Winter Maintenance Forecast Improvements Using Mobile Observations

Date and Time: Tuesday, May 9, 2023: 10:00 AM - 12:00 PM
Location: Keck 100

 

Lead Presenter:  James McCaa, Technical Product Manager
Affiliation:  Vaisala
Social Media Handle:  @jim_mccaa

Lead Presenter Biography

James McCaa, PhD, has extensive experience in developing and applying numerical models of atmospheric and associated weather phenomena. He currently leads a development team working on combining new data sets with traditional road weather modeling to improve the information available to winter maintenance decision-makers. His specialties include scalable computing and the parameterization of boundary layer processes, especially near-surface winds. Prior to joining Vaisala, he held positions at 3TIER, a renewable energy consulting company, the Applied Physics Laboratory of the University of Washington, and the National Center for Atmospheric Research. At Vaisala he has focused his efforts on practical knowledge of how to operate models to deliver meaningful and accurate forecasts. 

Co-Authors

Presentation Description 

Impacts of mobile sensing data on a road weather forecasting system were analyzed. The data was assimilated in the forecast system by using them to adjust the model state through a radiative coupling process for temperature, and by direct inclusion of water layer thicknesses. The effects of the mobile sensing data were estimated by looking at the frequency and magnitude of the adjustments made to the model when they were available.

Mean absolute error of surface temperature was reduced in 30-minute ahead forecasts by slightly
more than 0.5 °C, or approximately 35%. The benefit of the mobile observations decayed over
roughly 12 hours.

In an operational system with a rapid forecast update cycle, the inclusion of mobile observations should have a positive impact on operational decisions made during winter weather events.

Extended Summary

Extended Abstract

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Presentation Video