Assimilation of Aerosol Optical Depth Into The Warn-on-forecast System For Smoke (wofs-smoke)

Abstract

This research extends the Warn-on-Forecast System for Smoke (WoFS-Smoke) by adding the capability to assimilate aerosol optical depth (AOD) retrievals from the Geostationary Operational Environmental Satellite Series-R (GOES-R) satellites. The WoFS is a rapidly cycling, ensemble-based analysis and forecasting system designed to generate short term (0–3 hr) forecasts of high impact weather. WoFS-Smoke provides short-term forecasts of smoke aerosols injected into the atmosphere from ongoing wildfires. The vertically integrated concentration of smoke aerosols in the atmosphere can be estimated from satellite based AOD retrievals. To assimilate AOD into WoFS-Smoke, a smoke control variable is added to the prognostic state that is updated during each assimilation cycle. Then, a forward operator is created to relate modeled smoke aerosols to AOD retrievals using a mathematical function developed for the smoke-AOD conversion used by the High-Resolution Rapid Refresh for Smoke. Finally, GOES-R AOD retrievals are quality controlled and are assimilated at 15 min intervals. Comparing analyzed AOD with smoke and other atmospheric variables indicates that assimilating AOD not only directly impacts smoke aerosol concentration in the system, but also has indirect impacts on variables such as temperature, humidity, and wind. Results from two wildfire cases in Oklahoma and Arizona show that assimilating AOD substantially impacts the concentration and distribution of smoke aerosols in the system. Forecast verification against satellite and surface observations indicates the overall impact of assimilating AOD in WoFS-Smoke can improve forecast skill of smoke and the surrounding environment. Key Points Ensemble data assimilation of Geostationary Operational Environmental Satellite Series-R aerosol optical depth (AOD) retrievals for short-term smoke forecasts Assimilation of AOD improves the forecast of smoke aerosols in two wildfire cases Improved smoke forecasts impact forecasts of the surrounding atmospheric conditions Plain Language Summary Short-term forecasts of smoke generated from the Warn-on-Forecast System for Smoke (WoFS-Smoke) data assimilation and forecasting system are improved through the assimilation of aerosol characteristics derived from satellites. Satellite measurements of aerosols provide information on the amount and distribution of aerosols in the atmosphere. Assimilating these data into a system designed to track smoke aerosols produces a more accurate analysis of smoke concentration. This work uses aerosol observations from a geostationary orbiting satellite to take advantage of the high temporal frequency (<15 min) needed to continuously update smoke in WoFS-Smoke. Testing of two wildfire events showed that assimilating aerosol characteristics improved both smoke forecasts and forecasts of the surrounding atmospheric conditions.