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Evaluating Mixing Height Estimations in the Western United States Using Satellite Observations

Authors :
Christopher Wright
Dean Berkowitz
Julia Liu
Lauren Mock
Brandy Nisbet-Wilcox
Kenton Ross
Travis Toth
Keith Weber
Source :
Journal of Operational Meteorology. :24-32
Publication Year :
2023
Publisher :
National Weather Association, 2023.

Abstract

Wildfire smoke can be transported far from its origin, adversely impacting human health. The height of the atmospheric mixing layer, the near-surface layer of the troposphere in which turbulent convection leads to vertical mixing, is called the mixing height. Mixing height is a critical input in the smoke dispersion and air quality models used by agencies that monitor wildfires and air pollution. These models, coupled with forecaster expertise, are also used to determine if it is safe to execute a prescribed burn. In this paper, we derive mixing heights from two satellite datasets in order to assess mixing height forecasts produced by the National Weather Service (NWS) Fire Weather Program. Namely, we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) Vertical Feature Masks (VFM) and vertical water vapor profiles from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our comparison indicates that NWS forecasts tend to underestimate CALIOP mixing heights with a median relative error of –13% and a mean relative error of –3.34%. Although MODIS and NWS mixing heights showed some agreement below 3 km, the lower vertical resolution of the MODIS estimates hindered a full comparison. We examine the discrepancies among mixing heights over wildfire smoke plumes determined by these methods and discuss biases and limitations. This work provides insight into potential bias patterns present in current mixing height forecasts and provides directions for future improvements in both NWS mixing height forecasts and satellite-based measurements of mixing height.

Details

ISSN :
23256184
Database :
OpenAIRE
Journal :
Journal of Operational Meteorology
Accession number :
edsair.doi...........53511c003aba5b3e34888ddaa3931e2e