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Hiebl J.,Zentralanstalt fur Meteorologie und Geodynamik ZAMG | Frei C.,Operation Center 1
Theoretical and Applied Climatology | Year: 2015

Current interest into past climate change and its potential role for changes in the environment call for spatially distributed climate datasets of high temporal resolution and extending over several decades. To foster such research, we present a new gridded dataset of daily minimum and maximum temperature covering Austria at 1-km resolution and extending back till 1961 at daily time resolution. To account for the complex and highly variable thermal distributions in this high-mountain region, we adapt and employ a recently published interpolation method that estimates nonlinear temperature profiles with altitude and accounts for the non-Euclidean spatial representativity of station measurements. The spatial analysis builds upon 150 station series in and around Austria (homogenised where available), all of which extend over or were gap-filled to cover the entire study period. The restriction to (almost) complete records shall avoid long-term inconsistencies from changes in the station network. Systematic leave-one-out cross-validation reveals interpolation errors (mean absolute error) of about 1 °C. Errors are relatively larger for minimum compared to maximum temperatures, for the interior of the Alps compared to the flatland and for winter compared to summer. Visual comparisons suggest that valley-scale inversions and föhn are more realistically captured in the new compared to existing datasets. The usefulness of the presented dataset (SPARTACUS) is illustrated in preliminary analyses of long-term trends in climate impact indices. These reveal spatially variable and eventually considerable changes in the thermal climate in Austria. © 2015 Springer-Verlag Wien Source


Fischer A.,Austrian Academy of Sciences | Stocker-Waldhuber M.,Zentralanstalt fur Meteorologie und Geodynamik ZAMG | Seiser B.,Austrian Academy of Sciences | Hynek B.,Austrian Academy of Sciences | Slupetzky H.,University of Salzburg
Eco.mont | Year: 2014

Glaciers are important and fast changing landscape elements in Hohe Tauern National Park (HTNP). In 1998, 10% of the HTNP area was covered with ice, less than half of the glaciated area during the Little Ice Age maximum. Glaciological monitoring includes mass balance measurements, glacier inventories, length change records and flow velocity measurements, complemented by climatological, hydrological and dendrochronological observations. All these data evidence the climate and glacier history of HTNP in an outstanding way, comparable to few other sites in the world. Source


Zemp M.,University of Zurich | Thibert E.,IRSTEA | Huss M.,University of Fribourg | Stumm D.,International Center for Integrated Mountain Development | And 13 more authors.
Cryosphere | Year: 2013

Glacier-wide mass balance has been measured for more than sixty years and is widely used as an indicator of climate change and to assess the glacier contribution to runoff and sea level rise. Until recently, comprehensive uncertainty assessments have rarely been carried out and mass balance data have often been applied using rough error estimation or without consideration of errors. In this study, we propose a framework for reanalysing glacier mass balance series that includes conceptual and statistical toolsets for assessment of random and systematic errors, as well as for validation and calibration (if necessary) of the glaciological with the geodetic balance results. We demonstrate the usefulness and limitations of the proposed scheme, drawing on an analysis that comprises over 50 recording periods for a dozen glaciers, and we make recommendations to investigators and users of glacier mass balance data. Reanalysing glacier mass balance series needs to become a standard procedure for every monitoring programme to improve data quality, including reliable uncertainty estimates. © 2013 Author(s). Source


Dvornikov Y.,Russian Academy of Sciences | Leibman M.,Russian Academy of Sciences | Heim B.,Alfred Wegener Institute for Polar and Marine Research | Bartsch A.,Zentralanstalt fur Meteorologie und Geodynamik ZAMG | And 11 more authors.
Polarforschung | Year: 2016

The research station Vaskiny Dachi (VD) in central Yamal, Western Siberia was established in 1988. Continuous monitoring of the permafrost state is conducted since 25 years, which allows collecting a large amount of data related to permafrost state and environment of this region. To store and visualise the geospatial data, containing our knowledge of the research area and research topic, we created a geodatabase (GDB) to operatively process different types of geospatial data. The produced GDB contains so far 11 vector feature datasets and raster data in the same coordinate system. The vector data represent: 1) bathymetry; 2) social-economic objects; 3) field data; 4) geomorphology; 5) hydrography; 6) landscapes; 7) permafrost; 8) snow; 9) topography; 10) vegetation; 11) long-term measurement grids and transects (Circumpolar Active Layer Monitoring (CALM) transect, CALM measurement grid). All these feature datasets contain 60 feature classes of spatial data in total. Some of the geodata layers are directly linked to data bases of field data. The raster data contain 37 layers, including a digital ele vation model with derivatives, a map of snow distribution for the key site, ba thymetric maps and other maps of different scale. Moreover, the key area is a site for international research projects and the ongoing exchange of the data is supported by the VD GDB. Geographical Information System (GIS) allows collecting, storing and processing geospatial data from different sources in a wide range of types and formats. WebGIS platforms allow displaying the geospatial data for different users, giving the impression of the general pro cesses on the certain geographic area. Also, we use the WebGIS service to publish the data and to make it available for the larger community. This paper is an overview on the permafrost studies at the VD research station, the GDB for permafrost monitoring as well as the established Yamal WebGIS project. Source


Haslinger K.,Zentralanstalt fur Meteorologie und Geodynamik ZAMG | Anders I.,Zentralanstalt fur Meteorologie und Geodynamik ZAMG | Hofstatter M.,Zentralanstalt fur Meteorologie und Geodynamik ZAMG
Climate Dynamics | Year: 2013

In this study the results of the regional climate model COSMO-CLM (CCLM) covering the Greater Alpine Region (GAR, 4°-19°W and 43°-49°N) were evaluated against observational data. The simulation was carried out as a hindcast run driven by ERA-40 reanalysis data for the period 1961-2000. The spatial resolution of the model data presented is approx. 10 km per grid point. For the evaluation purposes a variety of observational datasets were used: CRU TS 2. 1, E-OBS, GPCC4 and HISTALP. Simple statistics such as mean biases, correlations, trends and annual cycles of temperature and precipitation for different sub-regions were applied to verify the model performance. Furthermore, the altitude dependence of these statistical measures has been taken into account. Compared to the CRU and E-OBS datasets CCLM shows an annual mean cold bias of -0. 6 and -0. 7 °C, respectively. Seasonal precipitation sums are generally overestimated by +8 to +23 % depending on the observational dataset with large variations in space and season. Bias and correlation show a dependency on altitude especially in the winter and summer seasons. Temperature trends in CCLM contradict the signals from observations, showing negative trends in summer and autumn which are in contrast to CRU and E-OBS. © 2012 Springer-Verlag. Source

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