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NASA NTRSDate not supplied

Exemplifying the Usability of NASA Earth Observations to Analyze Potential Risk Factors that Predispose Wildfires in the Rural-Urban Areas of Córdoba, Argentina

In recent years, Córdoba, Argentina has experienced intensified wildfire activity, with fires in 2020 alone scorching over 300,000 hectares within the province. Potential causes for the increased burn area include climate change, the expanding wildland-urban interface, and inadequate fire management practices. Previous studies have produced fire frequency maps for the region, but gaps remain in understanding the parameters influencing fire behavior and growth. This project partnered with the Instituto Nacional de Tecnología Agropecuaria to address these gaps by utilizing NASA’s remote sensing capabilities to analyze key wildfire risk factors. Using a combination of data inputs from Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), and Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), a ten-year baseline was created using environmental variables to determine anomalies that influenced the fires of 2020. Of these anomalies, the baseline data were used to calculate the statistical significance of the environmental factors to the wildfires. This study found that the normalized difference vegetation index (NDVI) and precipitation were the strongest indicators for the September 2020 wildfires. Using the environmental risk factors, this project created a wildfire risk map for the province of Córdoba, which can be used to enhance partner’s fire management strategies and decision-making processes.

Chassety Raines↗
NASA NTRS2024

Assessing the effects of landcover and land use change on wildfire exposure and risk to communities and olive orchards in Mediterranean landscapes

A growing concern in the Mediterranean region is that recent landcover and land use change is increasing wildfire risk, or the exposure and impacts of wildfire to valued resources. However, the magnitude of these effects is not well understood given the widely diverse landscapes of communities, natural vegetation, and agricultural land. In this study, we use wildfire simulation modeling to assess how landcover and land use changes in three areas of southern Greece have affected exposure of- and fire risk to- communities and economically important permanent agriculture such as Olea europaea (European olive) orchards. We mapped agricultural and wildland fuel change from 2000 to 2020 and simulated fuel scenarios in agricultural land to assess the impacts of agricultural land practices, such as understory clearing, on fire risk. We show that wildfire exposure and risk to communities and permanent agriculture has increased in some areas due to natural fuel densification and decreased in other areas, mainly due to agricultural land expansion. These results highlight that wildfire exposure and risk are driven by local conditions including density and location of communities, spatial arrangement of natural fuels and agricultural land, and agricultural land use practices. Human settlement burn probability and modeled permanent crop loss increased with greater unmaintained agricultural area in all study areas, emphasizing the importance of agricultural land maintenance practices, such as understory clearing, to reduce fuel continuity and fire intensity. Ultimately, quantitative fire risk analyses such as this study provide a useful framework to identify areas of concern where either fuel mitigation or landowner incentives to maintain agricultural land in a less-burnable condition could be applied.

Aaron M Sparks↗
NASA NTRSDate not supplied

Advancing Wildfire Monitoring with TEMPO and ML tools: Hourly Smoke and Fire‑Front Mapping and Near‑Surface NO₂ Predictions

Wildfires impose substantial impacts on communities and regions downwind of wildfire smoke. We present a TEMPO‑enabled workflow that generates value‑added Level‑3 smoke‑plume masks and fire‑front maps for large wildfires, such as 2024 Park Fire, using the self‑supervised deep learning system SIT‑FUSE, along with near‑surface NO₂ predictions produced by a foundation model (Microsoft Aurora). We conclude by outlining a roadmap for expanding these capabilities to additional Western U.S. wildfire events and for delivering actionable tools to stakeholders. This open-source, reproducible workflow provides a scalable framework for cross-agency wildfire monitoring to overcome traditional limitations in smoke-cloud discrimination and air-quality forecasting by incorporating TEMPO data and beyond.

Xiaohua Pan↗
NASA NTRS2016

Wildfires Dynamics in Siberian Larch Forests

Wildfire number and burned area temporal dynamics within all of Siberia and along a south-north transect in central Siberia (45deg-73degN) were studied based on NOAA/AVHRR (National Oceanic and Atmospheric Administration/ Advanced Very High Resolution Radiometer) and Terra/MODIS (Moderate Resolution Imaging Spectroradiometer) data and field measurements for the period 1996-2015. In addition, fire return interval (FRI) along the south-north transect was analyzed. Both the number of forest fires and the size of the burned area increased during recent decades (p < 0.05). Significant correlations were found between forest fires, burned areas and air temperature (r = 0.5) and drought index (The Standardized Precipitation Evapotranspiration Index, SPEI) (r = 0.43). Within larch stands along the transect, wildfire frequency was strongly correlated with incoming solar radiation (r = 0.91). Fire danger period length decreased linearly from south to north along the transect. Fire return interval increased from 80 years at 62 N to 200 years at the Arctic Circle (6633' N), and to about 300 years near the northern limit of closed forest stands (about 71+ N). That increase was negatively correlated with incoming solar radiation (r = 0.95). Keywords: wildfires; drought index; larch stands; fire return interval; fire frequency; burned area; climate-induced trends in Siberian wildfires

wildfires↗
NASA NTRS2014

Airborne In-Situ Trace Gas Measurements of Multiple Wildfires in California (2013-2014)

Biomass burning emissions are an important source of a wide range of trace gases and particles that can impact local, regional and global air quality, climate forcing, biogeochemical cycles and human health. In the western US, wildfires dominate over prescribed fires, contributing to atmospheric trace gas budgets and regional and local air pollution. Limited sampling of emissions from wildfires means western US emission estimates rely largely on data from prescribed fires, which may not be a suitable proxy for wildfire emissions.We report here in-situ measurements of carbon dioxide, methane, ozone and water vapor from the plumes of a variety of wildfires sampled in California in the fire seasons of 2013 and 2014. Included in the analysis are the Rim Fire (August October 2013, near Yosemite National Park), the Morgan Fire (September 2013, near Clayton, CA), and the El Portal Fire (July August 2014, in Yosemite National Park), among others. When possible, fires were sampled on multiple days.Emission ratios and estimated emission factors will be presented and discussed in the context of fuel composition, plume structure, and fire phase. Correlations of plume chemical composition to MODISVIIRS Fire Radiative Power (FRP) and other remote sensing information will be explored. Furthermore, the role of plumes in delivery of enhanced ozone concentrations to downwind municipalities will be discussed.

Gas↗
NASA NTRSDate not supplied

Proposition to Optimize Fire Stations for Wildfires

The rising trend in wildfire occurrence and severity has put a strain on wildfire management organizations by spreading out limited resources to meet increasing demand. There has been extensive prior research and data collection to determine the areas of highest risk and to predict regional wildfire damages based on historical trends. Our group aims to utilize this data to best determine fire station placement, optimizing where resources are allocated to reduce the time and investment needed to effectively mitigate wildfires. Using existing research, we are able to calculate optimal fire station locations by utilizing a single-objective facility location problem algorithm incentivized for cost reduction. Further work would be needed to refine the algorithm to accommodate for more realistic factors including access to water and roadways as well as better accounting for the costs involved, but our work serves as a proof of concept and lays the foundation for future research. Implementation of this algorithm would allow public fire planning agencies (such as CAL FIRE and Forest Service) to shift resources to where they would be most effective.

Wildfires↗
NASA NTRSDate not supplied

Hyper-Spectral Infrared Remote Sensing for Wildfire-Related Research and Air Quality Monitoring

The National Airborne Sounder Testbed-Interferometer (NAST-I) is an airborne FTS remote sensor that nominally flies on NASA high-altitude aircraft to serve as a spaceborne instrument simulator. NAST-I continues to serve as a pathfinder for future satellite FTS systems and the next generation advanced atmospheric sounders in general. NAST-I provides high resolution spectrally resolved infrared radiances. NAST-I retrieval products characterizing the surface (i.e., skin temperature and spectral emissivity), atmosphere (i.e., profiles of temperature, moisture, ozone, carbon monoxide, and other trace species), and clouds (e.g., optical depth, particle size, temperature, and height) can be used to support fire-related monitoring and research. NAST-I provided 3-d characterizations of wildfire-induced plumes of CO during the FIREX-AQ field campaign (conducted during 2019) which showed the intensity and size evolution of wildfire plumes at high spatial and temporal resolutions. Wildfire-induced CO plumes, in conjunction with their evolution, transport, and age have been identified and recently published in scientific journals. Other research applications, such as surface emissivity changes due to fire burning of ground landscape, have been under investigation. These products could be used in support of wildfire management to better inform decision making and operations for pre-, active, and post-fire environments.

remote sensing↗
NASA NTRSDate not supplied

Utilizing Advanced Air Mobility Rotorcraft Tools for Wildfire Applications

Over the past decade, due in large part to heavy investment in the field of Advanced Air Mobility (AAM), significant progress in rotorcraft-focused modeling tools has been made. Such progress has notably increased AAM rotorcraft modeling capabilities in the topics of conceptual design, preliminary design, and more recently flight dynamics. Yet, due to recent and persistent increases in extreme weather events, an emerging interest has been raised in utilizing such modeling capabilities for aiding in emergency relief efforts and other public good missions. This paper uses wildfire fighting as a representative public good mission and demonstrates the relevance of the NASA Revolutionary Vertical Lift Technology (RVLT) rotorcraft toolchain to such missions. An emphasis is placed on flight dynamics modeling and control because of the hazards and challenges associated with the atmospheric environment of wildfires. In this work, the NASA FlightCODE tool was used to analyze both a UH-60 and the NASA six-passenger quadcopter reference model hovering in an experimentally informed wildfire turbulent environment. Preliminary results of this study estimate actuator usage exceedances and disturbance rejection capabilities of the vehicles’ translational rate command systems. Leveraging the RVLT toolchain, refinement and expansion of this work could lead to handling qualities envelope estimation and design optimization for wildfire turbulent environments. This would provide pilots with additional information to make real-time decisions in high-risk scenarios and begins preparations for simulating these dangerous environments for pilot training and experimentation.

Rotorcraft↗
NASA NTRSDate not supplied

Utilizing Advanced Air Mobility Rotorcraft Tools for Wildfire Applications

Over the past decade, due in large part to heavy investment in the field of Advanced Air Mobility (AAM), significant progress in rotorcraft-focused modeling tools has been made. Such progress has notably increased AAM rotorcraft modeling capabilities in the topics of conceptual design, preliminary design, and more recently flight dynamics. Yet, due to recent and persistent increases in extreme weather events, an emerging interest has been raised in utilizing such modeling capabilities for aiding in emergency relief efforts and other public good missions. This paper uses wildfire fighting as a representative public good mission and demonstrates the relevance of the NASA Revolutionary Vertical Lift Technology (RVLT) rotorcraft toolchain to such missions. An emphasis is placed on flight dynamics modeling and control because of the hazards and challenges associated with the atmospheric environment of wildfires. In this work, the NASA FlightCODE tool was used to analyze both a UH-60 and the NASA six-passenger quadcopter reference model hovering in an experimentally informed wildfire turbulent environment. Preliminary results of this study estimate actuator usage exceedances and disturbance rejection capabilities of the vehicles’ translational rate command systems. Leveraging the RVLT toolchain, refinement and expansion of this work could lead to handling qualities envelope estimation and design optimization for wildfire turbulent environments. This would provide pilots with additional information to make real-time decisions in high-risk scenarios and begins preparations for simulating these dangerous environments for pilot training and experimentation.

Rotorcraft↗
NASA NTRS2001

Modeling and Prediction of Wildfire Hazard in Southern California, Integration of Models with Imaging Spectrometry

Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated into standard fuel models accessible to the FARSITE fire spread simulator. The FARSITE model and BEHAVE are considered industry standards for fire behavior analysis. Anderson level fuels map, generated using a binary decision tree classifier are available for multiple dates in the Santa Monica Mountains and at least one date for Santa Barbara. Fuel maps that will fill in the areas between Santa Barbara and the Santa Monica Mountains study sites are in progress, as part of a NASA Regional Earth Science Application Center, the Southern California Wildfire Hazard Center. Species-level maps, were supplied to fire managing agencies (Los Angeles County Fire, California Department of Forestry). Research results were published extensively in the refereed and non-refereed literature. Educational outreach included funding of several graduate students, undergraduate intern training and an article featured in the California Alliance for Minorities Program (CAMP) Quarterly Journal.

Roberts, Dar A.↗
NASA NTRS2005

Automated Wildfire Detection Through Artificial Neural Networks

We have tested and deployed Artificial Neural Network (ANN) data mining techniques to analyze remotely sensed multi-channel imaging data from MODIS, GOES, and AVHRR. The goal is to train the ANN to learn the signatures of wildfires in remotely sensed data in order to automate the detection process. We train the ANN using the set of human-detected wildfires in the U.S., which are provided by the Hazard Mapping System (HMS) wildfire detection group at NOAA/NESDIS. The ANN is trained to mimic the behavior of fire detection algorithms and the subjective decision- making by N O M HMS Fire Analysts. We use a local extremum search in order to isolate fire pixels, and then we extract a 7x7 pixel array around that location in 3 spectral channels. The corresponding 147 pixel values are used to populate a 147-dimensional input vector that is fed into the ANN. The ANN accuracy is tested and overfitting is avoided by using a subset of the training data that is set aside as a test data set. We have achieved an automated fire detection accuracy of 80-92%, depending on a variety of ANN parameters and for different instrument channels among the 3 satellites. We believe that this system can be deployed worldwide or for any region to detect wildfires automatically in satellite imagery of those regions. These detections can ultimately be used to provide thermal inputs to climate models.

Miller, Jerry↗
NASA NTRS2008

Operational Experience with Long Duration Wildfire Mapping: UAS Missions Over the Western United States

The National Aeronautics and Space Administration, United States Forest Service, and National Interagency Fire Center have developed a partnership to develop and demonstrate technology to improve airborne wildfire imaging and data dissemination. In the summer of 2007, a multi-spectral infrared scanner was integrated into NASA's Ikhana Unmanned Aircraft System (UAS) (a General Atomics Predator-B) and launched on four long duration wildfire mapping demonstration missions covering eight western states. Extensive safety analysis, contingency planning, and mission coordination were key to securing an FAA certificate of authorization (COA) to operate in the national airspace. Infrared images were autonomously geo-rectified, transmitted to the ground station by satellite communications, and networked to fire incident commanders within 15 minutes of acquisition. Close coordination with air traffic control ensured a safe operation, and allowed real-time redirection around inclement weather and other minor changes to the flight plan. All objectives of the mission demonstrations were achieved. In late October, wind-driven wildfires erupted in five southern California counties. State and national emergency operations agencies requested Ikhana to help assess and manage the wildfires. Four additional missions were launched over a 5-day period, with near realtime images delivered to multiple emergency operations centers and fire incident commands managing 10 fires.

Hall, Philip↗
NASA NTRS2010

High-Volume Airborne Fluids Handling Technologies to Fight Wildfires

NASA recently partnered with the U.S. Forest Service (USFS) on a project to examine mission suitability and recommend policies and procedures for the use of very large aerial firefighting aircraft such as the Boeing 747 and DC-10 aerial retardant delivery aircraft. The aircraft under study included a 10Tanker DC-10 and an Evergreen B-747. NASA's Dryden Flight Research Center and Ames Research Center worked with the USFS to help determine the safe flight envelope for these Very Large Air Tanker (VLAT) aircraft for the USFS and the Department of the Interior (DOI). This new generation of supertankers includes aircraft like these that have as much as four times the delivery capacity of the previous generation of aerial firefighting aircraft. Dryden performed operational test and evaluation assessments and reported findings and recommendations on these aircraft in cooperation with Ames. The team developed, implemented, and directed an evaluation test plan for use in flight test and in simulation. Ames provided support using pilot-in-the-loop simulations and coordinated simulator models, flight profiles, and data analysis with Dryden. The test plan was designed to evaluate the suitability of VLAT aircraft as a function of mission environment. Based on this analysis, NASA generated interim flight envelope limitations to enhance safety and operational utility in the fire-retardant delivery mission. These recommended flight limitations were adopted by the USFS. The 10Tanker DC-10 has been in use for several years with the California Department of Forestry and Fire Protection(Cal-Fire), but until NASA took on the challenge of reviewing VLAT capabilities and limitations, the USFS was hesitant to add them to the federal wildfire arsenal. The DC-10 delivery system is based on an externally mounted set of tanks and a bomb-bay style set of clamshell doors that are opened in precisely calibrated ways to deliver the amounts and concentrations of retardant called for by the specific wildfire situation. The system was manufactured by Jordan Air of Central Point, OR, and was installed by Victorville Aerospace in Victorville, CA. It can deliver 12,000 gallons (45.4 kL) of retardant in as little as eight seconds. The aircraft can deliver a partial load of retardant and make multiple drops on the same flight, or the entire load can be rapidly delivered in one pass if required for maximum coverage. The Evergreen 747 uses internal tankage and a pressurized delivery system to enable volume and coverage levels that also meet USFS requirements, but enables computer control of flow for desired precision. This system was designed and built by Adaptive Aerospace of Tehachapi, CA and can deliver about 20,000 gallons (75.7 kL) of retardant in approximately ten seconds. The 747 can also make multiple independent drops, or deliver the entire load at once. NASA found that both of these VLAT aircraft are compatible with the wildfire suppression mission when used to supplement other aerial retardant delivery platforms. The major recommendations for deployment that resulted from this study relate to terrain clearance, the type of terrain in the drop area, availability of qualified lead planes to guide the VLAT approach to the drop area, and low-altitude maneuvering limitations. NASA s analysis suggests that with the appropriate flight procedures, these aircraft will provide a powerful set of tools to fight wildfires.

Dickerson, Mark↗
NASA NTRS2011

NASA A-Train and Terra Observations of the 2010 Russian Wildfires

Wildfires raged throughout western Russia and parts of Eastern Europe during a persistent heat wave in the summer of 2010. Anomalously high surface temperatures (35 - 41 C) and low relative humidity (9 - 25 %) from mid- June to mid-August 2010 shown by analysis of radiosonde data from multiple sites in western Russia were ideal conditions for the wildfires to thrive. Measurements of outgoing longwave radiation (OLR) from the Atmospheric Infrared Sounder (AIRS) over western Russian indicate persistent subsidence during the heat wave. Daily three-day back-trajectories initiated over Moscow reveal a persistent anticyclonic circulation for 18 days in August, coincident with the most intense period of fire activity observed by Moderate Resolution Imaging Spectroradiometer (MODIS). This unfortunate meteorological coincidence allowed transport of polluted air from the region of intense fires to Moscow and the surrounding area. We demonstrate that the 2010 Russian wildfires are unique in the record of observations obtained by remote-sensing instruments on-board NASA satellites: Aura and Aqua (part of the A-Train Constellation) and Terra. Analysis of the distribution of MODIS fire products and aerosol optical thickness (AOT), UV aerosol index (AI) and single-scattering albedo (SSA) from Aura's Ozone Monitoring Instrument (OMI), and total column carbon monoxide (CO) from Aqua s Atmospheric Infrared Sounder (AIRS) show that the region in the center of western Russia surrounding Moscow (52-58 deg N, 33 -43 deg E) is most severely impacted by wildfire emissions. Over this area, AIRS CO, OMI AI, and MODIS AOT are significantly enhanced relative to the historical satellite record during the first 18 days in August when the anti-cyclonic circulation persisted. By mid-August, the anti-cyclonic circulation was replaced with westerly transport over Moscow and vicinity. The heat wave

Witte, J. C.↗
NASA NTRS2013

Polarimetric and Multi-Doppler Radar Observations of Electrified and Unelectrified Wildfire Smoke Plumes

Pyrocumulus clouds above three Colorado wildfires (Hewlett Gulch, High Park, and Waldo Canyon; all occurred during summer 2012) electrified and produced small intracloud discharges whenever the smoke plumes grew to high altitudes (over 10 km above mean sea level, or MSL). This occurred during periods of rapid wildfire growth, as indicated by the shortwave infrared channel on a geostationary satellite, as well as by incident reports. In the Hewlett Gulch case, the fire growth led to increased updrafts within the plume, as inferred by multiple‐ Doppler radar syntheses, which led to the vertical development and subsequent electrification ‐ a life cycle as short as 30 minutes. The lightning, detected by a threedimensional lightning mapping network, was favored in high‐altitude regions (~10 km MSL) containing modest reflectivities (25 dBZ and lower), ~0 dB differential reflectivity, and reduced correlation coefficient (~0.6‐0.7). This indicated the likely presence of ice particles (crystals and aggregates, possibly rimed) mixed with ash. Though neither multiple‐Doppler nor polarimetric observations were available during the electrification of the High Park and Waldo Canyon plumes, their NEXRAD observations showed reflectivity structures consistent with Hewlett Gulch. In addition, polarimetric and multiple‐Doppler scanning of unelectrified High Park plumes indicated only irregularly shaped ash, and not ice, was present (i.e., reflectivities < 25 dBZ, differential reflectivity > 5 dB, correlation < 0.4), and there was no broaching of the 10 km altitude. Based on these results, the electrification likely was caused by ice‐based processes that did not involve significant amounts of graupel. The results demonstrate the scientific value of multiple‐Doppler and polarimetric radar observations of wildfire smoke plumes ‐ including the ability to distinguish between regions of pure hydrometeors, regions of pure ash, and mixtures of both ‐ and also suggest a possible new application for lightning data in monitoring wildfires.

Lang, Timothy J.↗
NASA NTRS2014

Soot Superaggregates from Flaming Wildfires and Their Direct Radiative Forcing

Wildfires contribute significantly to global soot emissions, yet their aerosol formation mechanisms and resulting particle properties are poorly understood and parameterized in climate models. The conventional view holds that soot is formed via the cluster-dilute aggregation mechanism in wildfires and emitted as aggregates with fractal dimension D(sub f) approximately equals 1.8 mobility diameter D(sub m) (is) less than or equal to 1 micron, and aerodynamic diameter D(sub a) (is) less than or equal to 300 nm. Here we report the ubiquitous presence of soot superaggregates (SAs) in the outflow from a major wildfire in India. SAs are porous, low-density aggregates of cluster-dilute aggregates with characteristic D(sub f) approximately equals 2.6,D(sub m) (is) greater than 1 micron, and D(sub a) is less than or equal to 300 nm that form via the cluster-dense aggregation mechanism.We present additional observations of soot SAs in wildfire smoke-laden air masses over Northern California, New Mexico, and Mexico City. We estimate that SAs contribute, per unit optical depth, up to 35% less atmospheric warming than freshly-emitted (D(sub f) approximately equals 1.8) aggregates, and approximately equals 90% more warming than the volume-equivalent spherical soot particles simulated in climate models.

SAS↗
NASA NTRS2018

The Sensitivity of US Wildfire Occurrence to Pre-Season Soil Moisture Conditions Across Ecosystems

It is well accepted that drought and low moisture conditions are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state has been challenging due to a lack of soil moisture observations at an appropriate spatial scale. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission, combined in a predictive algorithm with the US Forest Service’s Fire-Occurrence Database. We estimate a relationship between historic surface moisture and wildfire occurrence to produce annual probable wildfire occurrence and burned area at 0.25-degree resolution for the contiguous United States by land-cover classification. Cross-validation indicates increased frequency of smaller fires when the months preceding fire season are wet, while larger fires are more frequent when soils are dry. This demonstrates that assimilated GRACE data holds information that could aid national-scale fire potential assessments for early decision-support.

Fire-Occurrence database↗
NASA NTRS2019

Four Years of Airborne Measurements of Wildfire Emissions in California, with a Focus on the Evolution of Emissions During the Soberanes Megafire

Biomass burning is an important source of trace gases and particles which can influence air quality on local, regional, and global scales. With wildfire events increasing due to changes in land use, increasing population, and climate change, characterizing wildfire emissions and their evolution is vital. In this work we report in situ airborne measurements of carbon dioxide (CO2), methane (CH4), water vapor (H2O), ozone (O3), and formaldehyde (HCHO) from nine wildfire events in California between 2013 and 2016, which were sampled as part of the Alpha Jet Atmospheric eXperiment (AJAX) based at NASA Ames Research Center. One of those fires, the Soberanes Megafire, began on 22 July 2016 and burned for three months. During that time, five flights were executed to sample emissions near and downwind of the Soberanes wildfire. In situ data are used to determine enhancement ratios (ERs), or excess mixing ratio relative to CO2, as well as assess O3 production from the fire. Changes in the emissions as a function of fire evolution are explored. Air quality impacts downwind of the fire are addressed using ground-based monitoring site data, satellite smoke products, and the Community Multiscale Air Quality (CMAQ) photochemical grid model.

Iraci, Laura T.↗