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

Details

• Journal Title:
  Geoscientific Model Development
• Personal Author:
  Pan, Li ; Kim, HyunCheol ; Lee, Pius ; Saylor, Rick ; Tang, YouHua ; Tong, Daniel ; Baker, Barry ; Kondragunta, Shobha ; Xu, Chuanyu ; Ruminski, Mark G. ; Chen, Weiwei ; Mcqueen, Jeff ; Stajner, Ivanka
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; ARL (Air Resources Laboratory) ; CISESS (Cooperative Institute for Satellite Earth System Studies) ; NESDIS (National Environmental Satellite, Data, and Information Service) ; NWS (National Weather Service) ; NCEP (National Centers for Environmental Prediction) ; EMC (Environmental Modelling Center)
• Description:
  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.
• Keywords:
  Fire Smoke Observations Simulations Fire Smoke
• Source:
  Geosci. Model Dev., 13, 2169–2184, 2020
• DOI:
  https://doi.org/10.5194/gmd-13-2169-2020
• Document Type:
  Journal Article
• Rights Information:
  CC BY
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha256:5e8b3ea83a91462624faaa06b691492de7d1e1eba5c48a5ce017e9343c4cb3df
• Download URL:
  https://repository.library.noaa.gov/view/noaa/29188/noaa_29188_DS1.pdf
• File Type:
  [PDF - 16.13 MB ]