The scale of wildfires and their associated smoke plumes have increased in the last four decades and have exacerbated the health risks for people living within wildfire-prone areas. While satellite imagery enables us to monitor the location, abundance, and severity of smoke, datasets such as NOAA’s Hazard Mapping System (HMS) smoke product are unvalidated and may not reflect ground-level smoke conditions. We propose that airports monitoring the presence of smoke may offer a localized constraint on satellite smoke products. Our research aims to validate NOAA’s HMS product by comparing how well the HMS smoke data agree with NOAA’s Integrated Surface Database (ISD) of local, hourly airport data from 2010 to 2020 across the US. Our spatial and temporal analysis shows that the trend in the number of smoke days is similar between the two datasets. HMS smoke plumes are qualitatively categorized into 3 densities: light, medium, and heavy. Particularly, HMS smoke plumes with “medium or heavy” densities have the strongest correlation of r = 0.60 and a mean absolute error of 0.73. We observe the greatest difference in the airport and HMS-derived mean smoke days across the west and east coast, especially in California’s Central Valley and eastern Washington. However, there is a very weak correlation of r = 0.17 between surface-level mean smoke days and from HMS “heavy, medium, or light” density smoke days. Further, using all HMS smoke densities tend to overestimate the trends in and magnitude of smoke days. Based on these results, NOAA’s HMS product is somewhat consistent with trends observed at airports, but caution should be used in assuming equivalence with surface conditions in research investigating wildfire smoke and its consequences for public health.