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Long-range Transport of Siberian Biomass Burning Emissions to North America During FIREX-AQ

Biomass burning from wildfires is a significant global source of aerosol and trace gases which impact air quality, tropospheric and stratospheric composition, and climate. During the summer of 2019, wildfire activity in central and eastern Siberia occurred during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign conducted between July 24 and September 6, 2019. Ground-based lidar observations from the Autonomous Mobile Ozone Lidar for Tropospheric Experiments (AMOLITE) system in Alberta, Canada retrieved frequent anomalous ozone (O3) and aerosol lamina in the troposphere and lower stratosphere during this campaign. Data from NASA’s GEOS Composition Forecast (GEOS-CF) coupled chemistry meteorology model, TROPOspheric Monitoring Instrument (TROPOMI), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), and ground-based insitu data were used to define the trans-Pacific and trans-Arctic transport pathway of Siberian biomass burning emissions resulting in the enhanced O3 and aerosol lamina observed by AMOLITE in western Canada. Siberian wildfires impacted North American air quality resulting in enhancements of hourly-averaged surface carbon monoxide (CO) (total CO >150 ppb) and fine particulate matter (PM2.5) (>20 μg m-3) in western Canada, however, minimal increases in surface-level O3 were measured as well as modeled by GEOS-CF. The impact in western Canada due to Siberian wildfires was much larger in the free troposphere, demonstrated by GEOS-CF and AMOLITE O3 lamina 30–40 ppb above background values and model-predicted PM2.5 lamina >30 μg m-3. In addition to tropospheric composition effects, the large wildfire activity in Siberia may have influenced the stratosphere as data from AMOLITE, CALIPSO, and GEOS-CF all suggested aerosol layers from the fires were located 13–18 km above ground level (agl). This study shows that the Siberian biomass burning emissions in the summer of 2019 impacted tropospheric/stratospheric composition in western Canada, and potentially could have influenced areas in the vicinity of FIREX-AQ airborne measurements, and future studies of FIREX-AQ chemical composition should consider how this long-range transport could have influenced the background trace gas and aerosol concentrations being investigated.

Biomass↗

Leveraging NASA Soil Moisture Active Passive for Assessing Fire Susceptibility and Potential Impacts over Australia and California

Wildfires are a major concern around the globe because of the immediate impact they have on people's lives, local ecosystems, and the environment. Soil moisture is one of the most important factors that influences wildfire occurrences and spread. However, it is also one of the most challenging hydrological variables to measure routinely and accurately. Therefore, soil moisture is significantly underutilized in operational wildfire risk applications. Thus, the aim here is to use a well-established operational soil moisture product to isolate the soil moisture-fire relationship and assess the utility of using soil moisture as a leading indicator of potential fire risk. We evaluated the value of remotely-sensed soil moisture observations from the Soil Moisture Active Passive (SMAP) sensor for monitoring and predicting fire risk in Australia and California. We quantified the relationship between observed fire activity and soil moisture conditions and analyzed the soil moisture conditions for two extreme fire events. Our findings show that fire activity is strongly associated with soil moisture anomalies. Lagged correlation analysis demonstrated that a remote-sensing based soil moisture product could predict fire activity with a 1-2 month lead-time. Soil moisture anomalies consistently decreased in the months preceding fire occurrence, often from normal to drier conditions, according to a spatiotemporal analysis of soil moisture in two extreme fire events. Overall, our findings indicate that soil moisture conditions prior to large wildfires can aid in their prediction and operational satellite-based soil moisture products such as the one used here have real value for supporting wildfire susceptibility and impacts.

Nazmus Sazib↗

Source and Variability of Formaldehyde (HCHO) at Northern High Latitude: an Integrated Satellite, Aircraft, and Model Study

Here we use satellite observations of formaldehyde (HCHO)vertical column densities (VCD) from the TROPOspheric Monitoring Instrument (TROPOMI), aircraft measurements, combined with a nested regional chemical transport model (GEOS-Chem at 0.5°×0.625° resolution), to understand the variability and sources of summertime HCHO better in Alaska. We first evaluate GEOS-Chem with in-situ airborne measurements during Atmospheric Tomography Mission 1 (ATom-1) aircraft campaign. We show reasonable agreement between observed and modeled HCHO, isoprene, monoterpenes and the sum of methyl vinyl ketone and methacrolein (MVK+MACR) in continental boundary layer. In particular, HCHO profiles show spatial homogeneity in Alaska, suggesting a minor contribution of biogenic emissions to HCHO VCD. We further examine the TROPOMI HCHO product in Alaska summer, reprocessed by GEOS-Chem model output for a priori profiles and shape factors. For the year with low wildfire activity (e.g.,2018), we find that HCHO VCDs are largely dominated by background HCHO (58-71%), with minor contributions from wildfires (20-32%) and biogenic VOC emissions (8-10%). For the year with intense wildfires (e.g.,2019), summertime HCHO VCD is dominated by wildfire emissions (50-72%), with minor contributions from background (22-41%) and biogenic VOCs (6-10%). In particular, the model indicates a major contribution of wildfires from direct emissions of HCHO, instead of secondary production of HCHO from oxidation of larger VOCs. We find that the column contributed by biogenic VOC is often small and below the TROPOMI detection limit, in part due to the slow HCHO production from isoprene oxidation under low NOx conditions. This work highlights challenges for quantifying HCHO and its precursors in remote pristine regions.

HCHO↗

Córdoba Wildland Fires: Assessing Fire Risk Factors in Córdoba, Argentina using Earth Observations

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 (WUI), and inadequate fire management practices. Previous studies have produced fire frequency maps for the region, but gaps remain in understanding the environmental parameters influencing fire behavior and growth. We partnered with the Instituto Nacional de Tecnología Agropecuaria (INTA) to address these gaps by utilizing NASA Earth observing data 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), we created a ten-year baseline using environmental variables to determine anomalies that influenced the fires of 2020. Baseline data were used to calculate the statistical significance of the environmental factors as precursors to wildfires. We found that the normalized difference vegetation index (NDVI) and precipitation were the strongest indicators for the September 2020 wildfires. Using the environmental risk factors, we created a wildfire risk map for the province of Córdoba, which can be used to enhance our partner’s fire management strategies and decision-making processes.

wildland fires↗

Understanding Changes in Modeled Land Surface Characteristics Prior to Lightning-Initiated Holdover Fire Breakout

Lightning initiated wildfires are only 16% of the total number of wildfires within the United States, but account for 56% of the acreage burned. One of the challenges with lightning-initiated wildfires is their ability to "holdover" which means smolder for up to 2+ weeks before breaking out into a full fledged fire. This work helps characterize the percentage of holdover events due to lightning, and helps quantify changes in the land surface characteristics to help understand trends in soil moisture and vegetation stress that potentially contribute to the fire breaking out into a full wildfire.

wildfire↗

On the Electrification of Pyrocumulus Clouds

The electrification (or lack thereof) of pyrocumulus clouds is examined for several different wildfires that occurred during 2012‐2013. For example, 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 three‐dimensional 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. Results for pyrocumulus clouds above notable 2013 wildfires that also experienced rapid growth (e.g., Black Forest, Yarnell Hill, West Fork, Tres Lagunas, etc.) will be compared against the 2012 cases, with special emphasis on polarimetric NEXRAD and available lightning measurements, in order to better understand the physical processes responsible for pyrocumulus electrification.

Lang, Timothy J.↗

The gathering firestorm in southern Amazonia

Wildfires, exacerbated by extreme weather events and land use, threaten to change the Amazon from a net carbon sink to a net carbon source. Here, we develop and apply a coupled ecosystem-fire model to quantify how greenhouse gas–driven drying and warming would affect wildfires and associated CO2 emissions in the southern Brazilian Amazon. Regional climate projections suggest that Amazon fire regimes will intensify under both low- and high-emission scenarios. Our results indicate that projected climatic changes will double the area burned by wildfires, affecting up to 16% of the region’s forests by 2050. Although these fires could emit as much as 17.0 Pg of CO2 equivalent to the atmosphere, avoiding new deforestation could cut total net fire emissions in half and help prevent fires from escaping into protected areas and indigenous lands. Aggressive efforts to eliminate ignition sources and suppress wildfires will be critical to conserve southern Amazon forests.

P. M. Brando↗

The System Modeling and Analysis of Resiliency in STEReO (SMARt-STEReO)

Wildfire emergency response has remained rooted in relatively low-tech solutions for coordination between ground and aerial assets. These low-tech solutions are robust for the remote environments in which wildfires are usually fought, but limit strategic cross-organizational support and the ability to deploy and effectively utilize aerial assets. As aircraft become more advanced and new technology, including drones, become available to firefighters, a new, more modern method of asset coordination is needed. NASA is working on a project called ‘Scalable Traffic Management for Emergency Response Operations’ (STEReO) to integrate unmanned aerial systems (UAS)and UAS traffic management (UTM)into wildfire response. STEReO’s goals include simplifying the coordination of aerial assets, improving the existing UAS framework, and increasing the role of additional autonomous systems to reduce human risk and to increase system resilience. This paper describes the development of the ‘System Modeling and Analysis of Resiliency in STEReO’ (SMARt-STEReO) project, which aims to model wildfire response and to quantify the additional system resilience that STEReO technology provides firefighters. This paper verifies SMARt-STEReO and defines its scope; it includes experimental and statistical analysis of the impact that the addition of UAS has on both performance metrics and also on performance resiliency response to a given fault. SMARt-STEReO is a grid-based model of fire propagation that incorporates varying crew responses. Through the use of a Python package called ‘fmdtools’, the model easily allows for the addition of faults to the system. These faults allow analysts to investigate various response parameters. Factors including terrain, fuel type and wind speed can be modified to affect the fire propagation; additionally, the number of ground crews, engines, fixed wing aircraft, helicopters, and UAS can be changed to affect the crew response. The communication lines between actors mimic those used in real life situations. This paper explains the development of SMARt-STEReO including background research, verification and validation, and preliminary experimental analysis of system resilience to both a minor and major fault in systems with and without UAS.

Resiliency↗

Marin County Wildland Fires: Examining Fuel Load and Land Cover Change to Inform Fire Prevention and Suppression Decisions in Marin County, CA

Heightened occurrence of severe wildfires in the Western United States is increasing the need to better understand regions of high potential wild fire severity and develop methodologies for identifying the best locations for fuels reduction and active wildfire suppression, especially in populated regions such as Marin County, California. Marin County, located in the San Francisco Bay Area, has had significant development in the wildland-urban interface and periods of highly wildfire-prone conditions. The NASA DEVELOP team collaborated with Fire Foundry, a Marin-based fire service work force development program, to develop new models to assist with fire management. Using data from Sentinel-2A, Planet Scope, ECOSTRESS, a county-wide LiDAR mapping effort, Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI), the team developed several input data layers to three models evaluating wild fire severity. One model performed a suitability analysis with weights based on scientific literature, another utilized machine learning based on past fires in Marin and neighboring Sonoma County to predict the difference normalized burn ratio, and the third inputted data layers into the Flam Map tool, which outputs risk categories. The team compared model outputs and, using the best-fit model, performed fuzzy logic analysis to identify specific locations where a fire break could be constructed to interrupt the progress of an active fire. These tools were proven useful and will assist partners in preparing for and managing an active wildfire event.

Suhani Dalal↗

Creating Gridded Fire Probability Maps using NASA Data

Fire is a nationally and globally significant process that strongly affects human–dominated and wild landscapes. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes, providing value by decreasing fuels at the Wildland Urban Interface (WUI) to promote safe communities. However, uncontained wildfires can devastate communities, threaten our health, and result in substantial economic losses. There has been greater than a $50B increase in wildfire insurance claims from 2017-2021, which has been exacerbated by climate change. Our partners at Kettle reinsurance are focused on building a smarter reinsurance model for protecting today’s globalized world from the catastrophic effects of climate change. Our objective is to develop the world's first grid-based wildfire probability product using multiple sources of satellite data to determine whether a ‘conflagration' (fire larger than 999+ acres) has ‘breached’ a grid cell. This will substantially decrease the time it takes for homeowners to receive payouts, from over a year to a couple months. Working with our partners at Kettle reinsurance, we use multiple satellites and ancillary data to weigh the likelihood of fire, based on a number of sources that verify a fire burning in a grid cell and the level of confidence in the data source. For example, Sentinel-2 vegetation-change indices have a higher level of confidence than VIIRS (Visible Infrared Imaging Radiometer Suite) active-fire detection data; and VIIRS active-fire detection data have a higher-level of confidence than MODIS (Moderate Resolution Imaging Spectroradiometer) active-fire detection data. The first iteration has been developed for responding to wildfires in California, with the possibility to expand nationwide and globally.

Emily Gargulinski↗

Creating IR-verified Gridded Fire Burn Maps using Public NASA and Satellite Data

Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes, providing value by decreasing fuels at the Wildland Urban Interface (WUI) to promote safe communities. However, uncontained wildfires can devastate communities, threaten our health, and result in substantial economic losses. There has been greater than a $50B increase in wildfire insurance claims from 2017-2021, which has been exacerbated by climate change. Our partners at Kettle reinsurance are focused on building a smarter reinsurance model for protecting today’s globalized world from the catastrophic effects of climate change. Our objective is to develop a high-confidence grid-based wildfire burn product using multiple sources of satellite data to determine whether a ‘conflagration' (fire larger than 999+ acres) has ‘breached’ a grid cell. This product will substantially decrease the time it takes for homeowners to receive payouts, from over a year to a couple months. Working with our partners at Kettle reinsurance, we use VIIRS (Visible Infrared Imaging Radiometer Suite) 375 m fire detections and Sentinel-2 10 m satellite imagery to create a 20-m gridded fire burn product. Our process is based on the level of confidence in the data source and takes into account vegetation change throughout the life of the fire. For example, Sentinel-2 vegetation-change indices have a higher level of confidence when congruent with VIIRS active-fire detection data, rather than VIIRS detections alone. We have also verified our fire burn product against MODIS/ASTER Airborne Simulator (MASTER) Infrared (IR) data from the Fire Influence on Regional to Global Environments Experiment - Air Quality (FIREX-AQ) 2019 campaign, with 88% overall agreement. The first iteration has been developed for responding to wildfires in California, with the possibility to expand nationwide and globally.

Emily Gargulinski↗

Nevada Wildland Fires: Mapping Historical Burned Areas and Identifying Drivers of Fuel Load Growth to Inform Desert Tortoise Habitat Management in Southern Nevada

Wildfire frequency and intensity in the Mojave desert are increasing, driven by invasive grasses that outcompete native vegetation not well-adapted to wildfire. These grasses, primarily cheatgrass (Bromus tectorum) and red brome (Bromus rubens), and the wildfires that occur when the grasses ignite, are a serious threat to the critically endangered Mojave desert tortoise (Gopherus agassizii). Declining Mojave desert tortoise populations are of great concern to project partners, the Bureau of Land Management Southern Nevada District Office, the US Forest Service’s Rocky Mountain Research Station, and the US Department of Agriculture Agricultural Research Service’s Arid Lands Ecology Lab, who currently lack the resources for fire recovery studies essential for informed fire and invasive grass management. To address this gap, the team utilized NASA Earth observations including Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Terra MODIS, Landsat 5 Thematic Mapper (TM), and Landsat 8 Operational Land Imager (OLI), to analyze trends in burned areas over the past 20 years through historic burn maps and to examine fuel load growth drivers, with a focus on invasive vegetation. These historical burn maps revealed a pattern of precipitation anomalies that strongly correlate with higher Normalized Difference Vegetation Index (NDVI) values. Years with significant precipitation and NDVI spikes led to greater fuel load in the dry season and larger burns. Additionally, El Niño years correlated significantly with precipitation anomalies which may provide our partners with insights into burn trends and enable better allocation of fuel load treatment practices. However, while identifying drivers of fuel load growth proved feasible, a lack of in situ data hindered attempts to analyze pre-fire growth of invasive grasses compared with native grasses. Despite this limitation, the project demonstrated the feasibility of using Earth observations for wildfire and habitat management, ultimately benefiting conservation efforts for the Mojave desert tortoise.

fuel load↗

Ten Years of Forest Cover Change in the Sierra Nevada Detected Using Landsat Satellite Image Analysis

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in forest vegetation cover for areas burned by wildfires in the Sierra Nevada Mountains of California between the periods of 1975- 79 and 1995-1999. Results for areas burned by wildfire between 1995 and 1999 confirmed the importance of regrowing forest vegetation over 17% of the combined burned areas. A notable fraction (12%) of the entire 5-km (unburned) buffer area outside the 1995-199 fires perimeters showed decline in forest cover, and not nearly as many regrowing forest areas, covering only 3% of all the 1995-1999 buffer areas combined. Areas burned by wildfire between 1975 and 1979 confirmed the importance of disturbed (or declining evergreen) vegetation covering 13% of the combined 1975- 1979 burned areas. Based on comparison of these results to ground-based survey data, the LEDAPS methodology should be capable of fulfilling much of the need for consistent, low-cost monitoring of changes due to climate and biological factors in western forest regrowth following stand-replacing disturbances.

Vegetation↗

Satellite-Based Assessment of Grassland Conversion and Related Fire Disturbance in the Kenai Peninsula, Alaska

Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has heightened local wildfire risk as canopy loss facilitates the conversion from bare to fire-prone grassland. We collected images from NASA satellite-based Earth observations to visualize land cover succession at roughly five-year intervals following a severe, mid-1990's beetle infestation to the present. We classified these data by vegetation cover type to quantify grassland encroachment patterns over time. Raster band math provided a change detection analysis on the land cover classifications. Results indicate the highest wildfire risk is linked to herbaceous and black spruce land cover types, The resulting land cover change image will give the Kenai National Wildlife Refuge (KENWR) ecologists a better understanding of where forests have converted to grassland since the 1990s. These classifications provided a foundation for us to integrate digital elevation models (DEMs), temperature, and historical fire data into a model using Python for assessing and mapping changes in wildfire risk. Spatial representations of this risk will contribute to a better understanding of ecological trajectories of beetle-affected landscapes, thereby informing management decisions at KENWR.

Risk modeling↗

Satellite-Based Assessment of Grassland Conversion and Related Fire Disturbance in the Kenai Peninsula, Alaska

Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has been hypothesized by local ecologists to result in the conversion of forest to grassland and subsequent increased fire danger. This hypothesis stands in contrast to empirical studies in the continental US which suggested that beetle mortality has only a negligible effect on fire danger. In response, we conducted a study using Landsat data and modeling techniques to map land cover change in the Kenai Peninsula and to integrate change maps with other geospatial data to predictively map fire danger for the same region. We collected Landsat imagery to map land cover change at roughly five-year intervals following a severe, mid-1990s beetle infestation to the present. Landcover classification was performed at each time step and used to quantify grassland encroachment patterns over time. The maps of land cover change along with digital elevation models (DEMs),temperature, and historical fire data were used to map and assess wildfire danger across the study area. Results indicate the highest wildfire danger tended to occur in herbaceous and black spruce land cover types, suggesting that the relationship between spruce beetle damage and wildfire danger in costal Alaskan forested ecosystems differs from the relationship between the two in the forests of the coterminous United States. These change detection analyses and fire danger predictions provide the Kenai National Wildlife Refuge (KENWR) ecologists and other forest managers a better understanding of the extent and magnitude of grassland conversion and subsequent change in fire danger following the 1990s spruce beetle outbreak.

wildfire↗

Evaluation of Novel NASA MODIS and VIIRS Aerosol Products and Assessment of Smoke Height Boundary Layer Ratio During Extreme Smoke Events in the Western U.S.

We analyze new aerosol products from NASA satellite retrievals over the western U.S. during August 2013, with special attention to locally generated wildfire smoke and downwind plume structures. Aerosol optical depth (AOD) at 550 nm from MODIS (Terra and Aqua Collections 6 and 6.1) and VIIRS Deep Blue (DB) and MODIS (Terra and Aqua) Multi‐Angle Implementation of Atmospheric Correction (MAIAC) retrievals are evaluated against ground‐based AErosol RObotic NETwork (AERONET) observations. We find a significant improvement in correlation with AERONET and other metrics in the latest DB AOD (MODIS C6.1 r^2=0.75, VIIRS r^2=0.79) compared to MODIS C6 (r2=0.62). In general, MAIAC (r^2=0.84) and DB (MODIS C6.1 and VIIRS) present similar statistical evaluation metrics for the western U.S. and are useful tools to characterize aerosol loading associated with wildfire smoke. We also evaluate three novel NASA MODIS plume injection height (PIH) products, one from MAIAC and two from the Aerosol Single scattering albedo and layer Height Estimation (ASHE) (MODIS and VIIRS) algorithm. Both Terra and Aqua MAIAC PIHs statistically agree with ground‐based and satellite lidar observations near the fire source, as do ASHE, although the latter is sensitive to assumptions about aerosol absorption properties. We introduce a first‐order approximation Smoke Height Boundary Layer Ratio (SHBLR) to qualitatively distinguish between aerosol pollution within the planetary boundary layer and the free troposphere. We summarize the scope, limitations, and suggestions for scientific applications of surface level aerosol concentrations specific to wildfire emissions and smoke plumes using these novel NASA MODIS and VIIRS aerosol products.

Plume injection height↗

Estimation of Fire-induced CO Plume Age from NAST-I During the FIREX-AQ Field Campaign

Ultra-spectrally resolved infrared measurements from aircraft and space-based observations contain information about tropospheric carbon monoxide (CO) and ozone (O3), as well as other trace species. A methodology for retrieving these tropospheric trace species from such remotely sensed spectral data has been developed and validated for the National Airborne Sounder Testbed-Interferometer (NAST–I). The Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign was conducted during August 2019 to investigate the impact of wildfire and biomass smoke on air quality and weather in the continental United States. NAST–I CO and O3 measurements from the recent FIREX-AQ field campaign are presented and used to estimate wildfire plume age. Results show enhanced levels of CO in the evolving plume as it is transported away from the fire ground site, and its plume age is associated with the plume distance in both the vertical and horizontal directions from the wildfire location. These results are enabled by the moderate-vertical and high-horizontal resolution obtained from the NAST–I IR spectrometer onboard the NASA ER-2 aircraft. This study advances our knowledge of fire-induced plumes with their evolution and age characterized in three-dimensional space using information from NAST–I retrieved CO and O3 and relative changes in their concentrations.

plume age↗

Ad-Hawk Aerial Connectivity Network: An Integrated and Empirical System Evaluation

Wildfires in the United States have been increasing significantly in both frequency and size in recent decades, requiring unprecedented resource and communication efficiency on the part of wildfire management organizations. However, while the methodology and technology to combat wildfires have improved, the connectivity infrastructure in rural regions of the country is either incompatible with newer technology or altogether non-existent. Due to this, many modern communication methods are rendered useless in areas where a connection is needed most, complicating the overall fire management procedure. To improve communication and logistics between responders on the front lines and headquarters, a team of NASA research associates has developed the schematic for a rapidly deployable mobile ad-hoc internet-enabled Wi-Fi network that can bring stable internet access to any desired area. This paper contains the testing and analysis of the Ad-Hawk project conceived in the summer of 2022 and developed in the summer of 2023.

Wildfire↗