The Feldbach region in southeast Austria, characteristic for experiencing a rich variety of weather and climate patterns, has been selected as the focus area for a pioneering weather and climate observation network at very high resolution: The WegenerNet comprises 151 meteorological stations measuring temperature, precipitation, and other parameters, in a tightly spaced grid within an area of about 20 km × 15 km centered near the city of Feldbach (46.93°N, 15.90°E). With its stations about every 2 km2, each with 5-min time sampling, the network provides regular measurements since January 2007, after a pilot phase, until 2010, meanwhile in an operational manner. Quality-controlled station time series and gridded field data (spacing 200 m × 200 m) are available in near–real time (data latency less than 1–2 h) for visualization and download via a data portal (www.wegenernet.org; detailed information is available via www.wegcenter.at/wegenernet). This paper introduces the WegenerNet from its design and setup via its processing system and data products to showing example results. The latter include extreme weather event examples, climate variability over the 5-yr period from 2007 to 2011, and an example of calibration support to coupled climate–hydrology modeling. The network is set to serve as a long-term monitoring and validation facility for weather and climate research and applications. Uses include validation of nonhydrostatic models operated at 1-km-scale resolution and of statistical downscaling techniques (in particular for precipitation), validation of weather radar and satellite data, study of orography–climate relationships, and many others.
Operational analyses of 2-m temperature, 2-m humidity, and 10-m wind speed are verified independently against observations obtained from the WegenerNet, an extremely high-density, grid-type surface station network in southeastern Austria with an average distance between stations of 1.4 km. The Integrated Nowcasting through Comprehensive Analysis (INCA) system provides high-resolution analyses in space (1 km) and time (1 h) over the eastern Alpine region and has been specially designed for use in complex terrain. The quality of the system is investigated within a small domain with gentle topography ranging in elevation from 250 to 500 m. A comprehensive validation of INCA relative to WegenerNet for a 3-yr period from December 2007 to November 2010 indicates high analysis skill during all seasons. A sensitivity study reveals the importance of a sufficiently dense station network used by the system and, even more important, the relevance of adequate representativeness of the observation data.
Abstract. The WegenerNet climate station network is a pioneering weather and climate observation experiment at very high resolution in southeastern Austria. The network comprises 151 meteorological stations within a limited area of approximately 20 km × 15 km centered near the town of Feldbach. Measurements include the parameters air temperature, relative humidity, precipitation amount, and others at selected stations (e.g. wind and soil parameters). The temporal sampling is 5 min except 30 min sampling of soil measurements. All data pass a Quality Control System and the provided data products include station data (∼1.4 km × 1.4 km grid) and gridded data (1 km × 1 km and 0.01• × 0.01• grids) on various temporal scales (from 5 min to annual). For application purposes all data are available in near real time (data latency less than 1-2 h in standard operation) via the WegenerNet data portal (www.wegenernet.org).
Abstract. This paper describes the latest reprocessed data record (version 7.1) over 2007 to 2019 from the WegenerNet climate station networks, which since 2007 provide measurements with very high spatial and temporal resolution of hydrometeorological variables for two regions in the state of Styria, southeastern Austria: 1) the WegenerNet Feldbach Region, in the Alpine forelands of southeastern Styria, which extends over an area of about 22 km × 16 km and comprises 155 meteorological stations placed on a tightly spaced grid, with an average spatial density of one station per ∼2 km2 and a temporal sampling of 5 min; and 2) the WegenerNet Johnsbachtal, which is a smaller sister network of the WegenerNet Feldbach Region in the mountainous Alpine region of upper Styria that extends over an area of about 16 km ×17 km and comprises 13 meteorological stations and one hydrographic station, at altitudes ranging from below 600 m to over 2100 m and with a temporal sampling of 10 min. These networks operate on a long-term basis and continuously provide quality-controlled station time series for a multitude of hydrometeorological near-surface and surface variables, including air temperature, relative humidity, precipitation, wind speed and direction, wind gust speed and direction, soil moisture, soil temperature, and others like pressure and radiation variables at a few reference stations. In addition, gridded data are available at a resolution of 200 m × 200 m for air temperature, relative humidity, precipitation and heat index, for the Feldbach Region, and at a resolution of 100 m × 100 m for the wind parameters for both regions. Here we describe this dataset (the most recent reprocessing version 7.1), in terms of the measurement site and station characteristics as well as the data processing from raw data (level 0) via quality-controlled basic station data (level 1) to weather and climate data products (level 2). In order to showcase the practical utility of the data we also include two illustrative example applications and briefly summarize and refer to scientific uses in a range of previous studies. The dataset is published as part of the University of Graz Wegener Center's WegenerNet data repository under the DOI https://doi.org/10.25364/WEGC/WPS7.1:2020.1 (Fuchsberger et al., 2020) and is continuously extended.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.