Empirical high-resolution wind field and gust model in mountainous and hilly terrain based on the dense WegenerNet station networks

Abstract

Abstract. A weather diagnostic application for automatic generation of gridded wind fields in near-real-time, recently developed by the authors Schlager et al. (2017), is applied to the WegenerNet Johnsbachtal (JBT) meteorological station network. This station network contains 11 meteorological stations at elevations from about 600 to 2200 m in a mountainous region in the north of Styria, Austria. The application generates, based on meteorological observations with a temporal resolution of 10 min from the WegenerNet JBT, mean wind and wind gust fields at 10 and 50 m height levels with a high spatial resolution of 100 m × 100 m and a temporal resolution of 30 min. These wind field products are automatically stored to the WegenerNet data archives, which also include long-term averaged weather and climate datasets from post-processing. The main purpose of these empirically modeled products is the evaluation of convection-permitting dynamical climate models as well as investigating weather and climate variability on a local scale. The application's performance is evaluated against the observations from meteorological stations for representative weather conditions, for a month including mainly thermally induced wind events (July 2014) and a month with frequently occurring strong wind events (December 2013). The overall statistical agreement, estimated for the vector-mean wind speed, shows a reasonably good modeling performance. Due to the spatially more homogeneous wind speeds and directions for strong wind events in this mountainous region, the results show somewhat better performance for these events. The difference between modeled and observed wind directions depends on the station location, where locations along mountain slopes are particularly challenging. Furthermore, the seasonal statistical agreement was investigated from 5-year climate data of the WegenerNet JBT in comparison to 9-year climate data from the high-density WegenerNet meteorological station network Feldbach Region (FBR) analyzed by Schlager et al. (2017). In general, the 5-year statistical evaluation for the JBT indicates similar performance as the shorter-term evaluations of the two representative months. Because of the denser WegenerNet FBR network, the statistical results show better performance for this station network. The application can now serve as a valuable tool for intercomparison with, and evaluation of, wind fields from high-resolution dynamical climate models in both the WegenerNet FBR and JBT regions.

Response to Referee #2

“…(b) Map of the WegenerNet JBT region (black rectangle) including its meteorological stations, with the legend explaining map characteristics and station operators. variability, especially through strong convective activity and severe weather in summer (Kirchengast et al, 2014;Kann et al, 2015a;O et al, 2017, 2018Schroeer and Kirchengast, 2018). The wind fields in this study area are character-ized by thermally induced local flows and influenced by thermally driven regional wind systems with weak wind speeds, caused by a dynamical process called Alpine pumping (Lugauer and Winkler, 2005).…”

WegenerNet high-resolution weather and climate data from 2007 to 2020

“…The WegenerNet JBT has been in development for many years and has not yet been described in its entirety in a single paper, although information can be taken from various papers and reports: Strasser et al (2013) describe 10 of the 14 currently operating stations and a project related to the region, the "cooperation platform Johnsbachtal". Schlager et al (2018) give a general description and information about 11 of the 13 meteorological stations, their location, and measured parameters. An MSc thesis by Grünwald (2014) (written in German) contains a detailed description of the Johnsbachtal region, covering its location, geology, and climate as well as providing detailed information about 10 of the 13 meteorological stations.…”

“…Related scientific output has grown over time, as illustrated by the fact that 11 of 22 scientific journal papers collected as "WegenerNet-related publications" were published in 2018 and 2019. They cover a wide range of topics, including works with a focus on high-resolution rainfall variability and heavy precipitation (Hiebl and Frei, 2018;O et al, 2018;Frei and Isotta, 2019;O and Foelsche, 2019), works with a focus on temperature variability and change (Kabas et al, 2011a;Kann et al, 2011;Krähenmann et al, 2011), works with a focus on wind field data and dynamic modeling (Schlager et al, 2017(Schlager et al, , 2018(Schlager et al, , 2019, works evaluating precipitation data from radar or satellite measurements (Kann et al, 2015;O et al, 2017;Tan et al, 2018;Lasser et al, 2019;Hu et al, 2020), works with a focus on hydrological modeling of high-and low-flow extremes (Hohmann et al, 2018(Hohmann et al, , 2020, and works with a focus on ecosystem research (Denk and Berg, 2014). Some of them are directly linked to aspects of the WegenerNet data processing: Schlager et al (2017Schlager et al ( , 2018Schlager et al ( , 2019 focus on the development and evaluation of high-resolution wind fields for both WegenerNet regions, and O et al (2018) address the validation and correction of rainfall data from the WegenerNet FBR.…”

“…The WPG generates high-resolution 100 m × 100 m wind fields and peak gust fields for the WegenerNet FBR and WegenerNet JBT using the California Meteorological Model (CALMET) as a core tool. It is run hourly after the DPG processing has finished and was derived in recent years by Schlager et al (2017Schlager et al ( , 2018. Input variables of the model are meteorological observations, terrain elevations taken from a 100 m resolution DEM, and land use information.…”

“…Detailed information about the WPG can be found in Schlager et al (2017) and Schlager et al (2018), and a comparison with other models for both regions was made by Schlager et al (2019).…”