Greater Alpine Region Research Articles

Elevation dependent change in ERA5 precipitation and its extremes

Mountain regions are recognised as hot-spots of climate change. Although the existence of an Elevation-Dependent Warming has been extensively confirmed in several mountain areas of the globe, fewer studies have analysed the elevational stratification of temporal trends of other climate variables, and particularly for precipitation. This study analyses changes in mean precipitation and its extremes in ERA5 global reanalysis data in key mountain areas of the globe, along with their elevational dependence, from 1951 to 2020. These include the Tibetan Plateau, the US Rocky Mountains, the Greater Alpine Region, and the Andes, as representative of different latitudes and climatic influences. Our analysis reveals common patterns of elevational dependent change in precipitation and its extremes in most of the mountainous areas, which emerge beyond their geographical differences. A positive elevational gradient of trends of extreme precipitation indices is found in the Tibetan Plateau, the Greater Alpine Region, and the subtropical Andes, highlighting a wetting effect (positive trends) at very high elevations. In contrast, the Rocky Mountains exhibit a negative elevational gradient, with a drying effect (negative trends) increasing with the elevation. Notably, a simple linear regression proved to be effective to describe the stratification of change in the Greater Alpine Region and the Rocky Mountains, whereas more complex vertical patterns need to be considered for the Andes and the Tibetan Plateau. Mean precipitation, heavy (≥\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge$$\\end{document}10 mm) precipitation and the length of consecutive wet days show a consistent elevation-dependent stratification within each of the study areas, suggesting possible common driving mechanisms.

AI based 1-D P- and S-wave velocity models for the greater alpine region from local earthquake data

SUMMARY The recent rapid improvement of machine learning techniques had a large impact on the way seismological data can be processed. During the last years several machine learning algorithms determining seismic onset times have been published facilitating the automatic picking of large data sets. Here we apply the deep neural network PhaseNet to a network of over 900 permanent and temporal broad-band stations that were deployed as part of the AlpArray research initiative in the Greater Alpine Region (GAR) during 2016–2020. We selected 384 well distributed earthquakes with ML ≥ 2.5 for our study and developed a purely data-driven pre-inversion pick selection method to consistently remove outliers from the automatic pick catalogue. This allows us to include observations throughout the crustal triplication zone resulting in 39 599 P and 13 188 S observations. Using the established VELEST and the recently developed McMC codes we invert for the 1-D P- and S-wave velocity structure including station correction terms while simultaneously relocating the events. As a result we present two separate models differing in the maximum included observation distance and therefore their suggested usage. The model AlpsLocPS is based on arrivals from ≤130 km and therefore should be used to consistently (re)locate seismicity based on P and S observations. The model GAR1D_PS includes the entire observable distance range of up to 1000 km and for the first time provides consistent P- and S-phase synthetic traveltimes for the entire Alpine orogen. Comparing our relocated seismicity with hypocentral parameters from other studies in the area we quantify the absolute horizontal and vertical accuracy of event locations as ≈2.0 and ≈6.0 km, respectively.

Convection-permitting climate models offer more certain extreme rainfall projections

Extreme precipitation events lead to dramatic impacts on society and the situation will worsen under climate change. Decision-makers need reliable estimates of future changes as a basis for effective adaptation strategies, but projections at local scale from regional climate models (RCMs) are highly uncertain. Here we exploit the km-scale convection-permitting multi-model (CPM) ensemble, generated within the FPS Convection project, to provide new understanding of the changes in local precipitation extremes and related uncertainties over the greater Alpine region. The CPM ensemble shows a stronger increase in the fractional contribution from extreme events than the driving RCM ensemble during the summer, when convection dominates. We find that the CPM ensemble substantially reduces the model uncertainties and their contribution to the total uncertainties by more than 50%. We conclude that the more realistic representation of local dynamical processes in the CPMs provides more reliable local estimates of change, which are essential for policymakers to plan adaptation measures.

Mapping the mantle transition zone discontinuities across South-Central Europe using body waves from seismic noise correlations

We map the mantle transition zone (MTZ) discontinuities beneath South-Central Europe using P-wave reflection phases recovered from noise correlations. We analyze up to four years of seismic noise recordings from 900 broadband stations in the study area. By stacking noise correlations in selected summer months, we significantly improved the retrieval of typically low-amplitude body-wave reflection phases in the light of a quiet surface-wave environment and sufficient noise body-wave illumination from deep paths. We obtain reliable P-wave reflections associated with the 410 km and 660 km discontinuities in the period band of 4–10 s. These short-period reflections reveal clear lateral depth variations of the two discontinuities, indicating complex MTZ structure under the greater Alpine region. This provides new important constraints on present and past mantle dynamics, and it shows the strong potential of passive seismic imaging for studying deep-Earth discontinuities.

Revisiting HISTALP precipitation dataset

AbstractThe article presents a recent update of a comprehensive dataset of long‐term series of precipitation data from instrumental observations in the Greater Alpine Region (GAR), that is, the region of Europe including the Alpine mountain range and their nearer surroundings (4°–19° E in longitude and 43°–49° N in latitude). A comparison to different national homogenized datasets is also presented. Results show that in the national homogenized datasets more breaks have been detected due to higher station density. They also demonstrate the necessity of constant exchange with data providers. The resulting trends in all datasets are mainly weak and only a minority of them is statistically significant. In most cases the similarity of statistical index numbers are promising, with, for example, small RMSE between the presented new HISTALP homogenization and the time series of the national homogenized datasets. Nevertheless, for some stations higher differences occur and break signals are not what would be expected due to possible causes in the station history. The differences between the national and the HISTALP new homogenization—due to, for example, different methods used, different points in time when the homogenization took place, different options of data handling (combination of station data, gap filling routines, …) and different reference stations—illustrate the inherent uncertainty unavoidably associated to homogenization and point out the need of careful communication and use of the data. On the other hand, the results highlight the advantage of consistently homogenized datasets, versus the risks associated with mixing results from different homogenizations.

The AlpArray Research Seismicity-Catalogue

Summary We take advantage of the new large AlpArray Seismic Network (AASN) as part of the AlpArray research initiative (www.alparray.ethz.ch), to establish a consistent seismicity-catalogue for the greater Alpine region (GAR) for the time period 2016 January 1–2019 December 31. We use data from 1103 stations including the AASN backbone composed of 352 permanent and 276 (including 30 OBS) temporary broad-band stations (network code Z3). Although characterized by a moderate seismic hazard, the European Alps and surrounding regions have a higher seismic risk due to the higher concentration of values and people. For these reasons, the GAR seismicity is monitored and routinely reported in catalogues by a 11 national and 2 regional seismic observatories. The heterogeneity of these data set limits the possibility of extracting consistent information by simply merging to investigate the GAR's seismicity as a whole. The uniformly spaced and dense AASN provides, for the first time, a unique opportunity to calculate high-precision hypocentre locations and consistent magnitude estimation with uniformity and equal uncertainty across the GAR. We present a new, multistep, semi-automatic method to process ∼50 TB of seismic signals, combining three different software. We used the SeisComP3 for the initial earthquake detection, a newly developed Python library ADAPT for high-quality re-picking, and the well-established VELEST algorithm both for filtering and final location purposes. Moreover, we computed new local magnitudes based on the final high-precision hypocentre locations and re-evaluation of the amplitude observations. The final catalogue contains 3293 seismic events and is complete down to local magnitude 2.4 and regionally consistent with the magnitude 3+ of national catalogues for the same time period. Despite covering only 4 yr of seismicity, our catalogue evidences the main fault systems and orogens’ front in the region, that are documented as seismically active by the EPOS-EMSC manually revised regional bulletin for the same time period. Additionally, we jointly inverted for a new regional minimum 1-D P-wave velocity model for the GAR and station delays for both permanent station networks and temporary arrays. These results provide the base for a future re-evaluation of the past decades of seismicity, and for the future seismicity, eventually improving seismic-hazard studies in the region. Moreover, we provide a unique, consistent seismic data set fundamental to further investigate this complex and seismically active area. The catalogue, the minimum 1-D P-wave velocity model, and station delays associated are openly shared and distributed with a permanent DOI listed in the data availability section.

Imaging structure and geometry of slabs in the greater Alpine area – a P-wave travel-time tomography using AlpArray Seismic Network data

Abstract. We perform a teleseismic P-wave travel-time tomography to examine the geometry and structure of subducted lithosphere in the upper mantle beneath the Alpine orogen. The tomography is based on waveforms recorded at over 600 temporary and permanent broadband stations of the dense AlpArray Seismic Network deployed by 24 different European institutions in the greater Alpine region, reaching from the Massif Central to the Pannonian Basin and from the Po Plain to the river Main. Teleseismic travel times and travel-time residuals of direct teleseismic P waves from 331 teleseismic events of magnitude 5.5 and higher recorded between 2015 and 2019 by the AlpArray Seismic Network are extracted from the recorded waveforms using a combination of automatic picking, beamforming and cross-correlation. The resulting database contains over 162 000 highly accurate absolute P-wave travel times and travel-time residuals. For tomographic inversion, we define a model domain encompassing the entire Alpine region down to a depth of 600 km. Predictions of travel times are computed in a hybrid way applying a fast TauP method outside the model domain and continuing the wave fronts into the model domain using a fast marching method. We iteratively invert demeaned travel-time residuals for P-wave velocities in the model domain using a regular discretization with an average lateral spacing of about 25 km and a vertical spacing of 15 km. The inversion is regularized towards an initial model constructed from a 3D a priori model of the crust and uppermost mantle and a 1D standard earth model beneath. The resulting model provides a detailed image of slab configuration beneath the Alpine and Apenninic orogens. Major features are a partly overturned Adriatic slab beneath the Apennines reaching down to 400 km depth still attached in its northern part to the crust but exhibiting detachment towards the southeast. A fast anomaly beneath the western Alps indicates a short western Alpine slab whose easternmost end is located at about 100 km depth beneath the Penninic front. Further to the east and following the arcuate shape of the western Periadriatic Fault System, a deep-reaching coherent fast anomaly with complex internal structure generally dipping to the SE down to about 400 km suggests a slab of European origin limited to the east by the Giudicarie fault in the upper 200 km but extending beyond this fault at greater depths. In its eastern part it is detached from overlying lithosphere. Further to the east, well-separated in the upper 200 km from the slab beneath the central Alps but merging with it below, another deep-reaching, nearly vertically dipping high-velocity anomaly suggests the existence of a slab beneath the eastern Alps of presumably the same origin which is completely detached from the orogenic root. Our image of this slab does not require a polarity switch because of its nearly vertical dip and full detachment from the overlying lithosphere. Fast anomalies beneath the Dinarides are weak and concentrated to the northernmost part and shallow depths. Low-velocity regions surrounding the fast anomalies beneath the Alps to the west and northwest follow the same dipping trend as the overlying fast ones, indicating a kinematically coherent thick subducting lithosphere in this region. Alternatively, these regions may signify the presence of seismic anisotropy with a horizontal fast axis parallel to the Alpine belt due to asthenospheric flow around the Alpine slabs. In contrast, low-velocity anomalies to the east suggest asthenospheric upwelling presumably driven by retreat of the Carpathian slab and extrusion of eastern Alpine lithosphere towards the east while low velocities to the south are presumably evidence of asthenospheric upwelling and mantle hydration due to their position above the European slab.

Imaging seismic wave-fields with AlpArray and neighboring European networks

The AlpArray experiment and the deployment of Swath-D together with the dense permanent network in Italy allow for detailed imaging of the spatio-temporal imaging complexity of seismic wave-fields within the greater Alpine region. The distance of any point within the area to the nearest station is less than 30 km, resulting in an average inter-station distance of about 45 km. With a much denser deployment in a smaller region of the Alps (320 km in length and 140 km wide), the Swath-D network possesses an average inter-station distance of about 15 km. We show that seismogram sections with a spatial sampling of less than 5 km can be obtained using recordings of these regional arrays for just a single event. Multiply reflected body waves can be observed for up to 2 h after source time. In addition, we provide and describe animations of long-period seismic wave-fields using recordings of about 1300–1600 broadband stations for six representative earthquakes. These illustrate the considerable spatio-temporal variability of the wave-field’s properties at a high lateral resolution. Within denser station distributions like those provided by Swath-D, even shorter period body and surface wave features can be recovered. The decrease of the horizontal wavelength from P to S to surface waves, deviations from spherically symmetric wavefronts, and the capability to detect multi-orbit arrivals are demonstrated qualitatively by the presented wave-field animations, which are a valuable tool for educational, quality control, and research purposes. We note that the information content of the acquired datasets can only be adequately explored by application of appropriate quantitative methods accounting for the considerable complexity of the seismic wave-fields as revealed by the now available station configuration.

Snow Cover Variability in the Greater Alpine Region in the MODIS Era (2000–2019)

Snow cover is particularly important in the Alps for tourism and the production of hydroelectric energy. In this study, we investigate the spatiotemporal variability in three snow cover metrics, i.e., the length of season (LOS), start of season (SOS) and end of season (EOS), obtained by gap-filling of MOD10A1 and MYD10A1, daily snow cover products of MODIS (Moderate-resolution Imaging Spectroradiometer). We analyze the period 2000–2019, evaluate snow cover patterns in the greater Alpine region (GAR) as a whole and further subdivide it into four subregions based on geographical and climate divides to investigate the drivers of local variability. We found differences both in space and time, with the northeastern region having generally the highest LOS (74 ± 4 days), compared to the southern regions, which exhibit a much shorter snow duration (48/49 ± 2 days). Spatially, the variability in LOS and the other metrics is clearly related to elevation (r2 = 0.85 for the LOS), while other topographic (slope, aspect and shading) and geographic variables (latitude and longitude) play a less important role at the MODIS scale. A high interannual variability was also observed from 2000 to 2019, as the average LOS in the GAR ranged between 41 and 85 days. As a result of high variability, no significant trends in snow cover metrics were seen over the GAR when considering all grid cells. Considering 500-m elevation bands and subregions, as well as individual grid points, we observed significant negative trends above 3000 m a.s.l., with an average of −17 days per decade. While some trends appeared to be caused by glacierized areas, removing grid cells covered by glaciers leads to an even higher frequency of grid cells with significant trends above 3000 m a.s.l., reaching 100% at 4000 m a.s.l. Trends are however to be considered with caution because of the limited length of the observation period.

Teleseismic P waves at the AlpArray seismic network: wave fronts, absolute travel times and travel-time residuals

Abstract. We present an extensive dataset of highly accurate absolute travel times and travel-time residuals of teleseismic P waves recorded by the AlpArray Seismic Network and complementary field experiments in the years from 2015 to 2019. The dataset is intended to serve as the basis for teleseismic travel-time tomography of the upper mantle below the greater Alpine region. In addition, the data may be used as constraints in full-waveform inversion of AlpArray recordings. The dataset comprises about 170 000 onsets derived from records filtered to an upper-corner frequency of 0.5 Hz and 214 000 onsets from records filtered to an upper-corner frequency of 0.1 Hz. The high accuracy of absolute and residual travel times was obtained by applying a specially designed combination of automatic picking, waveform cross-correlation and beamforming. Taking travel-time data for individual events, we are able to visualise in detail the wave fronts of teleseismic P waves as they propagate across AlpArray. Variations of distances between isochrons indicate structural perturbations in the mantle below. Travel-time residuals for individual events exhibit spatially coherent patterns that prove to be stable if events of similar epicentral distance and azimuth are considered. When residuals for all available events are stacked, conspicuous areas of negative residuals emerge that indicate the lateral location of subducting slabs beneath the Apennines and the western, central and eastern Alps. Stacking residuals for events from 90∘ wide azimuthal sectors results in lateral distributions of negative and positive residuals that are generally consistent but differ in detail due to the differing direction of illumination of mantle structures by the incident P waves. Uncertainties of travel-time residuals are estimated from the peak width of the cross-correlation function and its maximum value. The median uncertainty is 0.15 s at 0.5 Hz and 0.18 s at 0.1 Hz, which is more than 10 times lower than the typical travel-time residuals of up to ±2 s. Uncertainties display a regional dependence caused by quality differences between temporary and permanent stations as well as site-specific noise conditions.

Extreme Sub‐Hourly Precipitation Intensities Scale Close to the Clausius‐Clapeyron Rate Over Europe

AbstractOver subhourly time scales, extreme precipitation events play a critical role for many sectors impacted by climate change; however, it is unclear how these events will evolve in a warmer climate. Here, we perform climate simulations using a regional climate model over the greater Alpine region at kilometer‐scale resolution. By analyzing precipitation intensities with short accumulation times, we show that the model can capture the observed percentiles of extreme subhourly precipitation measured at surface rain‐gauge stations. Then, by simulating the future climate, we show that the associated increases in intensity of subhourly extreme precipitation events grow with the intensity of the events but tends asymptotically toward 6.5% per degree warming. This suggests that the most extreme intensities scale with the Clausius‐Clapeyron scaling rate that represents the ability of a warmer atmosphere to hold more water vapor. It should be expected that these changes will lead to increased risks of flash flooding, land‐slides, and erosion over Europe in a warmer climate.

200\xa0years of equilibrium-line altitude variability across the European Alps (1901\u22122100)

Mountain glaciers are key indicators of climate change. Their response is revealed by the environmental equilibrium-line altitude (ELA), i.e. the regional altitude of zero mass balance averaged over a long period of time. We introduce a simple approach for distributed modelling of the environmental ELA over the entire European Alps based on the parameterization of ELA in terms of summer temperature and annual precipitation at a glacier. We use 200 years of climate records and forecasts to model environmental ELA from 1901 to 2100 at 5 arcmin grid cell resolution. Historical environmental ELAs are reconstructed based on precipitation from the Long-term Alpine Precipitation reconstruction (LAPrec) dataset and temperature from the Historical Instrumental climatological Surface Time series of the greater Alpine region (HISTALP). The simulations of future environmental ELAs are forced with high-resolution EURO-CORDEX regional climate model projections for the European domain using three different greenhouse gas emissions scenarios (Representative Concentration Pathways, RCP). Our reconstructions yielded an environmental ELA across the European Alps of 2980 m above sea level for the period 1901−1930, with a rise of 114 m in the period 1971−2000. The environmental ELA is projected to exceed the maximum elevation of 69%, 81% and 92% of the glaciers in the European Alps by 2071−2100 under mitigation (RCP2.6), stabilization (RCP4.5) and high greenhouse gas emission (RCP8.5) scenarios, respectively.

Coda-Q in the 2.5–20 s period band from seismic noise: application to the greater Alpine area

SUMMARY Coda-Q is used to estimate the attenuation and scattering properties of the Earth. So far focus has been on earthquake data at frequencies above 1 Hz, as the high noise level in the first and second microseismic peak, and possibly lower scattering coefficient, hinder stable measurements at lower frequencies. In this work, we measure and map coda-Q in the period bands 2.5–5 s, 5–10 s and 10–20 s in the greater Alpine region using noise cross-correlations between station pairs, based on data from permanent seismic stations and from the temporary AlpArray experiment. The observed coda-Q for short interstation distances is independent of azimuth so there is no indication of influence of the directivity of the incoming noise field on our measurements. In the 2.5–5 s and 5–10 s period bands, our measurements are self-consistent, and we observe stable geographic patterns of low and high coda-Q in the period bands 2.5–5 s and 5–10 s. In the period band 10–20 s, the dispersion of our measurements increases and geographic patterns become speculative. The coda-Q maps show that major features are observed with high resolution, with a very good geographical resolution of for example low coda-Q in the Po Plain. There is a sharp contrast between the Po Plain and the Alps and Apennines where coda-Q is high, with the exception a small area in the Swiss Alps which may be contaminated by the low coda-Q of the Po Plain. The coda of the correlations is too short to make independent measurements at different times within the coda, so we cannot distinguish between intrinsic and scattering Q. Measurements on more severely selected data sets and longer time-series result in identical geographical patterns but lower numerical values. Therefore, high coda-Q values may be overestimated, but the geographic distribution between high and low coda-Q areas is respected. Our results demonstrate that noise correlations are a promising tool for extending coda-Q measurements to frequencies lower than those analysed with earthquake data.

Projections of Alpine Snow-Cover in a High-Resolution Climate Simulation

The recent development of high-resolution climate models offers a promising approach in improving the simulation of precipitation, clouds and temperature. However, higher grid spacing is also a promising feature to improve the simulation of snow cover. In particular, it provides a refined representation of topography and allows for an explicit simulation of convective precipitation processes. In this study we analyze the snow cover in a set of decade-long high-resolution climate simulation with horizontal grid spacing of 2.2 km over the greater Alpine region. Results are compared against observations and lower resolution models (12 and 50 km), which use parameterized convection. The simulations are integrated using the COSMO (Consortium for Small-Scale Modeling) model. The evaluation of snow water equivalent (SWE) in the simulation of present-day climate, driven by the ERA-Interim reanalysis, against an observational dataset, reveals that the high-resolution simulation clearly outperforms simulations with grid spacing of 12 and 50 km. The latter simulations underestimate the cumulative amount of SWE over Switzerland over the whole annual cycle by 33% (12 km simulation) and 56% (50 km simulation) while the high-resolution simulation shows a spatially and temporally averaged difference of less than 1%. Scenario simulations driven by GCM MPI-ESM-LR (2081–2090 RCP8.5 vs. 1991–2000) reveal a strong decrease of SWE over the Alps, consistent with previous studies. Previous studies had found that the relative decrease becomes gradually smaller with elevation, but this finding was limited to low and intermediate altitudes (as a 12 km simulation resolves the topography up to 2500 m). In the current study we find that the height gradient reverses sign, and relative reductions in snow cover increases above 3000 m asl, where important parts of the cryosphere are present. In addition, the simulations project a transition from permanent to seasonal snow cover at high altitudes, with potentially important impacts to Alpine permafrost. This transition and the more pronounced decline of SWE emphasize the value of the higher grid spacing. Overall, we show that high-resolution climate models offer a promising approach in improving the simulation of snow cover in Alpine terrain.

Analyzing Spatial Congruencies and Mismatches between Supply, Demand and Flow of Ecosystem Services and Sustainable Development

Ecosystem services (ESs) are increasingly included into decision-making to achieve Sustainable Development Goals (SDGs). Although both concepts consider the interactions between humans and the environment, spatial relationships between ESs and sustainability have been rarely addressed. Therefore, this study aims at analyzing spatial congruencies and mismatches between ESs and sustainability in the greater Alpine region. Using hot spot and overlap analyses, we overlaid maps of supply, demand and flow of eight key ESs with the spatial distribution of sustainability based on 24 indicators. Our results reveal that, in most cases, supply of and demand for ESs are greatly dislocated. These mismatches are reflected also in the spatial distribution of sustainability. In contrast to ES demand hot spots, supply hot spots are generally characterized by high sustainability levels, especially in relation to the environment. However, due to discrepancies in the social and economic dimensions, it cannot be assumed that ES supply hot spots always correspond to high sustainability. Hence, using ES indicators for measuring sustainability provides rather limited insights. We conclude that both concepts should be applied in a complementary way to maximize ecological, social and economic benefits in land management and planning processes.

Spatial Verification of Ensemble Precipitation: An Ensemble Version of SAL

Abstract Spatial verification methods able to handle high-resolution ensemble forecasts and analysis ensembles are increasingly required because of the increasing development of such ensembles. An ensemble extension of the structure–amplitude–location (SAL) spatial verification method is proposed here. The ensemble SAL (eSAL) allows for verifying ensemble forecasts against a deterministic or ensemble analysis. The eSAL components are equal to those of SAL in the deterministic case, thus allowing the comparison of deterministic and ensemble forecasts. The Mesoscale Verification Intercomparison over Complex Terrain (MesoVICT) project provides a dataset containing deterministic and ensemble precipitation forecasts as well as a deterministic and ensemble analysis for case studies in summer 2007 over the greater Alpine region. These datasets allow for testing of the sensitivity of SAL and eSAL to analysis uncertainty and their suitability for the verification of ensemble forecasts. Their sensitivity with respect to the main parameter of this feature-based method—the threshold for defining precipitation features—is furthermore tested for both the deterministic and ensemble forecasts. Our results stress the importance of using meaningful thresholds in order to limit any unstable behavior of the threshold-dependent SAL components. The eSAL components are typically close to the median of the distribution of deterministic SAL components calculated for all combinations of ensemble members of the forecast and the analysis, with considerably less computational time. The eSAL ensemble extension of SAL can be considered as a relevant summary measure that leads to more easily interpretable SAL diagrams.

Elevation-dependent warming in global climate model simulations at high spatial resolution

The enhancement of warming rates with elevation, so-called elevation-dependent warming (EDW), is one of the regional, still not completely understood, expressions of global warming. Sentinels of climate and environmental changes, mountains have experienced more rapid and intense warming trends in the recent decades, leading to serious impacts on mountain ecosystems and downstream. In this paper we use a state-of-the-art Global Climate Model (EC-Earth) to investigate the impact of model spatial resolution on the representation of this phenomenon and to highlight possible differences in EDW and its causes in different mountain regions of the Northern Hemisphere. To this end we use EC-Earth climate simulations at five different spatial resolutions, from sim 125 to sim 16 km, to explore the existence and the driving mechanisms of EDW in the Colorado Rocky Mountains, the Greater Alpine Region and the Tibetan Plateau–Himalayas. Our results show that the more frequent EDW drivers in all regions and seasons are the changes in albedo and in downward thermal radiation and this is reflected in both daytime and nighttime warming. In the Tibetan Plateau-Himalayas and in the Greater Alpine Region, an additional driver is the change in specific humidity. We also find that, while generally the model shows no clear resolution dependence in its ability to simulate the existence of EDW in the different regions, specific EDW characteristics such as its intensity and the relative role of different driving mechanisms may be different in simulations performed at different spatial resolutions. Moreover, we find that the role of internal climate variability can be significant in modulating the EDW signal, as suggested by the spread found in the multi-member ensemble of the EC-Earth experiments which we use.

Spatial characteristics of precipitation shortfalls in the Greater Alpine Region\u2014a data-based analysis from observations

In this paper, we investigate space time patterns of meteorological drought events in the Greater Alpine Region (GAR) of Europe. A long-term gridded dataset of monthly precipitation sums spanning the last 210 years is used to assess abnormally dry states using a shortfall below a monthly precipitation percentile threshold. These anomalies are calculated for 1, 3, 6, and 12 monthly moving averages. Contiguous areas of grid points below the threshold are indicating drought areas which are analyzed with respect to their drought severity. The severity is quantified by taking the average deviation from the threshold and the size of the drought area into account. The results indicate that the most severe dry anomalies in the GAR occurred in the 1860s, the 1850s, and the 1940s. However, no significant trends of dry anomaly severity are found over the last 210 years. A spatial clustering analysis of the detected drought areas shows distinct spatial patterns, with the Main Alpine Crest as a frequent divide between dryer areas in the north and wetter areas in the south, or vice versa. The patterns are highly significant and similar for all averaging time scales. The clusters are more clearly defined in winter than in summer. Droughts in the north are most frequent in the second half of the nineteenth century, while in the south and east, they are most frequent in the late twentieth century.

High-resolution surface wave tomography of the European crust and uppermost mantle from ambient seismic noise

Taking advantage of the large number of seismic stations installed in Europe, in particular in the greater Alpine region with the AlpArray experiment, we derive a new high-resolution 3-D shear wave velocity model of the European crust and uppermost mantle from ambient-noise tomography. The correlation of up to 4 yr of continuous vertical-component seismic recordings from 1293 broad-band stations (10 • W-35 • E, 30 • N-75 • N) provides Rayleigh wave group velocity dispersion data in the period band 5-150 s at more than 0.8 million virtual source-receiver pairs. 2-D Rayleigh wave group velocity maps are estimated using adaptive parametrization to accommodate the strong heterogeneity of path coverage. A probabilistic 3-D shear wave velocity model, including probability densities for the depth of layer boundaries and S-wave velocity values, is obtained by nonlinear Bayesian inversion. A weighted average of the probabilistic model is then used as starting model for the linear inversion step, providing the final V s model. The resulting S-wave velocity model and Moho depth are validated by comparison with previous geophysical studies. Although surface wave tomography is weakly sensitive to layer boundaries, vertical cross-sections through our V s model and the associated probability of the presence of interfaces display striking similarities with reference controlled-source seismology (CSS) and receiver function sections across the Alpine belt. Our model even provides new structural information such as an ∼8 km Moho jump along the CSS ECORS-CROP profile that was not imaged by the reflection data due to poor penetration across a heterogeneous upper crust. Our probabilistic and final shear wave velocity models have the potential to become new reference models of the European crust, both for crustal structure probing and geophysical studies including waveform modelling or full-waveform inversion.

Verification of Gridded Wind Forecasts in Complex Alpine Terrain: A New Wind Verification Methodology Based on the Neighborhood Approach

AbstractA novel wind verification methodology is presented and analyzed for six surface wind cases in the greater Alpine region as well as an idealized setup. The methodology is based on the idea of the fractions skill score, a neighborhood-based spatial verification metric frequently used for verifying precipitation. The new score avoids the problems of traditional nonspatial verification metrics (the “double penalty” problem and the failure to distinguish between a “near miss” and much poorer forecasts) and can distinguish forecasts even when the spatial displacement of wind patterns is large. Moreover, the time-averaged score value in combination with a statistical significance test enables different wind forecasts to be ranked by their performance.