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Abstract We utilized high temporal resolution, near-surface observations of sustained winds and gusts from two networks, the primarily airport-based Automated Surface Observing System (ASOS) and the New York State Mesonet (NYSM), to evaluate forecasts from the operational High-Resolution Rapid Refresh (HRRR) model, versions 3 and 4. Consistent with past studies, we showed the model has a high degree of skill in reproducing the diurnal variation of network-averaged wind speed of ASOS stations, but also revealed several areas where improvements could be made. Forecasts were found to be underdispersive, deficient in both temporal and spatial variability, with significant errors occurring during local nighttime hours in all regions and in forested environments for all hours of the day. This explained why the model overpredicted the network-averaged wind in the NYSM because much of that network’s stations are in forested areas. A simple gust parameterization was shown not only to have skill in predicting gusts in both networks but also to mitigate systemic biases found in the sustained wind forecasts. Significance Statement Many users depend on forecasts from operational models and need to know their strengths, weaknesses, and limitations. We examined generally high-quality near-surface observations of sustained winds and gusts from the nationwide Automated Surface Observing System (ASOS) and the New York State Mesonet (NYSM) and used them to evaluate forecasts from the previous (version 3) and current (version 4) operational High-Resolution Rapid Refresh (HRRR) model for a selected month. Evidence indicated that the wind forecasts are excellent yet imperfect and areas for further improvement remain. In particular, we showed there is a high degree of skill in representing the diurnal variation of sustained wind at ASOS stations but insufficient spatial and temporal forecast variability and overprediction at night everywhere, in forested areas at all times of day, and at NYSM sites in particular, which are more likely to be sited in the forest. Gusts are subgrid even at the fine grid spacing of the HRRR (3 km) and thus must be parameterized. Our simple gust algorithm corrected for some of these systemic biases, resulting in very good predictions of the maximum hourly gust. 

We analyzed meteorological conditions that occurred during the December 2021 Boulder, Colorado, downslope windstorm. This event is of particular interest due to the ignition and spread of the Marshall Fire, which quickly became the most destructive wildfire in Colorado history. Observations indicated a rapid onset of fast winds with gusts as high as 51 m/s that generally remained confined to the east-facing slopes and foothills of the Rockies, similar to previous Boulder windstorms. After about 12 h, the windstorm shifted into a second, less intense phase. Midtropospheric winds above northwestern Colorado weakened prior to the onset of strong surface winds and the event strength started waning as stronger winds moved back into the area. Forecasts from NOAA high-resolution operational models initialized more than a few hours prior to windstorm onset did not simulate the start time, development rate and/or maximum strength of the windstorm correctly, and day-ahead runs even failed to develop strong downslope windstorms at all. Idealized modeling confirmed that predictability was limited by errors on the synoptic scale affecting the midtropospheric wind conditions representing the Boulder windstorm’s inflow environment. Gust forecasts for this event were critically evaluated. 

Abstract Subgrid-scale turbulence in numerical weather prediction models is typically handled by a PBL parameterization. These schemes attempt to represent turbulent mixing processes occurring below the resolvable scale of the model grid in the vertical direction, and they act upon temperature, moisture, and momentum within the boundary layer. This study varies the PBL mixing strength within 4-km WRF simulations of a 26–29 January 2015 snowstorm to assess the sensitivity of baroclinic cyclones to eddy diffusivity intensity. The bulk critical Richardson number for unstable regimes is varied between 0.0 and 0.25 within the YSU PBL scheme as a way of directly altering the depth and magnitude of subgrid-scale turbulent mixing. Results suggest that varying the bulk critical Richardson number is similar to selecting a different PBL parameterization. Differences in boundary layer moisture availability, arising from reduced entrainment of dry, free tropospheric air, lead to variations in the magnitude of latent heat release above the warm frontal region, producing stronger upper-tropospheric downstream ridging in simulations with less PBL mixing. The more amplified flow pattern impedes the northeastward propagation of the surface cyclone and results in a westward shift of precipitation. In addition, trajectory analysis indicates that ascending parcels in the less-mixing simulations condense more water vapor and terminate at a higher potential temperature level than do ascending parcels in the more-mixing simulations, suggesting stronger latent heat release when PBL mixing is reduced. These results suggest that spread within ensemble forecast systems may be improved by perturbing PBL mixing parameters that are not well constrained.