Abstract
Abstract. With the rising share of renewable energy sources like wind energy in the energy mix, high-impact weather events like mid-latitude storms increasingly affect energy production, grid stability and safety and reliable forecasting becomes very relevant for e.g. transmission system operators to allow for actions to reduce imbalances. Traditionally, meteorological forecasts are provided by limited-area weather prediction models (LAMs), which can use high enough model resolution to represent the range of atmospheric scales of motions associated with such storm structures. While generally satisfactory, deterioration and insufficient deepening of large-scale storm structures are observed when they are introduced near the lateral boundaries of the LAM due to inadequate spatial and temporal interpolation. Global models with regional mesh refinement capabilities like the Model for Prediction Across Scales (MPAS) have the potential to provide an alternative, while avoiding sharp resolution jumps and lateral boundaries. In this study, MPAS' capabilities of simulating key evaluation metrics like storm intensity, storm location and storm duration are investigated based on a case study and assessed in comparison with buoy measurements, forecast products from the Climate Forecast System (CFSv2) and simulations with the Weather Research and Forecasting (WRF) LAM. Quasi-uniform and variable-resolution MPAS mesh configurations with different model physics settings are designed to analyze the impact of the mesh refinement and model physics on the model performance. MPAS shows good performance in predicting storm intensity based on the local minimum sea level pressure, while time of local minimum sea level pressure (storm duration) was generally estimated too late (too long) in comparison with the buoy measurements in part due to an early west-wards shift of the storm center in MPAS. The variable-resolution configurations showed a combination of an additional south-westwards shift and deviations in the sea level pressure field south-west of the storm center that introduced additional bias to the time of local minimum sea level pressure at some locations. The study highlights the need for a more detailed analysis of applied mesh refinements for particular applications and emphasizes the importance of methods like data assimilation techniques to prevent model drifts.
Highlights
Within the field of wind energy, weather patterns like midlatitude cyclones can affect several aspects of wind power production
Meteorological forecasts are provided by limitedarea weather prediction models (LAMs), which can use high enough model resolution to represent the range of atmospheric scales of motions associated with such storm structures
The results have shown that Model for Prediction Across Scales (MPAS) is generally able to represent storm intensity for the presented case, but challenges have been identified in the estimation of time of local minimum sea level pressure (tLMSLP) and storm duration
Summary
Within the field of wind energy, weather patterns like midlatitude cyclones can affect several aspects of wind power production. The frontal systems that are tightly connected with the passing low pressure system can cause sharp ramps in the power production (Steiner et al, 2017) or shut-down of whole wind farms when cut-out wind speed criteria are exceeded (Cutululis et al, 2012). This affects, among others, grid stability and safety (Cutululis et al, 2012; Steiner et al, 2017) and can affect the energy market (Artipoli and Durante, 2014). Reliable forecasts of mid-latitude cyclones are, seen
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