomalies at each grid point in GAR. Finally, these smooth anomalies were blended with the highly resolved monthly mean absolute temperature fields, provided by a project of the European Climate Support Network. The added value of this new high resolution and long‐term temperature dataset is shown and discussed using the examples of the height of the 0 °C altitude and vertical lapse rates. For the first time, these and other features are now available for more than two centuries in a topographically complex region like GAR.

Assessing drinking water consumption by inhabitants and tourists in the Alps using a WebGIS for information distribution

In the Alps, regional water balances are stressed by an imbalance between the distribution of naturally available water and the anthropogenic water demand. Due to the growing request for freshwater, water resources will have a tendency to decline in future which may cause impacts on water-related ecosystem services for the society. We use European-level statistics to model the alpine drinking water consumption rates of local residents and tourists using the Nomenclature of Units for Territorial Statistics from Eurostat at two levels (NUTS 2 and NUTS 3). Using the spatial distribution of local residents and tourists as well as the compiled daily water consumption rates, we modelled the amount of water consumed between 1990 and 2008. In the Greater Alpine Region (GAR) water consumption rates from the population on NUTS 3 level increased from 8.3 million m3 per day during the 1990s to 11.2 million m3 per day in 2008. The water consumption rates of both residents and tourists show an increase in central southern areas of the GAR from 1990 to 2000. This trend continues to the south-western part of the GAR between 2000 and 2008. Thus, the drinking water consumption of inhabitants and tourists is highest in places where hydro-climate changes indicate trends of declining naturally available water resources.

Development of a longterm dataset of solid/liquid precipitation

Abstract. Solid precipitation (mainly snow, but snow and ice pellets or hail as well), is an important parameter for climate studies. But as this parameter usually is not available operationally before the second part of the 20th century and nowadays is not reported by automatic stations, information usable for long term climate studies is rare. Therefore a proxy for the fraction of solid precipitation based on a nonlinear relationship between the percentage of solid precipitation and monthly mean temperature was developed for the Greater Alpine Region of Europe and applied to the existing longterm high resolution temperature and precipitation grids (5 arcmin). In this paper the method is introduced and some examples of the resulting datasets available at monthly resolution for 1800–2003 are given.

Characterization of aerosol chemical composition with aerosol mass spectrometry in Central Europe: an overview

Abstract. Real-time measurements of non-refractory submicron aerosols (NR-PM1) were conducted within the greater Alpine region (Switzerland, Germany, Austria, France and Liechtenstein) during several week-long field campaigns in 2002–2009. This region represents one of the most important economic and recreational spaces in Europe. A large variety of sites was covered including urban backgrounds, motorways, rural, remote, and high-alpine stations, and also mobile on-road measurements were performed. Inorganic and organic aerosol (OA) fractions were determined by means of aerosol mass spectrometry (AMS). The data originating from 13 different field campaigns and the combined data have been utilized for providing an improved temporal and spatial data coverage. The average mass concentration of NR-PM1 for the different campaigns typically ranged between 10 and 30 μg m−3. Overall, the organic portion was most abundant, ranging from 36% to 81% of NR-PM1. Other main constituents comprised ammonium (5–15%), nitrate (8–36%), sulfate (3–26%), and chloride (0–5%). These latter anions were, on average, fully neutralized by ammonium. As a major result, time of the year (winter vs. summer) and location of the site (Alpine valleys vs. Plateau) could largely explain the variability in aerosol chemical composition for the different campaigns and were found to be better descriptors for aerosol composition than the type of site (urban, rural etc.). Thus, a reassessment of classifications of measurements sites might be considered in the future, possibly also for other regions of the world. The OA data was further analyzed using positive matrix factorization (PMF) and the multi-linear engine ME (factor analysis) separating the total OA into its underlying components, such as oxygenated (mostly secondary) organic aerosol (OOA), hydrocarbon-like and freshly emitted organic aerosol (HOA), as well as OA from biomass burning (BBOA). OOA was ubiquitous, ranged between 36% and 94% of OA, and could be separated into a low-volatility and a semi-volatile fraction (LV-OOA and SV-OOA) for all summer campaigns at low altitude sites. Wood combustion (BBOA) accounted for a considerable fraction during wintertime (17–49% OA), particularly in narrow Alpine valleys BBOA was often the most abundant OA component. HOA/OA ratios were comparatively low for all campaigns (6–16%) with the exception of on-road, mobile measurements (23%) in the Rhine Valley. The abundance of the aerosol components and the retrievability of SV-OOA and LV-OOA are discussed in the light of atmospheric chemistry and physics.

Millennium-long summer temperature variations in the European Alps as reconstructed from tree rings

Abstract. This paper presents a reconstruction of the summer temperatures over the Greater Alpine Region (44.05°–47.41° N, 6.43°–13° E) during the last millennium based on a network of 38 multi-centennial larch and stone pine chronologies. Tree ring series are standardized using an Adaptative Regional Growth Curve, which attempts to remove the age effect from the low frequency variations in the series. The proxies are calibrated using the June to August mean temperatures from the HISTALP high-elevation temperature time series spanning the 1818–2003. The method combines an analogue technique, which is able to extend the too short tree-ring series, an artificial neural network technique for an optimal non-linear calibration including a bootstrap technique for calculating error assessment on the reconstruction. About 50% of the temperature variance is reconstructed. Low-elevation instrumental data back to 1760 compared to their instrumental target data reveal divergence between (warmer) early instrumental measurements and (colder) proxy estimates. The proxy record indicates cool conditions, from the mid-11th century to the mid-12th century, related to the Oort solar minimum followed by a short Medieval Warm Period (1200–1420). The Little Ice Age (1420–1830) appears particularly cold between 1420 and 1820 with summers that are 0.8 °C cooler than the 1901–2000 period. The new record suggests that the persistency of the late 20th century warming trend is unprecedented. It also reveals significant similarities with other alpine reconstructions.

Error characteristics of high resolution regional climate models over the Alpine area

This study describes typical error ranges of high resolution regional climate models operated over complex orography and investigates the scale-dependence of these error ranges. The results are valid primarily for the European Alpine region, but to some extent they can also be transferred to other orographically complex regions of the world. We investigate the model errors by evaluating a set of 62 one-year hindcast experiments for the year 1999 with four different regional climate models. The analysis is conducted for the parameters mean sea level pressure, air temperature (mean, minimum and maximum) and precipitation (mean, frequency and intensity), both as an area average over the whole modeled domain (the “Greater Alpine Region”, GAR) and in six subregions. The subregional seasonal error ranges, defined as the interval between the 2.5th percentile and the 97.5th percentile, lie between −3.2 and +2.0 K for temperature and between −2.0 and +3.1 mm/day (−45.7 and +94.7%) for precipitation, respectively. While the temperature error ranges are hardly broadened at smaller scales, the precipitation error ranges increase by 28%. These results demonstrate that high resolution RCMs are applicable in relatively small scale climate impact studies with a comparable quality as on well investigated larger scales as far as temperature is concerned. For precipitation, which is a much more demanding parameter, the quality is moderately degraded on smaller scales.

Precipitation and temperature statistics in high‐resolution regional climate models: Evaluation for the European Alps

In this study, high‐resolution climate change data from the regional climate models COSMO‐CLM, HIRHAM, RegCM, and REMO were evaluated in the Greater Alpine Region (GAR; 4°W–19°W and 43°N–49°N) and three additional subareas of 1.5° by 1° in size. Evaluation statistics include mean temperature and precipitation, frequency of days with precipitation over 1 mm and over 15 mm, 90% quantile of the frequency distribution, and maximum number of consecutive dry days. The evaluation for the 1961–1990 period indicates that the models reproduce spatial precipitation patterns and the annual cycle. The mean precipitation domain bias varies between 11% and 40% in winter season and between −14.5% and 11% in summer. Larger errors are found for other statistics and in the various regions. No single best model could be identified comparing modeled precipitation characteristics with observational reference. The study shows that there is still high uncertainty in the expected climate change. Furthermore, future temperature and precipitation changes simulated with different SRES scenarios and calculated by different RCMs overlap. The temperature calculations for the period 2071–2100 related to the period 1961–1990 in the GAR area show an increase in the monthly mean 2m temperature of up to 4.8 K in summer. In the GAR area, a precipitation decrease of up to 29% in summer and precipitation increase of approximately 20% in the winter season is simulated. Summer and autumn temperatures are expected to increase more than winter and spring temperatures. Detailed analysis reveals that the different regional climate model runs based on different regional models, different driving global models and different emission scenarios show similar trends, but differ in the magnitude of the expected climate change signal. All models seem to agree on the increased frequency of high‐precipitation events in the winter season.

A high-resolution 19611990 monthly temperature climatology for the greater Alpine region

The main object of the presented study was the creation of a high-resolution monthly temperature climatology for the greater Alpine region (GAR). This climatology, which is determined from observational averages for the period 1961-1990, necessitated a multinational, high-quality temperature dataset, in which especially inhomogeneities due to different methods of means estimation had to be regarded. Based on multilinear regression techniques and regionalisation, significant model improvements could be reached by adjusting for mesoscale effects in cold air pools, coastal and lakeshore belts, urban areas and slopes. The final 1x1 km grids allowing temperature description of the orographically complex Alpine terrain with an accuracy of 1 °C have been made available for further applications at the web pages of the Central Institute for Meteorology and Geodynamics.

The early instrumental warm-bias: a solution for long central European temperature series 1760–2007

Instrumental temperature recording in the Greater Alpine Region (GAR) began in the year 1760. Prior to the 1850–1870 period, after which screens of different types protected the instruments, thermometers were insufficiently sheltered from direct sunlight so were normally placed on north-facing walls or windows. It is likely that temperatures recorded in the summer half of the year were biased warm and those in the winter half biased cold, with the summer effect dominating. Because the changeover to screens often occurred at similar times, often coincident with the formation of National Meteorological Services (NMSs) in the GAR, it has been difficult to determine the scale of the problem, as all neighbour sites were likely to be similarly affected. This paper uses simultaneous measurements taken for eight recent years at the old and modern site at Kremsmunster, Austria to assess the issue. The temperature differences between the two locations (screened and unscreened) have caused a change in the diurnal cycle, which depends on the time of year. Starting from this specific empirical evidence from the only still existing and active early instrumental measuring site in the region, we developed three correction models for orientations NW through N to NE. Using the orientation angle of the buildings derived from metadata in the station histories of the other early instrumental sites in the region (sites across the GAR in the range from NE to NW) different adjustments to the diurnal cycle are developed for each location. The effect on the 32 sites across the GAR varies due to different formulae being used by NMSs to calculate monthly means from the two or more observations made at each site each day. These formulae also vary with time, so considerable amounts of additional metadata have had to be collected to apply the adjustments across the whole network. Overall, the results indicate that summer (April to September) average temperatures are cooled by about 0.4°C before 1850, with winters (October to March) staying much the same. The effects on monthly temperature averages are largest in June (a cooling from 0.21° to 0.93°C, depending on location) to a slight warming (up to 0.3°C) at some sites in February. In addition to revising the temperature evolution during the past centuries, the results have important implications for the calibration of proxy climatic data in the region (such as tree ring indices and documentary data such as grape harvest dates). A difference series across the 32 sites in the GAR indicates that summers since 1760 have warmed by about 1°C less than winters.

An analysis of global model projections over Italy, with particular attention to the Italian Greater Alpine Region (GAR)

This study surveys the most recent projections of future climate change provided by 20 Atmospheric-Ocean General Circulation Models (AOGCMs) participating in the Coupled Model Intercomparison Project 3 (CMIP3) with focus on the Italian region and in particular on the Italian Greater Alpine Region (GAR). We analyze historical and future simulations of monthly-mean surface air temperature (T) and total precipitation (P). We first compare simulated T and P from the AOGCMs with observations over Italy for the period 1951–2000, using bias indices as a metric for estimating the performance of each model. Using these bias indices and different ensemble averaging methods, we construct ensemble mean projections of future climate change over these regions under three different IPCC emission scenarios (A2, A1B, and B1). We find that the emissions pathway chosen has a greater impact on future simulated climate than the criteria used to obtain the ensemble means. Across all averaging methods and emission scenarios, the models project annual mean increase in T of 2–4°C over the period 1990–2100, with more pronounced increases in summer and warming of similar magnitude at high and low elevations areas (according to a threshold of 400 m). The models project decreases in annual-mean P over this same time period both over the Italian and GAR regions. This decrease is more pronounced over Italy, since a small increase in precipitation over the GAR is projected in the winter season.

Evaluation of the skill and added value of a reanalysis‐driven regional simulation for Alpine temperature

AbstractTo determine whether the use of regional climate models improves the representation of climate is a crucial topic in climate modelling. An improvement over coarser scale models is expected especially in areas with complex orography or along coastlines. However, some studies have shown no clear added value for regional climate models. In this study a high‐resolution regional climate simulation performed with REMO 5.0 (regional model) over the whole of Europe over the period 1958–1998 is analysed for 2‐m temperature over the European Alps and their surroundings called the Greater Alpine region (GAR). The simulation is driven by perfect boundary conditions at the lateral boundaries provided by the ERA40 reanalysis and spectral nudging of the large‐scale wind fields towards ERA40 values for the upper layers inside the model domain. The added value of the regional simulation (1/6° resolution) is analysed with respect to the driving reanalysis (1.125° resolution).Both the REMO simulation and the ERA40 reanalysis are validated against different station datasets of monthly and daily mean 2‐m temperature. Correlation analysis shows that the temporal variability of temperature is well represented by both REMO and ERA40, whereas both show considerable biases. The REMO bias reaches 3 K in summer in regions known to experience a problem with summer drying in a number of regional models. The comparison of REMO and ERA40 shows that an added value of the former exists for all regions in winter. For the regions surrounding the Alps, the added value is absent in summer, whereas in the inner Alpine subregions with most complex orography, REMO performs better than ERA40 during the whole year. The only moderate value added by REMO in this hindcast set‐up may be partly explicable by the fact that meteorological measurements are assimilated in the ERA40 reanalysis but not in the REMO simulation. Copyright © 2009 Royal Meteorological Society

Climate variability and change in the Greater Alpine Region over the last two centuries based on multi‐variable analysis

AbstractAn extensive analysis of the HISTALP database is presented with the aim of giving a comprehensive picture of secular climate variability and change in the Greater Alpine Region (GAR, 4–19 E, 43–49 N). The HISTALP database encompasses 242 sites and concerns temperature, pressure, precipitation, cloudiness, sunshine duration, vapour pressure and relative humidity. The analyses are based on four regional mean records representing different GAR low‐level areas and on an additional mean record representing high‐level locations.The first goal of the paper is to give an overview of the seasonal and annual records for the different variables, aiming to highlight both variability on decadal time scale and long‐term evolution. Then it focuses on trend and correlation analysis. Trends are presented both for the period of common data availability for all regional average series and for moving windows that permit studying the trends over a wide range of timescales. Correlations among the different variables are presented both for the regional average series and for their high‐pass‐filtered versions.The analyses, beside highlighting a warming that is about twice as large as the global trend, also show that the different variables have responded in different ways to this warming and that the mutual interactions linking the different variables are often present only at specific temporal scales and only in parts of the GAR and in defined seasons. In spite of this complex behaviour, which may also be due to some residual inhomogeneities still affecting the data, the analyses give evidence that the HISTALP database has an excellent internal consistency and show that the availability of a multi‐variable database turns out to be very useful in order to evaluate the reliability of the reconstruction of each variable and to better understand the behaviour and the mutual interactions of the different variables. Copyright © 2009 Royal Meteorological Society