Mark Ruminski

Description and Verification of the NOAA Smoke Forecasting System: The 2007 Fire Season

Abstract An overview of the National Oceanic and Atmospheric Administration’s (NOAA) current operational Smoke Forecasting System (SFS) is presented. This system is intended as guidance to air quality forecasters and the public for fine particulate matter (≤2.5 μm) emitted from large wildfires and agricultural burning, which can elevate particulate concentrations to unhealthful levels. The SFS uses National Environmental Satellite, Data, and Information Service (NESDIS) Hazard Mapping System (HMS), which is based on satellite imagery, to establish the locations and extents of the fires. The particulate matter emission rate is computed using the emission processing portion of the U.S. Forest Service’s BlueSky Framework, which includes a fuel-type database, as well as consumption and emissions models. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is used to calculate the transport, dispersion, and deposition of the emitted particulate matter. The model evaluation is carried out...

Verification of the NOAA Smoke Forecasting System: Model Sensitivity to the Injection Height

Abstract A detailed evaluation of NOAA’s Smoke Forecasting System (SFS) is a fundamental part of its development and further refinement. In this work, particulate matter with a diameter less than or equal to 2.5-μm (PM2.5) concentration levels, simulated by the SFS, have been evaluated against satellite and surface measurements. Four multiday forest fire case studies, one covering the continental United States, two in California, and one near the Georgia–Florida border, have been analyzed. The column-integrated PM2.5 concentrations for these cases compared to the satellite measurements showed a similar or better statistical performance than the mean performance of the SFS for the period covering 1 September 2006–1 November 2007. However, near the surface, the model shows a tendency to overpredict the measured PM2.5 concentrations in the western United States and underpredict concentrations for the Georgia–Florida case. Furthermore, a sensitivity analysis of the model response to changes in the smoke relea...

A statistical model for determining impact of wildland fires on Particulate Matter (PM2.5) in Central California aided by satellite imagery of smoke

As the climate in California warms and wildfires become larger and more severe, satellite-based observational tools are frequently used for studying impact of those fires on air quality. However little objective work has been done to quantify the skill these satellite observations of smoke plumes have in predicting impacts to PM2.5 concentrations at ground level monitors, especially those monitors used to determine attainment values for air quality under the Clean Air Act. Using PM2.5 monitoring data from a suite of monitors throughout the Central California area, we found a significant, but weak relationship between satellite-observed smoke plumes and PM2.5 concentrations measured at the surface. However, when combined with an autoregressive statistical model that uses weather and seasonal factors to identify thresholds for flagging unusual events at these sites, we found that the presence of smoke plumes could reliably identify periods of wildfire influence with 95% accuracy.

NAQFC Developmental Forecast Guidance for Fine Particulate Matter (PM2.5)

AbstractThe National Air Quality Forecasting Capability (NAQFC) upgraded its modeling system that provides developmental numerical predictions of particulate matter smaller than 2.5 μm in diameter (PM2.5) in January 2015. The issuance of PM2.5 forecast guidance has become more punctual and reliable because developmental PM2.5 predictions are provided from the same system that produces operational ozone predictions on the National Centers for Environmental Prediction (NCEP) supercomputers.There were three major upgrades in January 2015: 1) incorporation of real-time intermittent sources for particles emitted from wildfires and windblown dust originating within the NAQFC domain, 2) suppression of fugitive dust emissions from snow- and/or ice-covered terrain, and 3) a shorter life cycle for organic nitrate in the gaseous-phase chemical mechanism. In May 2015 a further upgrade for emission sources was included using the U.S. Environmental Protection Agency’s (EPA) 2011 National Emission Inventory (NEI). Emiss...

Comparison of the Hazard Mapping System (HMS) Fire Product to Ground‐based Fire Records in Georgia, USA

Biomass burning has a significant and adverse impact on air quality, climate change, and various ecosystems. The Hazard Mapping System (HMS) detects fires using data from multiple satellite sensors in order to maximize its fire detection rate. However, to date, the detection rate of the HMS fire product for small fires has not been well studied, especially using ground-based fire records. This paper utilizes the 2011 fire information compiled from ground observations and burn authorizations in Georgia to assess the comprehensiveness of the HMS active fire product. The results show that detection rates of the hybrid HMS increase substantially by integrating multiple satellite instruments. The detection rate increases dramatically from 3% to 80% with an increase in fire size from less than 0.02 km2 to larger than 2 km2, resulting in detection of approximately 12% of all recorded fires which represent approximately 57% of the total area burned. The spatial pattern of detection rates reveals that grid cells with high detection rates are generally located in areas where large fires occur frequently. The seasonal analysis shows that overall detection rates in winter and spring (12% and 13%, respectively) are higher than those in summer and fall (3% and 6%, respectively), mainly because of higher percentages of large fires (>0.19 km2) that occurred in winter and spring. The land cover analysis shows that detection rates are 2–7 percentage points higher in land cover types that are prone to large fires such as forestland and shrub land.

Use of multiple satellite sensors in NOAA's operational near real-time fire and smoke detection and characterization program

Environmental satellite data provides a unique capability to monitor large areas of the globe for the occurrence of fires and the smoke that they generate which can cause considerable degradation of air quality on a regional basis. The Hazard Mapping System (HMS) incorporates seven polar and geostationary satellites into a single workstation environment. While individual satellite platforms can provide important information that can be used in air quality models, integrating several platforms allows for the combined strengths of various spacecraft instruments to overcome their individual limitations. The HMS was specifically designed as an interactive tool to identify fires and the smoke emissions they produce over North America in an operational environment. Automated fire detection algorithms are employed for each of the sensors. Analysts apply quality control procedures for the automated fire detections by eliminating those that are deemed to be false and adding hotspots that the algorithms have not detected via examination of the satellite imagery. Areas of smoke are outlined by the analyst using animated visible channel imagery. An estimate of the smoke concentration is assigned to each plume outlined. The automated Geostationary Operational Environmental Satellite (GOES) Aerosol and Smoke Product (GASP) is used as an aid in providing smoke concentrations and identifying areas of smoke. HMS analysts provide estimates on the size, initiation and duration of smoke emitting fires that are used as input to NOAAs national air quality forecast capability. This system is currently providing 48 hour smoke forecast guidance for air quality forecasters and utilizes the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model.

Chapter 22 Regional Real-Time Smoke Prediction Systems

Abstract Several real-time smoke prediction systems have been developed worldwide to help land managers, farmers, and air quality regulators balance land management needs against smoke impacts. Profiled here are four systems that are currently operational for regional domains for North America and Australia, providing forecasts to a well-developed user community. The systems link fire activity data, fuels information, and consumption and emissions models, with weather forecasts and dispersion models to produce a prediction of smoke concentrations from prescribed fires, wildfires, or agricultural fires across a region. The USDA Forest Services BlueSky system is operational for regional domains across the United States and obtains prescribed burn information and wildfire information from databases compiled by various agencies along with satellite fire detections. The U.S. National Oceanic and Atmospheric Administration (NOAA) smoke prediction system is initialized with satellite fire detections and is operational across North America. Washington State Universitys ClearSky agricultural smoke prediction system is operational in the states of Idaho and Washington, and burn location information is input via a secure Web site by regulators in those states. The Australian Bureau of Meteorology smoke prediction system is operational for regional domains across Australia for wildfires and prescribed burning. Operational uses of these systems are emphasized as well as the approaches to evaluate their performance given the uncertainties associated with each systems subcomponents. These real-time smoke prediction systems are providing a point of interagency understanding between land managers and air regulators from which to negotiate the conflicting needs of ecological fire use while minimizing air quality health impacts.

Monitoring fire and smoke emissions with the hazard mapping system

The Hazard Mapping System (HMS) was developed in 2001 by the National Oceanic and Atmospheric Administrations (NOAA) National Environmental Satellite and Data Information Service (NESDIS) as an interactive tool to identify fires and the smoke emissions they produce over North America in an operational environment. The system utilizes 2 geostationary and 5 polar orbiting environmental satellites. Automated fire detection algorithms are employed for each of the sensors. Analysts apply quality control procedures for the automated fire detections by eliminating those that are deemed to be false and adding hotspots that the algorithms have not detected via a thorough examination of the satellite imagery. Areas of smoke are outlined by the analyst using animated visible channel imagery. A quantitative assessment of the smoke concentration is not performed at this time. However, integration of automated aerosol and smoke products into the HMS, such as the Geostationary Operational Environmental Satellite (GOES) Aerosol and Smoke Product (GASP) and the MODIS aerosol product in early 2006 and the aerosol product from the Ozone Monitoring Instrument (OMI) in late 2006 are expected to aid in providing smoke concentrations and identifying areas of smoke. HMS analysts also denote fires that are producing smoke emissions detected in satellite imagery as well as the start and end times of the emissions. These fire locations are used as input to the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. HYSPLIT utilizes a dynamic emissions rate for these fires as specified by the Blue Skies framework.

Impacts of fire smoke plumes on regional air quality, 2006–2013

Increases in the severity and frequency of large fires necessitate improved understanding of the influence of smoke on air quality and public health. The objective of this study is to estimate the effect of smoke from fires across the continental U.S. on regional air quality over an extended period of time. We use 2006–2013 data on ozone (O3), fine particulate matter (PM2.5), and PM2.5 constituents from environmental monitoring sites to characterize regional air quality and satellite imagery data to identify plumes. Unhealthy levels of O3 and PM2.5 were, respectively, 3.3 and 2.5 times more likely to occur on plume days than on clear days. With a two-stage approach, we estimated the effect of plumes on pollutants, controlling for season, temperature, and within-site and between-site variability. Plumes were associated with an average increase of 2.6 p.p.b. (2.5, 2.7) in O3 and 2.9 µg/m3 (2.8, 3.0) in PM2.5 nationwide, but the magnitude of effects varied by location. The largest impacts were observed across the southeast. High impacts on O3 were also observed in densely populated urban areas at large distance from the fires throughout the southeast. Fire smoke substantially affects regional air quality and accounts for a disproportionate number of unhealthy days.