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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Global Characterization of Biomass-Burning Patterns using Satellite Measurements of Fire Radiative Energy

Remote sensing is the most practical means of measuring energy release from large open-air biomass burning. Satellite measurement of fire radiative energy (FRE) release rate or power (FRP) enables distinction between fires of different strengths. Based on a 1-km resolution fire data acquired globally by the MODerate-resolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites from 2000 to 2006, instanteaneous FRP values ranged between 0.02 MW and 1866 MW, with global daily means ranging between 20 and 40 MW. Regionally, at the Aqua-MODIS afternoon overpass, the mean FRP values for Alaska, Western US, Western Australia, Quebec and the rest of Canada are significantly higher than these global means, with Quebec having the overall highest value of 85 MW. Analysis of regional mean FRP per unit area of land (FRP flux) shows that a peak fire season in certain regions, fires can be responsible for up to 0.2 W/m(sup 2) at peak time of day. Zambia has the highest regional monthly mean FRP flux of approximately 0.045 W/m(sup 2) at peak time of day and season, while the Middle East has the lowest value of approximately 0.0005 W/m(sup 2). A simple scheme based on FRP has been devised to classify fires into five categories, to facilitate fire rating by strength, similar to earthquakes and hurricanes. The scheme uses MODIS measurements of FRP at 1-km resolution as follows: catagory 1 (less than 100 MW), category 2 (100 to less than 500 MW), category 3 (500 to less than 1000 MW), category 4 (1000 to less than 1500 MW), catagory 5 (greater than or equal to 1500 MW). In most regions of the world, over 90% of fires fall into category 1, while only less than 1% fall into each of categories 3 to 5, although these proportions may differ significantly from day to day and by season. The frequency of occurence of the larger fires is region specific, and could not be explained by ecosystem type alone. Time-series analysis of the propertions of higher category fires based on MODIS measured FRP from 2002 to 2006 does not show any moticeable trend because of the short time period.

Ichoku, Charles↗
NASA NTRS2007

Multiple-Parameter, Low-False-Alarm Fire-Detection Systems

Fire-detection systems incorporating multiple sensors that measure multiple parameters are being developed for use in storage depots, cargo bays of ships and aircraft, and other locations not amenable to frequent, direct visual inspection. These systems are intended to improve upon conventional smoke detectors, now used in such locations, that reliably detect fires but also frequently generate false alarms: for example, conventional smoke detectors based on the blockage of light by smoke particles are also affected by dust particles and water droplets and, thus, are often susceptible to false alarms. In contrast, by utilizing multiple parameters associated with fires, i.e. not only obscuration by smoke particles but also concentrations of multiple chemical species that are commonly generated in combustion, false alarms can be significantly decreased while still detecting fires as reliably as older smoke-detector systems do. The present development includes fabrication of sensors that have, variously, micrometer- or nanometer-sized features so that such multiple sensors can be integrated into arrays that have sizes, weights, and power demands smaller than those of older macroscopic sensors. The sensors include resistors, electrochemical cells, and Schottky diodes that exhibit different sensitivities to the various airborne chemicals of interest. In a system of this type, the sensor readings are digitized and processed by advanced signal-processing hardware and software to extract such chemical indications of fires as abnormally high concentrations of CO and CO2, possibly in combination with H2 and/or hydrocarbons. The system also includes a microelectromechanical systems (MEMS)-based particle detector and classifier device to increase the reliability of measurements of chemical species and particulates. In parallel research, software for modeling the evolution of a fire within an aircraft cargo bay has been developed. The model implemented in the software can describe the concentrations of chemical species and of particulate matter as functions of time. A system of the present developmental type and a conventional fire detector were tested under both fire and false-alarm conditions in a Federal Aviation Administration cargo-compartment- testing facility. Both systems consistently detected fires. However, the conventional fire detector consistently generated false alarms, whereas the developmental system did not generate any false alarms.

Hunter, Gary W.↗
NASA NTRS2011

Persistent Effects of Fire Severity on Early Successional Forests in Interior Alaska

There has been a recent increase in the frequency and extent of wildfires in interior Alaska, and this trend is predicted to continue under a warming climate. Although less well documented, corresponding increases in fire severity are expected. Previous research from boreal forests in Alaska and western Canada indicate that severe fire promotes the recruitment of deciduous tree species and decreases the relative abundance of black spruce (Picea mariana) immediately after fire. Here we extend these observations by (1) examining changes in patterns of aspen and spruce density and biomass that occurred during the first two decades of post-fire succession, and (2) comparing patterns of tree composition in relation to variations in post-fire organic layer depth in four burned black spruce forests in interior Alaska after 10-20 years of succession.Wefound that initial effects of fire severity on recruitment and establishment of aspen and black spruce were maintained by subsequent effects of organic layer depth and initial plant biomass on plant growth during post-fire succession. The proportional contribution of aspen (Populus tremuloides) to total stand biomass remained above 90% during the first and second decades of succession in severely burned sites, while in lightly burned sites the proportional contribution of aspen was reduced due to a 40- fold increase in spruce biomass in these sites. Relationships between organic layer depth and stem density and biomass were consistently negative for aspen, and positive or neutral for black spruce in all four burns. Our results suggest that initial effects of post-fire organic layer depths on deciduous recruitment are likely to translate into a prolonged phase of deciduous dominance during post-fire succession in severely burned stands. This shift in vegetation distribution has important implications for climate-albedo feedbacks, future fire regime, wildlife habitat quality and natural resources for indigenous subsistence activities in interior Alaska.

Shenoy, Aditi↗
NASA NTRS2011

Mapping Canopy Damage from Understory Fires in Amazon Forests Using Annual Time Series of Landsat and MODIS Data

Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in separating burning from other types of forest damage in satellite data. We developed a new approach, the Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was applied to time series of Landsat (1997-2004) and MODIS (2000-2005) data covering one Landsat scene (path/row 226/068) in southern Amazonia and the results were compared to field observations, image-derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was essential for detection of burn scars less than 50 ha, yet these small burns contributed only 12% of all burned forest detected during 1997-2002. MODIS data were suitable for mapping medium (50-500 ha) and large (greater than 500 ha) burn scars that accounted for the majority of all fire-damaged forest in this study. Therefore, moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508 square kilometers) were an order of magnitude higher than during the 1997-1998 El Nino event (124 square kilometers and 39 square kilometers, respectively), suggesting a different link between climate and understory fires than previously reported for other Amazon regions. The results in this study illustrate the potential to address critical questions concerning climate and fire risk in Amazon forests by applying the BDR algorithm over larger areas and longer image time series.

Morton, Douglas C.↗
NASA NTRS2013

Integrated Active Fire Retrievals and Biomass Burning Emissions Using Complementary Near-Coincident Ground, Airborne and Spaceborne Sensor Data

Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

airborne scanner↗
NASA NTRS2017

Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar

Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaskas Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broad leaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from above ground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity from Landsat.

Alonzo, Michael↗
NASA NTRSDate not supplied

Quantifying Post-fire Vegetation Recovery on the Colorado Front Range

Forest composition and structure in the Colorado Front Range has been altered by changing wildfire regimes, particularly in response to increased fire severity. Subsequent reductions in post-fire tree regeneration can result in chronic impacts to ecological function and water quality. This project partnered with the U.S. Forest Service to estimate tree canopy recovery from 15 to 21 years after four Colorado Front Range fires that burned between 1996 and 2002— the Bobcat, Buffalo Creek, Hayman, and High Meadows fires—using Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI). First, we evaluated relationships between recovery metrics derived from spectral vegetation indices (i.e. post-fire vegetation, normalized burn ratio, percent unrecovered vegetation) and field-collected counts of post-fire tree seedling regeneration. Then, we used high-resolution imagery paired with Landsat timeseries spectral and geomorphometric data to map forest canopy cover 15-21 years post-fire. Finally, we assessed ecological drivers of recovery including topography, climate, soils, and fire severity using Random Forest. While we found that basic vegetation index metrics failed to distinguish field-measured tree regeneration, our data showed that both aspect and burn severity were important drivers of vegetation recovery. North-facing aspects tended to have higher pre-fire Normalized Difference Vegetation Index (NDVI) and thus higher burn severities. However, areas that burned at high severity experienced slower vegetation recovery, regardless of aspect suggesting that high severity fire can mute favorable site conditions on north-facing aspects (i.e. moister, more developed soils). While this work propels our understanding of variables that influence vegetative recovery, vegetation type, forest conversion, and watershed function, more work should focus on what vegetation indices identifying areas of recovery indicate across different forest types and burn severities.

NASA DEVELOP↗
NASA NTRS2021

Colorado Front Range Disasters: Understanding the Impact of Forest Management on the Cameron Peak and CalWood Fire

Along the Colorado Front Range, forest management has gained significant attention due to uncharacteristically large fires that burned late in 2020. The Cameron Peak Fire (largest in Colorado recorded history) and the CalWood Fire collectively burned an estimated 219,019 acres from August through December of 2020. Project partners at the Coalition for the Poudre River Watershed, Colorado State Forest Service, Ben Delatour Scout Ranch, The Nature Conservancy, Colorado Forest Restoration Institute, and Colorado State University were interested in understanding the effectiveness of previous forest treatments in reducing burn severity within the Cameron Peak Fire and the CalWood Fire. We first collated a forest treatment dataset from pre-existing datasets by reclassifying over 29,000 treatments, which occurred across the Northern Colorado Front Range between 1970-2020. Secondly, we mapped three burn severity indices using Landsat 8 OLI and Sentinel-2 MSI Earth observations and compared them to soil burn severity field data. Thirdly, a total of 35 topographic, disturbance, forest structure, and treatment predictor variables were generated across the fires. Finally, we assessed relationships between these predictor variables and burn severity using the random forest algorithm. Model results indicate that the primary drivers of burn severity were elevation and distance to treatment edge for the Cameron Peak Fire and fire area and forest canopy cover for the CalWood Fire. Further analysis of these variables paired with field data is necessary to understand the relationship between burn severity and treatments to guide future restoration efforts, improve forest resiliency, and mitigate fire risks.

Neal Swayze↗
DOE OSTI2016

Optimizing Short-Term Operation of a FIRES-like Industrial Heat Supply Thermal Energy Storage System

The Firebrick Resistance-heated Energy-storage System (FIRES) is under development at MIT for two applications: (1) integration with the Nuclear Air-Brayton Combined Cycle (NACC), a high-performance power conversion system (PCS) that may be used with high- temperature advanced reactors; and (2) industrial heat supply. This paper describes some key features of FIRES and equivalent systems configured for industrial heat supply and presents an assessment of the revenue achievable by a system operating under the conditions expected for early demonstration FIRES installations. The greatest technical challenge of the 21. century is likely to be the effort to minimize the damage caused by global climate change. This effort will require massive reductions in greenhouse gas (GHG) emissions throughout our economy and a transition to an electric power system driven entirely by very-low-carbon generators. Many investigators agree that this will require a substantial increase in electricity generation and in the use of nuclear power, and there is growing awareness that this will also require new technologies and systems for managing and storing energy and matching intermittent supply of renewable resources with electricity demand. Thermal energy storage systems (TESS) will, in some applications, be much more cost effective than the more popular and widely discussed battery electric storage systems and may provide unique capabilities. The Firebrick Resistance-heated Energy-storage System (FIRES) is under development at MIT for two applications: (1) integration with the Nuclear Air-Brayton Combined Cycle (NACC), a high-performance power conversion system (PCS) that may be used with high-temperature advanced reactors like the Fluoride-salt-cooled High-temperature Reactor (FHR), molten salt reactor (MSR) and sodium-cooled fast reactors (SFR); and (2) industrial heat supply. FIRES installations include a stack of refractory firebrick with imbedded electric heaters and airflow channels, a compressor or air blower, and a duct system to connect the firebrick with the heat demand (turbine or industrial customer). Analysis of the FIRES design space has shown that the concept is suitable for a wide range of peak operating temperatures (from about 200 deg.C up to at least 1800 deg. C) and pressures (from ambient to at least 20 atmospheres) and offers very high energy density (up to 1 MWh per cubic meter of firebrick for high temperature systems) at very low cost (as low as $5/kWh). These results favor early demonstration of FIRES. If the cost target of $5/kWh for FIRES systems were achieved, even the lowest expected operating income calculated here could cover the capital cost of a 10 MWh system in a single year. If the FIRES system were assumed to operate for at least 10 years, this level of operating income could readily recover a capital investment up to $50/kWh, which is simultaneously much cheaper than the costs expected for near-future battery systems (in excess of $200/kWh) and much more expensive than the small, low temperature firebrick systems already available for domestic heating. This provides a large margin for unexpected development costs and other uncertainties. FIRES would set a minimum price of electricity near that of natural gas-improving nuclear, wind, and solar economics while reducing greenhouse gas emissions from the industrial sector. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

A minimal model of fire-vegetation feedbacks and disturbance stochasticity generates alternative stable states in grassland–shrubland–woodland systems

Altered disturbance regimes in the context of global change are likely to have profound consequences for ecosystems. Interactions between fire and vegetation are of particular interest, as fire is a major driver of vegetation change, and vegetation properties (e.g., amount, flammability) alter fire regimes. Mediterranean-type ecosystems (MTEs) constitute a paradigmatic example of temperate fire-prone vegetation. Although these ecosystems may be heavily impacted by global change, disturbance regime shifts and the implications of fire-vegetation feedbacks in the dynamics of such biomes are still poorly characterized. We developed a minimal modeling framework incorporating key aspects of fire ecology and successional processes to evaluate the relative influence of extrinsic and intrinsic factors on disturbance and vegetation dynamics in systems composed of grassland, shrubland, and woodland mosaics, which characterize many MTEs. In this theoretical investigation, we performed extensive simulations representing different background rates of vegetation succession and disturbance regime (fire frequency and severity) processes that reflect a broad range of MTE environmental conditions. Varying fire-vegetation feedbacks can lead to different critical points in underlying processes of disturbance and sudden shifts in the vegetation state of grassland-shrubland-woodland systems, despite gradual changes in ecosystem drivers as defined by the environment. Vegetation flammability and disturbance stochasticity effectively modify system behavior, determining its heterogeneity and the existence of alternative stable states in MTEs. Small variations in system flammability and fire recurrence induced by climate or vegetation changes may trigger sudden shifts in the state of such ecosystems. The existence of threshold dynamics, alternative stable states, and contrasting system responses to environmental change has broad implications for MTE management.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Future Pathways for Arctic Forest Fires

Wildfires are expected to become more common and more severe in the Arctic states due to climate change. Main cause for the fires is human activity, even in the boreal and Arctic forests. Therefore, activities such forest management and tourism, together with firefighting capacity and readiness, can have a significant impact on future wildfire risks and impacts. To assess the impacts of these factors we have created pathways for future wildfires up to 2050 for the Arctic states. We explore high and low fire activity and risk pathways for all the Arctic states and suggest most our best guess pathways for each state separately. The low activity and fire risk pathway assumes active fire suppression via population participation and official land management, efficient fuel treatments to reduce fire risk, and active firefighting. The high activity and fire risk pathway assumes the opposite due to lack of government and community response, with addition of lacking response to climate-driven changes to wildfire risks. In the Nordic countries, human ignition sources, such as timber extraction, tourism, summer cottages, and expanding wildland-urban intermix due to exurban growth may increase. In addition to these in Canada and Alaska, expansion of agriculture increases the likelihood of open burning of agricultural waste, increasing risk of the fire spreading to wildlands. Drier fuels due to climate change increase the risk of fires, and there is a growing risk of extreme heat conditions, creating favorable conditions for extreme wildfires from any ignition source. Throughout the Arctic lightning is expected to increase, increasing the risk of tundra (specifically grassland) fires, with potential to occur in hard-to-reach locations for firefighting. In short, policy actions and education play a crucial role in future wildfire management and adaptation.

Future↗
NASA NTRSDate not supplied

CONUS and Global Carbon Consumption Database for Wildland Fire

Fire plays a significant role on both national and global scales, profoundly impacting landscapes shaped by human activity as well as wildlands. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes. Fires can also serve to reduce fuels to mitigate wildfire risk and maintain healthy ecosystem functions. However, the smoke produced by fires, regardless of their size or purpose, can pose adverse effects on human health when inhaled downwind. Understanding the influence of smoke on air quality and human well-being necessitates the quantification of emissions that fires release into the atmosphere. In response to this need, we have developed a carbon consumption database for the Continental United States (CONUS) and are developing a global carbon consumption database, both of which are directly link to distinct fuels within various fire danger categories. Fuel Characteristic Classification System (FCCS) fuels are used to parameterize biomass, and consumption is broken down into five Fire Danger categories (Low, Moderate, High, Very High, Extreme), for both ‘new’ and ‘residual’ burning scenarios. Residual burned area is defined as burning in areas that have recently burned. We implemented the FCCS 30-meter CONUS fuelbed dataset during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign to estimate daily carbon emissions. Our emissions estimates were rigorously compared against in-situ measurements of CO2, CO, and black carbon aerosols, revealing a robust agreement between the two datasets. The 300-meter global database builds upon the foundations of the Pettinari, M. Lucrecia (2015) Global Fuelbed database, a global fuel map with standardized FCCS biomass parameters. These products can serve as valuable tools when used in conjunction with burned area data to rapidly and accurately estimate carbon consumed and released into the atmosphere.

FCCS↗
DOE OSTI2020

Quantifying the drivers and predictability of seasonal changes in African fire

Africa contains some of the most vulnerable ecosystems to fires. Successful seasonal prediction of fire activity over these fire-prone regions remains a challenge and relies heavily on in-depth understanding of various driving mechanisms underlying fire evolution. Here, we assess the seasonal environmental drivers and predictability of African fire using the analytical framework of Stepwise Generalized Equilibrium Feedback Assessment (SGEFA) and machine learning techniques (MLTs). The impacts of sea-surface temperature, soil moisture, and leaf area index are quantified and found to dominate the fire seasonal variability by regulating regional burning condition and fuel supply. Compared with previously-identified atmospheric and socioeconomic predictors, these slowly evolving oceanic and terrestrial predictors are further identified to determine the seasonal predictability of fire activity in Africa. Our combined SGEFA-MLT approach achieves skillful prediction of African fire one month in advance and can be generalized to provide seasonal estimates of regional and global fire risk.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Machine learning to predict final fire size at the time of ignition

Fires in boreal forests of Alaska are changing, threatening human health and ecosystems. Given expected increases in fire activity with climate warming, insight into the controls on fire size from the time of ignition is necessary. Such insight may be increasingly useful for fire management, especially in cases where many ignitions occur in a short time period. Here we investigated the controls and predictability of final fire size at the time of ignition. Using decision trees, we show that ignitions can be classified as leading to small, medium or large fires with 50.4 ± 5.2% accuracy. This was accomplished using two variables: vapour pressure deficit and the fraction of spruce cover near the ignition point. The model predicted that 40% of ignitions would lead to large fires, and those ultimately accounted for 75% of the total burned area. Other machine learning classification algorithms, including random forests and multi-layer perceptrons, were tested but did not outperform the simpler decision tree model. Applying the model to areas with intensive human management resulted in overprediction of large fires, as expected. This type of simple classification system could offer insight into optimal resource allocation, helping to maintain a historical fire regime and protect Alaskan ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Wildfire towers drive firebrand lofting: insights from coupled fire-atmosphere model simulations

Wildfire behavior is shaped by complex fire dynamics, with firebrands playing a critical role in spot fire ignition and fire spread. While previous studies have explored firebrand generation and transport, the specific role of towers and troughs from wildland fires in the lofting of firebrands remains unquantified. This study addresses that gap by using physics-based coupled fire-atmosphere model simulations to examine how wildfire towers (updrafts) and troughs (downdrafts) influence firebrand lofting. Our results show that the majority of firebrands (78.85%) are lofted from towers, where strong updrafts drive long-range transport. In contrast, only 21.15% of firebrands are lofted within troughs, where downdrafts cause most firebrands to fall near the fireline. We also find that firebrand size significantly influences lofting behavior, with smaller particles (1 mm radius) exhibiting the strongest correlation with updraft intensity. These findings highlight the dominant role of wildfire towers in promoting long-distance firebrand dispersal—an essential factor in rapid wildfire growth and wildland-urban interface (WUI) fire risks. By quantifying the relationship between firebrand lofting and fire-induced atmospheric features, this study provides critical insights to improve spot fire modeling, support mitigation planning, and enhance firefighter and WUI community safety in spot fire-prone regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Climate regime shift and forest loss amplify fire in Amazonian forests

Frequent Amazonian fires over the last decade have raised the alarm about the fate of the Earth's most biodiverse forest. The increased fire frequency has been attributed to altered hydrological cycles. However, observations over the past few decades have demonstrated hydrological changes that may have opposing impacts on fire, including higher basin-wide precipitation and increased drought frequency and severity. Here, we use multiple satellite observations and climate reanalysis datasets to demonstrate compelling evidence of increased fire susceptibility in response to climate regime shifts across Amazonia. In this work, we show that accumulated forest loss since 2000 warmed and dried the lower atmosphere, which reduced moisture recycling and resulted in increased drought extent and severity, and subsequent fire. Extremely dry and wet events accompanied with hot days have been more frequent in Amazonia due to climate shift and forest loss. Simultaneously, intensified water vapor transport from the tropical Pacific and Atlantic increased high-altitude atmospheric humidity and heavy rainfall events, but those events did not alleviate severe and long-lasting droughts. Amazonia fire risk is most significant in the southeastern region where tropical savannas undergo long seasonally dry periods. We also find that fires have been expanding through the wet-dry transition season and northward to savanna-forest transition and tropical seasonal forest regions in response to increased forest loss at the "Arc of Deforestation." Tropical forests, which have adapted to historically moist conditions, are less resilient and easily tip into an alternative state. Our results imply forest conservation and fire protection options to reduce the stress from positive feedback between forest loss, climate change, and fire.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Wildland Fires in the Subtropical Hill Forests of Southeastern Bangladesh

The first ever comprehensive study on wildland fires in Bangladesh is carried out to develop a fire prevention and prediction method. The major causes of huge wildland fires (88%) in the subtropical Chittagong Hill forest (43% of total) of southern Bangladesh are reported as shifting cultivation, grazing and unauthorized settlement. We used satellite hotspot (HS) data from 2003 to 2021 (a total of 54,669 HSs) to clarify the spatio-temporal structure of wildland fires. Fire weather conditions were analyzed using various weather data and synoptic-scale weather maps at different air levels. Fires concentrated from March through April or a transitional period from the dry season, caused by the Asian winter monsoon, to the wet season, due to the Asian summer monsoon. Fire occurrence depended on dry conditions and pre-monsoon showers and their timing. The difference in 925 hPa heights of high and low pressure systems may be attributed to the different types of the Asian winter and summer monsoons. The average maximum air temperature and incident shortwave solar energy in April were the highest and strongest, contributing fire-prone weather conditions. Based on the analysis, a fire prevention and prediction method will be developed, and this report may also facilitate the establishment of future CO 2 reduction measures for Bangladesh.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Operation and Development Status of the Spacecraft Fire Experiments (Saffire)

Since 2012, a series of Spacecraft Fire Experiments (Saffire) have been under development by the Spacecraft Fire Safety Demonstration (SFS Demo) project, funded by NASA's Advanced Exploration Systems Division. The overall objective of this project is to reduce the uncertainty and risk associated with the design of spacecraft fire safety systems for NASA's exploration missions. The approach to achieving this goal has been to define, develop, and conduct experiments that address gaps in spacecraft fire safety knowledge and capabilities identified by NASA's Fire Safety System Maturation Team. The Spacecraft Fire Experiments (Saffire-I, -II, and -III) are material flammability tests at length scales that are realistic for a spacecraft fire in low-gravity. The specific objectives of these three experiments are to (1) determine how rapidly a large scale fire grows in low-gravity and (2) investigate the low-g flammability limits compared to those obtained in NASA's normal gravity material flammability screening test. The experiments will be conducted in Orbital ATK's Cygnus vehicle after it has unberthed from the International Space Station. The tests will be fully automated with the data downlinked at the conclusion of the test before the Cygnus vehicle reenters the atmosphere. This paper discusses the status of the Saffire-I, II, and III experiments followed by a review of the fire safety technology gaps that are driving the development of objectives for the next series of experiments, Saffire-IV, V, and VI.

Fire Safety↗