Sensitivity of the WRF model to PBL parametrizations and nesting techniques: evaluation of surface wind over complex terrain

Abstract

Abstract. Simulating surface wind over complex terrain is a challenge in regional climate modelling. Therefore, this study aims at identifying a setup of the WRF model that minimizes systematic errors of surface winds in hindcast simulations. Major factors of the model configuration are tested to find a suitable setup: the horizontal resolution, the PBL parameterization scheme and the way WRF is nested to the driving dataset. Hence, a number of sensitivity simulations at a spatial resolution of 2 km are carried out and compared to observations. Given the importance of wind storms, the analysis is based on case studies of 24 historical wind storms that caused great economic damage in Switzerland. Each of these events is downscaled using eight different model setups, but sharing the same driving dataset. The results show that the unresolved topography leads to a general overestimation of wind speed in WRF. However, this bias can be substantially reduced by using a PBL scheme that explicitly considers the effects of non-resolved topography, which also improves the spatial structure of wind speed over Switzerland. The wind direction, although generally well reproduced, is not very sensitive to the PBL scheme. Further sensitivity tests include four types of nesting methods: nesting only at the boundaries of the outermost domain, analysis and spectral nudging, and the so-called re-forecast method, where the simulation is frequently restarted. These simulations show that restricting the freedom of the model to develop large-scale disturbances slightly increases the temporal agreement with the observations, at the same time that it further reduces the overestimation of wind speed, especially for maximum wind peaks. The model skill is also evaluated in the outermost domains, where the resolution is coarser. The results demonstrate the important role of horizontal resolution, where the step from 6 to 2 km significantly improves model performance. In summary, the combination of a grid size of 2 km, the non-local PBL scheme modified to explicitly account for non-resolved orography, as well as analysis or spectral nudging, is a superior combination when dynamical downscaling is aimed at reproducing real wind fields.

Föhn winds on South Georgia and their impact on regional climate

“…This is in agreement with previous atmospheric modelling studies which have also looked at föhn events and other strong downslope wind events (see e.g. Valkonen et al, 2010;Steinhoff et al, 2013;Orr et al, 2014;Gómez-Navarro et al, 2015). Since the events are better captured in domains with higher horizontal resolution, this implies that the horizontal resolution of the model is a key constraint for capturing sufficient small-scale detail of the föhn flow at King Edward Point.…”

“…Therefore, this scheme aims to correct the general tendency of WRF to overestimate wind speed (see e.g. Cheng & Steenburgh, 2005), and has subsequently been shown to be more suited for reproducing wind speed over complex terrain (Jiménez & Dudhia, 2012;Lee et al, 2014;Gómez-Navarro et al, 2015;Gonçalves-Ageitos et al 2015). In contrast to this switch, accounting for topographical and shading effects (slope_rad and topo_sha; these switches account for shadows induced by nearby topography, self-shading and land surface inclination, which subsequently affect incoming radiation) have minimal impact on the surface meteorology during these föhn case studies.…”

An assessment of the Polar Weather Research and Forecasting (WRF) model representation of near‐surface meteorological variables over West Antarctica

“…Note that this resolution is 3 times higher than current hindcast experiments for Antarctica using WRF and Regional Atmospheric Climate Model, version 2.0 (RACMO2) undertaken as part of the Polar‐Coordinated Regional Downscaling Experiment initiative, and a factor of approximately 2 higher than the RACMO2 simulations detailed in Lenaerts et al []. Notwithstanding this, the insensitivity of our results to varying spatial resolution between 5 and 15 km for the coastal region of West Antarctica is at odds when compared to studies such as Valkonen et al [], Elvidge et al [], Orr et al [], and Gómez‐Navarro et al []. These studies stressed the need for kilometer‐scale grid resolution, which possibly raises doubts as to the quality of the GTOPO30 and Bedmap2 data sets used to make the model orography boundary conditions, i.e., whether they are overly smooth compared to reality.…”

“…Improved representation of the boundary layer in Polar WRF also makes a meaningful reduction in temperature [ Valkonen et al , ] and wind speed biases [ Gómez‐Navarro et al , ]. This was demonstrated by the sensitivity experiment Run A1 which used the MYJ boundary layer scheme instead of the MYNN scheme, resulting in a much improved representation of the diurnal cycle in 2 m temperature (particularly in January).…”

“…Finally, we suspect that the large positive pressure bias at Bear Peninsula is due to the pressure sensor not being calibrated correctly, as possible uncertainty in the measured elevation of the site was ruled out as the cause as this was verified from an independent source. Improved representation of the boundary layer in Polar WRF also makes a meaningful reduction in temperature [Valkonen et al, 2014] and wind speed biases [Gómez-Navarro et al, 2015]. This was demonstrated by the sensitivity experiment Run A1 which used the MYJ boundary layer scheme instead of the MYNN scheme, resulting in a much improved representation of the diurnal cycle in 2 m temperature (particularly in January).…”