Extended-range high-resolution dynamical downscaling over a continental-scale spatial domain with atmospheric and surface nudging

Extended‐range high‐resolution mesoscale simulations with limited‐area atmospheric models when applied to downscale regional analysis fields over large spatial domains can provide valuable information for many applications including the weather‐dependent renewable energy industry. Long‐term simulations over a continental‐scale spatial domain, however, require mechanisms to control the large‐scale deviations in the high‐resolution simulated fields from the coarse‐resolution driving fields. As enforcement of the lateral boundary conditions is insufficient to restrict such deviations, large scales in the simulated high‐resolution meteorological fields are therefore spectrally nudged toward the driving fields. Different spectral nudging approaches, including the appropriate nudging length scales as well as the vertical profiles and temporal relaxations for nudging, have been investigated to propose an optimal nudging strategy. Impacts of time‐varying nudging and generation of hourly analysis estimates are explored to circumvent problems arising from the coarse temporal resolution of the regional analysis fields. Although controlling the evolution of the atmospheric large scales generally improves the outputs of high‐resolution mesoscale simulations within the surface layer, the prognostically evolving surface fields can nevertheless deviate from their expected values leading to significant inaccuracies in the predicted surface layer meteorology. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil moisture, and snow conditions, toward their expected values obtained from a high‐resolution offline surface scheme is therefore proposed to limit any considerable deviation. Finally, wind speed and temperature at wind turbine hub height predicted by different spectrally nudged extended‐range simulations are compared against observations to demonstrate possible improvements achievable using higher spatiotemporal resolution. Key Points The main challenges for extended‐range mesoscale simulations are identifiedControlling large‐scale atmospheric deviations improves surface layer outputsFurther improvements are possible by correcting the prognostic surface fields