A spatial evaluation of high-resolution wind fields from empirical and dynamical modeling in hilly and mountainous terrain

Abstract. Empirical high-resolution surface wind fields, automatically generated by a weather diagnostic application, the WegenerNet Wind Product Generator (WPG), were intercompared with wind field analysis data from the Integrated Nowcasting through Comprehensive Analysis (INCA) system and with dynamical climate model wind field data from the non-hydrostatic climate model COSMO-CLM. The INCA analysis fields are available at a horizontal grid spacing of 1 km x 1 km, whereas the COSMO model fields are from simulations at a 3 km x 3 km grid. The WPG, developed by Schlager et al. (2017, 2018), generates diagnostic fields at a high resolution grid of 100 m x 100 m, using observations from two dense meteorological station networks: The WegenerNet Feldbach Region (FBR) and its alpine sister network, the WegenerNet Johnsbachtal (JBT). The high-density WegenerNet FBR is located in southeastern Styria, Austria, a region predominated by a hilly terrain and small differences in altitude. The network consists of more than 150 meteorological stations. The WegenerNet JBT contains eleven meteorological stations at elevations ranging from about 600 m to 2200 m in a mountainous region in northern Styria. The wind fields of these different empirical/dynamical modeling approaches were intercompared for thermally induced and strong wind events, using hourly temporal resolutions as supplied by the WPG, with the focus on evaluating spatial differences and displacements between the different datasets. For this comparison, a novel neighborhood-based spatial wind verification methodology based on fractions skill socres (FSS) is used to estimate the modeling performances. All comparisons show an increasing FSS with increasing neighborhood size. In general, the spatial verification indicates a better statistical agreement for the hilly WegenerNet FBR than for the mountainous WegenerNet JBT. The results for the WegenerNet FBR show a better agreement between INCA and WegenerNet than between COSMO and WegenerNet wind fields, especially for large scales (neighborhoods). In particular, COSMO-CLM clearly underperforms in case of thermally induced wind events. For the JBT region, all spatial comparisons indicate little overlap at small neighborhood sizes and in general large biases of wind vectors occur between the dynamical (COSMO) and analysis (INCA) fields and the diagnostic (WegenerNet) reference dataset. Furthermore, gridpoint-based error measures were calculated for the same evaluation cases. The statistical agreement, estimated for the vector-mean wind speed and wind directions show again a better agreement for the WegenerNet FBR than for the WegenerNet JBT region. In general, the difference between modeled and observed wind directions is smaller for strong wind speed events than for thermally induced ones. A combined examination of all spatial and gridpoint-based error measures shows that COSMO-CLM with its limited horizontal resolution of 3 km x 3 km and hence, a too smoothed orography, is not able to represent small-scale wind patterns. The results for the JBT region indicate that the INCA analysis fields generally overestimate wind speeds in the summit regions. For strong wind speed events the wind speed in the valleys is underestimated by INCA, however. Regarding the WegenerNet diagnostic wind fields, the statistics show decent performance in the FBR and somewhat overestimated wind speeds for strong wind speed events in the Enns valley of the JBT region.

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A spatial evaluation of high-resolution wind fields from empirical and dynamical modeling in hilly and mountainous terrain

Geoscientific Model Development ◽

10.5194/gmd-12-2855-2019 ◽

2019 ◽

Vol 12 (7) ◽

pp. 2855-2873

Author(s):

Christoph Schlager ◽

Gottfried Kirchengast ◽

Juergen Fuchsberger ◽

Alexander Kann ◽

Heimo Truhetz

Keyword(s):

High Resolution ◽

Wind Speed ◽

Climate Model ◽

Grid Point ◽

Regional Climate ◽

Small Scale ◽

Strong Wind ◽

Wind Fields ◽

Thermally Induced ◽

Wind Events

Abstract. Empirical high-resolution surface wind fields, automatically generated by a weather diagnostic application, the WegenerNet Wind Product Generator (WPG), were intercompared with wind field analysis data from the Integrated Nowcasting through Comprehensive Analysis (INCA) system and with regional climate model wind field data from the Consortium for Small Scale Modeling Model in Climate Mode (CCLM). The INCA analysis fields are available at a horizontal grid spacing of 1 km × 1 km, whereas the CCLM fields are from simulations at a 3 km × 3 km grid. The WPG, developed by Schlager et al. (2017, 2018), generates diagnostic fields on a high-resolution grid of 100 m × 100 m, using observations from two dense meteorological station networks: the WegenerNet Feldbach Region (FBR), located in a region predominated by a hilly terrain, and its Alpine sister network, the WegenerNet Johnsbachtal (JBT), located in a mountainous region. The wind fields of these different empirical–dynamical modeling approaches were intercompared for thermally induced and strong wind events, using hourly temporal resolutions as supplied by the WPG, with the focus on evaluating spatial differences and displacements between the different datasets. For this comparison, a novel neighborhood-based spatial wind verification methodology based on fractions skill scores (FSSs) is used to estimate the modeling performances. All comparisons show an increasing FSS with increasing neighborhood size. In general, the spatial verification indicates a better statistical agreement for the hilly WegenerNet FBR than for the mountainous WegenerNet JBT. The results for the WegenerNet FBR show a better agreement between INCA and WegenerNet than between CCLM and WegenerNet wind fields, especially for large scales (neighborhoods). In particular, CCLM clearly underperforms in the case of thermally induced wind events. For the JBT region, all spatial comparisons indicate little overlap at small neighborhood sizes, and in general large biases of wind vectors occur between the regional climate model (CCLM) and analysis (INCA) fields and the diagnostic (WegenerNet) reference dataset. Furthermore, grid-point-based error measures were calculated for the same evaluation cases. The statistical agreement, estimated for the vector-mean wind speed and wind directions again show better agreement for the WegenerNet FBR than for the WegenerNet JBT region. A combined examination of all spatial and grid-point-based error measures shows that CCLM with its limited horizontal resolution of 3 km × 3 km, and hence too smoothed an orography, is not able to represent small-scale wind patterns. The results for the JBT region indicate significant biases in the INCA analysis fields, especially for strong wind speed events. Regarding the WegenerNet diagnostic wind fields, the statistics show acceptable performance in the FBR and somewhat overestimated wind speeds for strong wind speed events in the Enns valley of the JBT region.

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A climatology of wintertime low-level jets in Nares Strait

Polar Research ◽

10.33265/polar.v40.3622 ◽

2021 ◽

Vol 40 ◽

Author(s):

Svenja H.E. Kohnemann ◽

Günther Heinemann

Keyword(s):

Wind Speed ◽

Climate Model ◽

Horizontal Resolution ◽

Strong Impact ◽

Strong Wind ◽

Low Level ◽

Wind Speeds ◽

Nares Strait ◽

The North ◽

Wind Events

Intense, southward low-level winds are common in Nares Strait, between Ellesmere Island and northern Greenland. The steep topography along Nares Strait leads to channelling effects, resulting in an along-strait flow. This research study presents a 30-year climatology of the flow regime from simulations of the COSMO-CLM climate model. The simulations are available for the winter periods (November–April) 1987/88 to 2016/17, and thus, cover a period long enough to give robust long-term characteristics of Nares Strait. The horizontal resolution of 15 km is high enough to represent the complex terrain and the meteorological conditions realistically. The 30-year climatology shows that LLJs associated with gap flows are a climatological feature of Nares Strait. The maximum of the mean 10-m wind speed is around 12 m s-1 and is located at the southern exit of Smith Sound. The wind speed is strongly related to the pressure gradient. Single events reach wind speeds of 40 m s-1 in the daily mean. The LLJs are associated with gap flows within the narrowest parts of the strait under stably stratified conditions, with the main LLJ occurring at 100–250 m height. With increasing mountain Froude number, the LLJ wind speed and height increase. The frequency of strong wind events (>20 m s-1 in the daily mean) for the 10 m wind shows a strong interannual variability with an average of 15 events per winter. Channelled winds have a strong impact on the formation of the North Water polynya.

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Atmospheric forcing of sea ice anomalies in the Ross Sea Polynya region

10.5194/tc-2016-89 ◽

2016 ◽

Cited By ~ 1

Author(s):

Ethan R. Dale ◽

Adrian J. McDonald ◽

Jack H.J. Coggins ◽

Wolfgang Rack

Keyword(s):

Wind Speed ◽

Sea Ice ◽

Ross Sea ◽

Strong Wind ◽

Sea Ice Concentration ◽

Sea Ice Extent ◽

Wind Speeds ◽

Wind Event ◽

Wind Events ◽

Ice Production

Abstract. Despite warming trends in global temperatures, sea ice extent in the Southern Hemisphere has shown an increasing trend over recent decades. Wind-driven sea ice export from coastal polynyas is an important source of sea ice production. Areas of major polynyas in the Ross Sea, the region with largest increase in sea ice extent, have been suggested to produce a vast amount of the sea ice in the region. We investigate the impacts of strong wind events on the Ross Sea Polynyas and its sea ice concentration and possible consequences on sea ice production. We utilise Bootstrap sea ice concentration (SIC) measurements derived from satellite based, Special Sensor Microwave Imager (SSM/I) brightness temperatures. We compared these with surface winds and temperatures from automatic weather stations (AWS) of the University of Wisconsin-Madison Antarctic Meteorology Program. Our analysis focusses on the austral winter period defined as 1st April to 1st November in this study. Daily data were used to classified into characteristic regimes based on the percentiles of wind speed. For each regime, a composite of SIC anomaly was formed for the Ross Sea region. We found that persistent weak winds near the edge of the Ross Ice Shelf are generally associated with positive SIC anomalies in the Ross Sea Polynya (RSP). Conversely we found negative SIC anomalies in this area during persistent strong winds. By analysing sea ice motion vectors derived from SSM/I and SSMIS brightness temperatures, we find significant sea ice motion anomalies throughout the Ross Sea during strong wind events. These anomalies persist for several days after the strong wind event. Strong, negative correlations are found between SIC and AWS wind speed within the RSP indicating that strong winds cause significant advection of sea ice in the region. We were able to recreate these correlations using co-located ERA-Interim wind speeds. However when only days of a certain percentile based wind speed classification were used, the cross correlation functions produced by ERA-Interim wind speeds differed significantly from those produced using AWS wind speeds. The rapid decrease in SIC during a strong wind event is followed by a more gradual recovery in SIC. This increase occurs on a more gradual time scale than the average persistence of a strong wind event and the resulting sea ice motion anomalies, highlighting the production of new sea ice through thermodynamic processes. In the vicinity of Ross Island, ERA-Interim underestimates wind speeds by a factor of 1.7, which results in a significant misrepresentation of the impact of winds on polynya processes.

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

10.5194/amt-2018-31 ◽

2018 ◽

Author(s):

Christoph Schlager ◽

Gottfried Kirchengast ◽

Juergen Fuchsberger

Keyword(s):

High Resolution ◽

Wind Field ◽

Climate Models ◽

Meteorological Station ◽

Strong Wind ◽

Climate Data ◽

Wind Fields ◽

Station Network ◽

Weather And Climate ◽

Wind Events

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 eleven meteorological stations at elevations from about 600 m 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 minutes from the WegenerNet JBT, mean wind and wind gust fields at 10 m and 50 m height levels with a high spatial resolution of 100 × 100 m and a temporal resolution of 30 minutes. 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. A 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 with somewhat better values for the strong wind conditions. 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 five-year climate data of the WegenerNet JBT in comparison to nine-year climate data from the high-density WegenerNet meteorological station network Feldbach Region (FBR) analyzed by Schlager et al., (2017)In general, the five-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.

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Spatial and temporal CCN variations in convection-permitting aerosol microphysics simulations in an idealised marine tropical domain

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-3371-2017 ◽

2017 ◽

Vol 17 (5) ◽

pp. 3371-3384 ◽

Cited By ~ 5

Author(s):

Céline Planche ◽

Graham W. Mann ◽

Kenneth S. Carslaw ◽

Mohit Dalvi ◽

John H. Marsham ◽

...

Keyword(s):

Particle Size ◽

High Resolution ◽

Wind Speed ◽

Large Scale ◽

Dimethyl Sulfide ◽

Climate Model ◽

Sea Salt ◽

Limited Area ◽

Strong Wind ◽

Aerosol Composition

Abstract. A convection-permitting limited area model with periodic lateral boundary conditions and prognostic aerosol microphysics is applied to investigate how concentrations of cloud condensation nuclei (CCN) in the marine boundary layer are affected by high-resolution dynamical and thermodynamic fields. The high-resolution aerosol microphysics–dynamics model, which resolves differential particle growth and aerosol composition across the particle size range, is applied to a domain designed to match approximately a single grid square of a climate model. We find that, during strongly convective conditions with high wind-speed conditions, CCN concentrations vary by more than a factor of 8 across the domain (5–95th percentile range), and a factor of ∼  3 at more moderate wind speed. One reason for these large sub-climate-grid-scale variations in CCN is that emissions of sea salt and dimethyl sulfide (DMS) are much higher when spatial and temporal wind-speed fluctuations become resolved at this convection-permitting resolution (making peak wind speeds higher). By analysing how the model evolves during spin-up, we gain new insight into the way primary sea salt and secondary sulfate particles contribute to the overall CCN variance in these realistic conditions, and find a marked difference in the variability of super-micron and sub-micron CCN. Whereas the super-micron CCN are highly variable, dominated by strongly fluctuating sea spray emitted, the sub-micron CCN tend to be steadier, mainly produced on longer timescales following growth after new particle formation in the free troposphere, with fluctuations inherently buffered by the fact that coagulation is faster at higher particle concentrations. We also find that sub-micron CCN are less variable in particle size, the accumulation-mode mean size varying by ∼  20 % (0.101 to 0.123 µm diameter) compared to ∼  35 % (0.75 to 1.10 µm diameter) for coarse-mode particles at this resolution. We explore how the CCN variability changes in the vertical and at different points in the spin-up, showing how CCN concentrations are introduced both by the emissions close to the surface and at higher altitudes during strong wind-speed conditions associated to the intense convective period. We also explore how the non-linear variation of sea-salt emissions with wind speed propagates into variations in sea-salt mass mixing ratio and CCN concentrations, finding less variation in the latter two quantities due to the longer transport timescales inherent with finer CCN, which sediment more slowly. The complex mix of sources and diverse community of processes involved makes sub-grid parameterisation of CCN variations difficult. However, the results presented here illustrate the limitations of predictions with large-scale models and the high-resolution aerosol microphysics–dynamics modelling system shows promise for future studies where the aerosol variations will propagate through to modified cloud microphysical evolution.

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Evaluating the dependence structure of compound precipitation and wind speed extremes

Earth System Dynamics ◽

10.5194/esd-12-1-2021 ◽

2021 ◽

Vol 12 (1) ◽

pp. 1-16

Author(s):

Jakob Zscheischler ◽

Philippe Naveau ◽

Olivia Martius ◽

Sebastian Engelke ◽

Christoph C. Raible

Keyword(s):

High Resolution ◽

Wind Speed ◽

Boundary Conditions ◽

Climate Models ◽

Climate Model ◽

Circulation Model ◽

Dependence Structure ◽

Historical Period ◽

Strong Wind ◽

Wind Extremes

Abstract. Estimating the likelihood of compound climate extremes such as concurrent drought and heatwaves or compound precipitation and wind speed extremes is important for assessing climate risks. Typically, simulations from climate models are used to assess future risks, but it is largely unknown how well the current generation of models represents compound extremes. Here, we introduce a new metric that measures whether the tails of bivariate distributions show a similar dependence structure across different datasets. We analyse compound precipitation and wind extremes in reanalysis data and different high-resolution simulations for central Europe. A state-of-the-art reanalysis dataset (ERA5) is compared to simulations with a weather model (Weather Research and Forecasting – WRF) either driven by observation-based boundary conditions or a global circulation model (Community Earth System Model – CESM) under present-day and future conditions with strong greenhouse gas forcing (Representative Concentration Pathway 8.5 – RCP8.5). Over the historical period, the high-resolution WRF simulations capture precipitation and wind extremes as well as their response to orographic effects more realistically than ERA5. Thus, WRF simulations driven by observation-based boundary conditions are used as a benchmark for evaluating the dependence structure of wind and precipitation extremes. Overall, boundary conditions in WRF appear to be the key factor in explaining differences in the dependence behaviour between strong wind and heavy precipitation between simulations. In comparison, external forcings (RCP8.5) are of second order. Our approach offers new methodological tools to evaluate climate model simulations with respect to compound extremes.

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Generation of High-Resolution Wind Fields from the WegenerNet Dense Meteorological Station Network in Southeastern Austria

Weather and Forecasting ◽

10.1175/waf-d-16-0169.1 ◽

2017 ◽

Vol 32 (4) ◽

pp. 1301-1319 ◽

Cited By ~ 3

Author(s):

Christoph Schlager ◽

Gottfried Kirchengast ◽

Jürgen Fuchsberger

Keyword(s):

Wind Speed ◽

Meteorological Station ◽

High Density ◽

Weather Data ◽

Strong Wind ◽

Wind Fields ◽

Near Surface ◽

Station Network ◽

Wind Speeds ◽

Weather And Climate

Abstract An operational weather diagnostics application for automatic generation of wind fields in near–real time from observations delivered by the high-density WegenerNet meteorological station network in the Feldbach region of Austria is introduced. The purpose of the application is to empirically provide near-surface wind fields of very high spatial and temporal resolution for evaluating convection-permitting climate models as well as investigating weather and climate variability on a local scale. The diagnostic California Meteorological Model (CALMET) is used as the core tool. This model computes 3D wind fields based on observational weather data, a digital elevation model, and land-use categories. The application first produces the required input files from the WegenerNet stations and subsequently runs the CALMET model based on this input. In a third step the modeled wind fields are stored in the WegenerNet data archives every 30 min with a spatial resolution of 100 m × 100 m, while also generating averaged weather and climate products during postprocessing. The performance of the modeling against station observations, for which wind speeds were classified into weak and strong wind speeds, is evaluated and reasonably good results were found for both wind speed classes. The statistical agreement for the vector-mean wind speed is slightly better for weak wind speeds than for strong ones while the difference between modeled and observed wind directions is smaller for strong wind speeds than for weak ones. The application is also a valuable tool for other high-density networks.

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

Atmospheric Measurement Techniques ◽

10.5194/amt-11-5607-2018 ◽

2018 ◽

Vol 11 (10) ◽

pp. 5607-5627 ◽

Cited By ~ 1

Author(s):

Christoph Schlager ◽

Gottfried Kirchengast ◽

Juergen Fuchsberger

Keyword(s):

High Resolution ◽

Climate Models ◽

Meteorological Station ◽

Strong Wind ◽

Mountainous Region ◽

Climate Data ◽

Wind Fields ◽

Station Network ◽

Weather And Climate ◽

Wind Events

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.

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A Study of the Intensity of Tropical Cyclone Idai Using Dual-Polarization Sentinel-1 Data

Remote Sensing ◽

10.3390/rs11232837 ◽

2019 ◽

Vol 11 (23) ◽

pp. 2837 ◽

Cited By ~ 2

Author(s):

Peng Yu ◽

Johnny A. Johannessen ◽

Xiao-Hai Yan ◽

Xupu Geng ◽

Xiaojing Zhong ◽

...

Keyword(s):

Wind Speed ◽

Tropical Cyclone ◽

Band Model ◽

Strong Wind ◽

Cross Polarization ◽

Dual Polarization ◽

Wind Fields ◽

Polarization Model ◽

Wind Speeds ◽

Intense Storm

Monitoring the intensity and size of a tropical cyclone (TC) is a challenging task, and is important for reducing losses of lives and property. In this study, we use Idai, one of the deadliest TCs on record in the Southern Hemisphere, as an example. Dual-polarization synthetic aperture radar (SAR) measurements from the Copernicus Sentinel-1 mission are used to examine the TC structure and intensity. The wind speed is estimated and compared using well known C-band model functions based on calibrated cross-polarization SAR images. Because of the relatively high noise floor of the Sentinel-1 data, wind speeds under 20 m/s from cross-polarization models are ignored and replaced by low to moderate wind speeds retrieved from co-polarization radar signals. Wind fields retrieved from the co- and cross-polarization model results are then merged together to estimate the TC size and the TC fullness scale, a concept related to the wind structure of a storm. Idai has a very strong wind speed and fullness structure, indicating that it was indeed a very intense storm. The approach demonstrates that open and freely available Sentinel-1 SAR data is a unique dataset to estimate the potential destructiveness of similar natural disasters like Idai.

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Evaluating the dependence structure of compound precipitation and wind speed extremes

10.5194/esd-2020-31 ◽

2020 ◽

Author(s):

Jakob Zscheischler ◽

Philippe Naveau ◽

Olivia Martius ◽

Sebastian Engelke ◽

Christoph C. Raible

Keyword(s):

High Resolution ◽

Wind Speed ◽

Boundary Conditions ◽

Climate Models ◽

Climate Model ◽

Circulation Model ◽

Dependence Structure ◽

Historical Period ◽

Strong Wind ◽

Wind Extremes

Abstract. Estimating the likelihood of compound climate extremes such as concurrent drought and heatwaves or compound precipitation and wind speed extremes is important for assessing climate risks. Typically, simulations from climate models are used to assess future risks, but it is largely unknown how well the current generation of models represents compound extremes. Here, we introduce a new metric that measures whether the tails of bivariate distributions show a similar dependence structure across different datasets. We analyse compound precipitation and wind extremes in reanalysis data and different high-resolution simulations for central Europe. A state-of-the-art reanalysis dataset (ERA5) is compared to simulations with a weather model (WRF) either driven by observation-based boundary conditions or a global circulation model (CESM) under present-day and future conditions with strong greenhouse gas forcing (RCP8.5). Over the historical period, the high-resolution WRF simulations capture precipitation and wind extremes and there response to orographic effects more realistically than ERA5. Thus, WRF simulations driven by observation-based boundary conditions are used as a benchmark for evaluating the dependence structure of wind and precipitation extremes. Overall, boundary conditions in WRF appear to be the key factor in explaining differences in the dependence behaviour between strong wind and heavy rainfall between simulations. In comparison, external forcings (RCP8.5) are of second order. Our approach offers new methodological tools to evaluate climate model simulations with respect to compound extremes.

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