1 citations · 2 across the 8 of their papers we have counts for
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A Generative Framework for Probabilistic, Spatiotemporally Coherent Downscaling of Climate Simulation
Jonathan Schmidt, Luca Schmidt, Felix Strnad +2
Local climate information is crucial for impact assessment and decision-making, yet coarse global climate simulations cannot capture small-scale phenomena. Current statistical down…
Climate data selection for multi-decadal wind power forecasts
Sofia Morelli, Nina Effenberger, Luca Schmidt +1
Reliable wind speed data is crucial for applications such as estimating local (future) wind power. Global Climate Models (GCMs) and Regional Climate Models (RCMs) provide forecasts…
Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6
Nina Effenberger, Nicole Ludwig
Climate change will impact wind and therefore wind power generation with largely unknown effect and magnitude. Climate models can provide insights and should be used for long-term…
Wind Power Assessment based on Super-Resolution and Downscaling -- A Comparison of Deep Learning Methods
Luca Schmidt, Nicole Ludwig
The efficient placement of wind turbines relies on accurate local wind speed forecasts. Climate projections provide valuable insight into long-term wind speed conditions, yet their…