The National Blend of Models (NBM) has already integrated this bias correction algorithm into its process by routinely bias correcting all gridded model data using the UnRestricted Mesoscale Analysis (URMA) as ground truth. For most weather elements bias correcting to URMA works quite well. However, URMA wind speed and wind gust analyses, which are derived from a disproportionate number of mesonet sites when compared to the number of METARs, has introduced a very noticeable low bias for both wind speed and wind gust especially in the vicinity of METAR locations. These biases are then propagated into the NBM by virtue of the NBM using URMA as its analyses. While URMA developers are aware of this problem and are actively working on a solution, in the interim, we plan to blend all MDL MOS wind speed and wind gust guidance. Each MOS input will be routinely bias corrected and weighted to its respective METAR location using the algorithm proposed by Woodcock and Engle [Woodcock, F., and C. Engel, 2005: Operational consensus forecasts. Wea. Forecasting, 20, 101–111]. The bias corrected values will then be objectively weighted and blended and then placed at the grid point nearest its respective METAR site. In this manner we stay true to the objective weighting methodology used in the NBM and simultaneously leverage the METAR observations and MOS guidance to more accurately predict wind speeds and wind gusts in the vicinity of airports where wind guidance is crucial to aviation operations.