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,Mark G Ruminski,Shobha Kondragunta,Barry Baker,Jeff Mcqueen,Hyuncheol Kim,Pius Lee,Daniel Tong,Weiwei Chen,Ivanka Stajner,Rick Saylor,Chuanyu Xu,Youhua Tang

doi:10.5194/gmd-13-2169-2020

Abstract

Abstract. Multiple observation data sets – Interagency Monitoring of Protected Visual Environments (IMPROVE) network data, the Automated Smoke Detection and Tracking Algorithm (ASDTA), Hazard Mapping System (HMS) smoke plume shapefiles and aircraft acetonitrile (CH3CN) measurements from the NOAA Southeast Nexus (SENEX) field campaign – are used to evaluate the HMS–BlueSky–SMOKE (Sparse Matrix Operator Kernel Emission)–CMAQ (Community Multi-scale Air Quality Model) fire emissions and smoke plume prediction system. A similar configuration 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 was valuable for deriving both fire emissions and forecast evaluation. This study also 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 retrieve fire signals and synergistically use multiple data sets. We also addressed the limitations of each of the observation data sets and evaluation methods.

Highlights

Wildfires and agricultural/prescribed burns are common in North America all year round but predominantly occur during the spring and summer months (Wiedinmyer et al, 2006)
The National Air Quality Forecasting Capability (NAQFC) fire simulation consists of the NOAA National Environmental and Satellite Data and Information Service (NESDIS) Hazard Mapping System (HMS) fire detection algorithm, the US Forest Service (USFS) BlueSky fire emissions estimation algorithm, the US EPA Sparse Matrix Operator Kernel
A system accounting for fire emissions in a chemical transport model is described, including a satellite fire-detecting system (HMS), a fire emission calculation model (BlueSky), a pre-processing of fire emissions (SMOKE) and simulation over the Southeast Nexus (SENEX) domain by Community Multi-scale Air Quality Model (CMAQ)

Summary

Introduction

Wildfires and agricultural/prescribed burns are common in North America all year round but predominantly occur during the spring and summer months (Wiedinmyer et al, 2006). These fires pose a significant risk to air quality and human health (Delfino et al, 2009; Rappold et al, 2011; Dreessen et al, 2016; Wotawa and Trainer, 2000; Sapkota et al, 2005; Jaffe et al, 2013; Johnston et al, 2012). Since January 2015, smoke emissions from fires have been included in the National Air Quality Forecasting Capability (NAQFC) daily PM2.5 operational forecast (Lee et al, 2017). Pan et al.: Evaluating a fire simulation algorithm in NAQFC

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