Evaluating a fire smoke simulation algorithm in the National Air Quality Forecast Capability (NAQFC) by using multiple observation data sets during the Southeast Nexus (SENEX) field campaign

Li Pan, Hyun Cheol Kim, Pius Lee, Rick Saylor, Youhua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen (+1 others)
2018 Geoscientific Model Development Discussions  
<p><strong>Abstract.</strong> Multiple observation data sets: Interagency Monitoring of Protected Visual Environments (IMPROVE) network data, Automated Smoke Detection and Tracking Algorithm (ASDTA), Hazard Mapping System (HMS) smoke plume shapefiles and aircraft acetonitrile (CH<sub>3</sub>CN) measurements from the NOAA Southeast Nexus (SENEX) field campaign are used to evaluate the HMS-BlueSky-SMOKE CMAQ fire emissions and smoke plume prediction system. A similar configuration is used in the
more » ... ion is used in the US National Air Quality Forecasting Capability (NAQFC). The system was found to capture most of the observed fire signals. Usage of HMS-detected fire hotspots and smoke plume information were valuable for both deriving fire emissions and forecast evaluation. This study also helped identified that the operational NAQFC did not include fire contributions through lateral boundary conditions resulting in significant simulation uncertainties. In this study we focused both on system evaluation and evaluation methods. We discussed how to use observational data correctly to filter out fire signals and synergistically use multiple data sets. We also addressed the limitations of each of the observation data sets and evaluation methods.</p>
doi:10.5194/gmd-2018-230 fatcat:qi4mqsgzuveutoq572p2xflrvu