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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Building a machine learning surrogate model for wildfire activities within a global Earth system model

Abstract. Wildfire is an important ecosystem process, influencing land biogeophysical and biogeochemical dynamics and atmospheric composition. Fire-driven loss of vegetation cover, for example, directly modifies the surface energy budget as a consequence of changing albedo, surface roughness, and partitioning of sensible and latent heat fluxes. Carbon dioxide and methane emitted by fires contribute to a positive atmospheric forcing, whereas emissions of carbonaceous aerosols may contribute to surface cooling. Process-based modeling of wildfires in Earth system land models is challenging due to limited understanding of human, climate, and ecosystem controls on fire counts, fire size, and burned area. Integration of mechanistic wildfire models within Earth system models requires careful parameter calibration, which is computationally expensive and subject to equifinality. To explore alternative approaches, we present a deep neural network (DNN) scheme that surrogates the process-based wildfire model with the Energy Exascale Earth System Model (E3SM) interface. The DNN wildfire model accurately simulates observed burned area with over 90 % higher accuracy with a large reduction in parameterization time compared with the current process-based wildfire model. The surrogate wildfire model successfully captured the observed monthly regional burned area during validation period 2011 to 2015 (coefficient of determination, R2=0.93). Since the DNN wildfire model has the same input and output requirements as the E3SM process-based wildfire model, our results demonstrate the applicability of machine learning for high accuracy and efficient large-scale land model development and predictions.

58 GEOSCIENCES↗
NASA NTRS2022

Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution and Controlling Factors, From Satellite Observations

The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Katherine T. Junghenn Noyes↗
DOE OSTI2021

North American boreal forests are a large carbon source due to wildfires from 1986 to 2016

Wildfires are a major disturbance to forest carbon (C) balance through both immediate combustion emissions and post-fire ecosystem dynamics. Here we used a process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to simulate C budget in Alaska and Canada during 1986–2016, as impacted by fire disturbances. We extracted the data of difference Normalized Burn Ratio (dNBR) for fires from Landsat TM/ETM imagery and estimated the proportion of vegetation and soil C combustion. We observed that the region was a C source of 2.74 Pg C during the 31-year period. The observed C loss, 57.1 Tg C year -1 , was attributed to fire emissions, overwhelming the net ecosystem production (1.9 Tg C year -1 ) in the region. Our simulated direct emissions for Alaska and Canada are within the range of field measurements and other model estimates. As burn severity increased, combustion emission tended to switch from vegetation origin towards soil origin. When dNBR is below 300, fires increase soil temperature and decrease soil moisture and thus, enhance soil respiration. However, the post-fire soil respiration decreases for moderate or high burn severity. The proportion of post-fire soil emission in total emissions increased with burn severity. Net nitrogen mineralization gradually recovered after fire, enhancing net primary production. Net ecosystem production recovered fast under higher burn severities. The impact of fire disturbance on the C balance of northern ecosystems and the associated uncertainties can be better characterized with long-term, prior-, during- and post-disturbance data across the geospatial spectrum. Our findings suggest that the regional source of carbon to the atmosphere will persist if the observed forest wildfire occurrence and severity continues into the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Evaluating Polymer Properties with Different Additives for Carbon Capture and Other Applications

Anthropogenic climate change is one of this generation’s most pressing concerns, with the potential to completely alter the delicate balance we’ve struck with nature. Already, global temperatures have risen 1.29°C, leading to disrupted weather systems, extinctions, increased risks of wildfires, and sea level rise, to name a few effects. Carbon dioxide emission from the combustion of fossil fuels and other industrial activity is a large driver of this phenomenon, as it absorbs heat before it can be radiated away from Earth, trapping it. Carbon dioxide has reached unprecedented levels in our atmosphere, showing a 50% increase from preindustrial averages to a whopping 430 ppm. Thus, reducing the amount of carbon dioxide via carbon capture technology is an important endeavor that serves to benefit everyone. The Microencapsulated CO 2 Sorbent (MECS) team at Lawrence Livermore National Laboratory (LLNL) has turned to microencapsulation to approach this endeavor. Microcapsules provide an attractive approach to carbon capture, combining large surface areas for more efficient mass transfer, regenerative abilities, reduced solvent loss, and improved handling. Additionally, while existing carbon capture technology relies on industrial plants, capsules could present a modular approach to carbon capture, reducing the need for extensive physical infrastructure. The MECS team’s design consists of a polymer membrane that contains a liquid carbon sequestering sorbent, aqueous sodium carbonate. The carbon capturing reaction occurs in three distinct steps, the first of which is the dissolution of carbon dioxide into the sorbent solution and its conversion into carbonic acid (H 2 CO 3 ), shown in equations 1 and 2 respectively. Because this step hinges upon the ability of carbon dioxide to reach the solution inside the capsule, it is necessary that the microcapsule shell is permeable to carbon dioxide gas. The MECS team produces these microcapsules using the in-air droplet encapsulation apparatus (IDEA) shown in figure 1, which can produce uniform micron-scale droplets at speeds much faster than traditional single-dispersal microfluidic-based techniques. The IDEA Is 100 times faster than these current techniques and can reach up to 1000 times their speed when incorporating a multi-nozzle design. Additionally, because droplets are produced in-air via vibration, IDEA can decrease post-processing times and material waste by 99% and can fabricate microgels that are 10 to 100 times more viscous than can be produced via traditional microfluidics. While this design represents a breakthrough in the throughput, efficiency, and tunability of microcapsule production, it imposes a major constraint on the microcapsule curing process. Because microcapsule shells are crosslinked with UV light while falling 30 cm through the air, this gives them a reaction window of approximately 0.2 seconds. Thus, the system and shell formulations must be optimized such that the shells can be fully crosslinked within this very narrow window, prompting investigations into curing behavior.

36 MATERIALS SCIENCE↗
NASA NTRS1992

Summertime measurements of selected nonmethane hydrocarbons in the Arctic and Subarctic during the 1988 Arctic Boundary Layer Expedition (ABLE 3A)

The concentration distributions of several nonmethane hydrocarbons (NMHIC) in the Arctic and Subarctic regions of Alaska are discussed using data obtained during July and August of 1988 as part of the Arctic Boundary Layer Expedition (ABLE 3A). Plume enhancement of some or all of the measured NMHIC were observed on more than half of the 33 missions flown during the project. The usual summer vertical profile of reactive hydrocarbons at these high latitudes has elevated concentrations at high altitudes, with mixing ratio variations largely controlled by hydroxyl radical reactions. Wildfires were established as a significant source of various NMHIC. Biomass burning emission ratios relative to ethane were established for ethyne (0.38 +/- 0.04) and propane (0.08 +/- 0.03). Activities associated with oil drilling are a probable source of enhanced levels of alkanes observed as much as 300 km northeast of Prudhoe Bay.

Blake, Donald R.↗
DOE OSTI2024

NSA Site Science: Use of ARM Observations from Northern Alaska to Evaluate and Improve Prediction Capabilities

The Arctic is warming at a rate nearly double that of the rest of the planet, leading to profound changes in atmospheric, oceanic, and ice processes. The U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility has played a significant role in Arctic research, operating observatories in Alaska's North Slope for over 25 years. These observatories provide a rich, and wide-reaching dataset that offers insight into atmospheric processes in northern Alaska. This report details the results of a nine-year research project (2015–2024) supported by the DOE Atmospheric Systems Research (ASR) program, that leverages data from ARM’s deployment of observing facilities at Utqiaġvik (known as the North Slope of Alaska, or NSA, site) and Oliktok Point, Alaska. The project was conducted in two phases: - Phase 1 (2015–2019): Focused on understanding key atmospheric processes at Oliktok Point, including cloud formation, high-latitude precipitation, aerosol-cloud interactions, and cloud properties. - Phase 2 (2019–2024): Extended the research to the broader North Slope region, using data from both Oliktok Point and Utqiaġvik. Topics explored included surface energy budgets, atmospheric stability, ice nucleation processes, and microphysics in Arctic clouds. The project resulted in numerous research products, including 50 peer-reviewed publications and dissertations, 169 presentations, and 10 data products. These products cover a variety of topics, including: - Cloud Macro- and Microphysical Properties: Arctic clouds play a crucial role in energy transfer, and accurate representation in models is critical. The study explored cloud transitions, ice crystal shapes, and dual-wavelength radar data to understand ice crystal habits and size distributions. - Aerosol Properties and Processes: The team examined aerosol sources in the Arctic, including industrial emissions and natural sources. Observations showed significant spatial gradients in aerosol concentrations due to human activities and wildfire smoke. The influence of aerosols on cloud formation and the surface energy budget was also assessed. - Aerosol-Cloud Interactions: Research revealed that aerosols might suppress cloud ice production, affecting cloud radiative forcing and precipitation. The impact of local industrial emissions on cloud properties was also investigated. - Contextualizing the North Slope of Alaska in the context of the broader Arctic: To understand broader trends, the project evaluated large-scale circulation patterns and the influence of weather systems on the Arctic. Studies indicated that large-scale processes play a significant role in temperature patterns and the timing of snowmelt. - Advancing ARM Observational and Modeling Capabilities: The project developed new radar data products and advanced measurement techniques, including clutter mitigation and drizzle detection. Uncrewed aerial systems (UAS) and tethered balloon systems (TBS) were deployed to gather detailed atmospheric data. Additionally, the project supported 10 early career scientists, providing training and mentorship to undergraduate interns, graduate students, postdoctoral researchers, and early career researchers. These efforts contributed to the advancement of ARM research capabilities and fostered a new generation of scientists skilled in Arctic atmospheric research. Ultimately, this ASR-supported project has provided valuable insights into Arctic atmospheric processes and their broader climate implications. Recommendations for future work include continuing support for long-term observing at Arctic locations to foster additional research, further exploration of aerosol-cloud interactions and the potential impacts of enhanced industrialization of the Arctic, and expanded use of uncrewed systems to gather data in this remote and harsh environment. Additionally, the data products developed by this work, and the data products developed through the ARM infrastructure, leave a treasure-trove of additional information that should be explored for many years to come to gain additional insight into physical processes in the Arctic atmosphere that drive the rapid changes occurring in at high latitudes and their global impact.

58 GEOSCIENCES↗
DOE OSTI2021

Assessing climate change impacts on live fuel moisture and wildfire risk using a hydrodynamic vegetation model

Abstract. Live fuel moisture content (LFMC) plays a critical role in wildfire dynamics, but little is known about responses of LFMC to multivariate climate change, e.g., warming temperature, CO2 fertilization, and altered precipitation patterns, leading to a limited prediction ability of future wildfire risks. Here, we use a hydrodynamic demographic vegetation model to estimate LFMC dynamics of chaparral shrubs, a dominant vegetation type in fire-prone southern California. We parameterize the model based on observed shrub allometry and hydraulic traits and evaluate the model's accuracy through comparisons between observed and simulated LFMC of three plant functional types (PFTs) under current climate conditions. Moreover, we estimate the number of days per year of LFMC below 79 % (which is a critical threshold for wildfire danger rating of southern California chaparral shrubs) from 1960 to 2099 for each PFT and compare the number of days below the threshold for medium and high greenhouse gas emission scenarios (RCP4.5 and 8.5). We find that climate change could lead to more days per year (5.2 %–14.8 % increase) with LFMC below 79 % between the historical (1960–1999) and future (2080–2099) periods, implying an increase in wildfire danger for chaparral shrubs in southern California. Under the high greenhouse gas emission scenario during the dry season, we find that the future LFMC reductions mainly result from a warming temperature, which leads to 9.1 %–18.6 % reduction in LFMC. Lower precipitation in the spring leads to a 6.3 %–8.1 % reduction in LFMC. The combined impacts of warming and precipitation change on fire season length are equal to the additive impacts of warming and precipitation change individually. Our results show that the CO2 fertilization will mitigate fire risk by causing a 3.5 %–4.8 % increase in LFMC. Our results suggest that multivariate climate change could cause a significant net reduction in LFMC and thus exacerbate future wildfire danger in chaparral shrub systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

The NASA TEMPO Mission: Hourly Daytime Air Pollution Observations for Enhanced Health and Air Quality Applications

The Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission was launched into Geostationary Earth Orbit (GEO) to 91°W longitude on April 7, 2023, and had a successful 3-day First Light period starting July 31 with TEMPO making its first hourly daytime scans across the TEMPO Field of Regard (FoR) covering greater North America on August 2. TEMPO will provide hourly daytime observations of aerosols and trace gases, including criteria pollutants of nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3), at high spatial resolution (e.g., 2.0 x 4.75 km2) across the FoR. The hyperspectral ultraviolet-to-visible measurements from the TEMPO imaging grating spectrometer will enable an O3 profile product capable of monitoring the daytime diurnal evolution of O3 pollution in the planetary boundary layer and assessing related health impacts. The non-standard or special scan operations of TEMPO at sub-hourly frequency (e.g., 2-10 minutes) over selected slices of the FoR will further enhance air quality monitoring capabilities during disasters (e.g., wildfires, volcanic eruptions, dust storms, industrial accidents) and other episodic events for better understanding emission sources and the evolution of harmful air pollutants. A large diversity of stakeholders and end-users have been engaged in the TEMPO Early Adopters Program, supported by the NASA Applied Sciences Program, which aims to enhance health and air quality applications and maximize the societal benefit of TEMPO data. Key outcomes from the Early Adopters Program include enhanced knowledge and preparation for using TEMPO data, tailoring the data dissemination and visualization tools for TEMPO based on user needs, and broadening the health and air quality applications facet of the mission. This presentation will provide the latest TEMPO mission and Early Adopters Program updates, insight into the health and air quality applications enabled through TEMPO data, and showcase the First Light NO2 imagery and provisional data from the mission.

Remote Sensing↗
DOE OSTI2026

Ammonia in northeast Colorado is increasing, rising most quickly in regions close to confined animal feeding operations

The Colorado Front Range urban corridor and nearby agricultural operations are important source regions of atmospheric ammonia (NH 3 ). Upslope flows periodically transport these emissions into Rocky Mountain National Park (RMNP), located 50 km west of the urban corridor, where wet and dry deposition of excess reactive nitrogen (N) impacts ecosystems. Here, we use a combination of in situ passive NH 3 measurements and NH 3 vertical column density retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) to assess variability and changes in NH 3 across three land use categories in the northeast Colorado source region (agricultural, urban, and remote) during the period 2013-2023. A strong seasonal cycle is present across the region with increased NH 3 during summer months. Elevated NH 3 is spatially correlated with the number of permitted animal units in confined animal feeding operations (CAFOs) within 12 km. Ground-level NH 3 concentrations are strongly positively correlated with monthly gridded IASI satellite column densities. Satellite retrievals reveal an increasing trend in NH 3 column amounts of ∼3% per year in agricultural and ∼2% per year in urban sub-regions. The magnitude of the trend observed in NH 3 columns averaged over the agricultural sub-region is > 3 times larger than observed near and over Denver. The largest increases in NH 3 are closely aligned with the distribution of CAFOs. Reductions in particle sulfate associated with declining sulfur dioxide (SO 2 ) emissions could account for only ∼0.1% per year increase in gaseous NH 3 . Wildfire smoke across the region has increased but appears unlikely to explain the majority of the observed NH 3 increase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Impact of Wildfires on Solar Resource Availability in California in a Changing Climate

Wildfires can emit large amounts of atmospheric particulate matters and influence not only air quality but also availability of photovoltaic (PV) generation due to scattering and absorption of solar radiation. Under anthropogenic changing climate, wildfire activity is projected to increase over western North America due to drier and warmer climate, implying increasing impact on solar resource and larger uncertainty in solar generation especially in regions with faster PV penetration. This study focuses on quantifying the impact of wildfires on aerosol optical depth (AOD) and thus solar resource over California using National Solar Radiation Database (NSRDB), developed by the National Renewable Energy Laboratory (NREL). This assessment includes historical analysis and estimation of solar resource under wildfire scenarios (2020 wildfire and an enhanced wildfire scenario based on 2020 wildfires). Historical analysis for the period of July-October 2019/2020 (low/high fire activity period) shows that the averaged global horizontal irradiance (GHI) and direct normal irradiance (DNI) are reduced by about 30 and 90 W m-2 (5.6 and 15.3%), respectively, during high fire activity period. To create AOD dataset for enhanced fire scenario, 165% increase in burn area (in around 2050) is selected based on comprehensive literature review, which is further applied to the Fire INventory from NCAR (FINN) fire emission. WRF-Chem model with the enhanced FINN emissions is used to simulate and represent a preserving spatial distribution of burned areas and wildfire-emitted aerosols. Our initial analysis suggests that the"enhanced 2020 wildfire" AOD can increase by a factor of 1.3 - 2, which can significantly reduce solar irradiance and increase uncertainty in generation and reliability of power system in extreme wildfire events under a high solar penetration scenario. Overall, this study provides an estimate of the impacts of wildfires on solar resource to make informed decisions on reserve planning, generation scheduling, and reliability investments.

aerosol optical depth↗
DOE OSTI2023

Matching diverse feedstocks to conversion processes for the future bioeconomy

A wide variety of wasted or underutilized organic feedstocks can be leveraged to build a sustainable bioeconomy, ranging from crop residues to food processor residues and municipal wastes. Leveraging these feedstocks is both high-risk and high-reward. Converting mixed, variable, and/or highly contaminated feedstocks can pose engineering and economic challenges. However, converting these materials to fuels and chemicals can divert waste from landfills, reduce fugitive methane emissions, and enable more responsible forest management to reduce the frequency and severity of wildfires. Historically, low-value components, including ash and lignin, are poised to become valuable coproducts capable of supplementing cement and valuable chemicals. Here, we evaluate the challenges and opportunities associated with converting a range of feedstocks to renewable fuels and chemicals.

09 BIOMASS FUELS↗
NASA NTRS2015

Enabling Earth Science Measurements with NASA UAS Capabilites

NASA's Airborne Science Program (ASP) maintains a fleet of manned and unmanned aircraft for Earth Science measurements and observations. The unmanned aircraft systems (UAS) range in size from very large (Global Hawks) to medium (SIERRA, Viking) and relatively small (DragonEye). UAS fly from very low (boundary layer) to very high altitude (stratosphere). NASA also supports science and applied science projects using UAS operated by outside companies or agencies. The aircraft and accompanying data and support systems have been used in numerous investigations. For example, Global Hawks have been used to study both hurricanes and atmospheric composition. SIERRA has been used to study ice, earthquake faults, and coral reefs. DragonEye is being used to measure volcanic emissions. As a foundation for NASA's UAS work, Altair and Ikkana not only flew wildfires in the Western US, but also provided major programs for the development of real-time data download and processing capabilities. In early 2014, an advanced L-band Synthetic Aperture Radar (SAR) also flew for the first time on Global Hawk, proving the utility of UAVSAR, which has been flying successfully on a manned aircraft. In this paper, we focus on two topics: 1) the results of a NASA program called UAS-Enabled Earth Science, in which three different science teams flew (at least) two different UAS to demonstrate platform performance, airspace integration, sensor performance, and applied science results from the data collected; 2) recent accomplishments with the high altitude, long-duration Global Hawks, especially measurements from several payload suites consisting of multiple instruments. The latest upgrades to data processing, communications, tracking and flight planning systems will also be described.

Earth Science↗
NASA NTRS2011

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003.2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS) ]derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top ]down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗
NASA NTRS2000

EOSDIS Terra Data Sampler #1: Western US Wildfires 2000

This CD-ROM contains sample data in HDF-EOS format from the instruments on board the Earth Observing System (EOS) Terra satellite: (1) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER); (2) Clouds and the Earth's Radiant Energy System (CERES); (3) Multi-angle Imaging Spectroradiometer (MISR); and (4) Moderate Resolution Imaging Spectroradiometer (MODIS). Data from the Measurements of Pollution in the Troposphere (MOPITT) instrument were not available for distribution (as of October 17, 2000). The remotely sensed, coincident data for the Western US wildfires were acquired August 30, 2000. This CD-ROM provides information about the Terra mission, instruments, data, and viewing tools. It also provides the Collage tool for viewing data, and links to Web sites containing other digital data processing software. Full granules of the data on this CD-ROM and other EOS Data and Information System (EOSDIS) data products are available from the NASA Distributed Active Archive Centers (DAACs).

Perkins, Dorothy C.↗
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 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↗
DOE OSTI2022

Wetter California Projected by CMIP6 Models With Observational Constraints Under a High GHG Emission Scenario

As the world's fifth-largest economy entity, California (CA) is vulnerable to climate changes especially the magnitude of winter (wet season) precipitation that is closely linked to regional drought severity, vegetation growth, and wildfire activities. However, the fate of CA precipitation in the future remains highly uncertain, for example, the state-of-the-art Earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) projected –3% to +42% and –27% to +63% precipitation changes in northern and central-southern CA, respectively, under the high greenhouse gas (GHG) emission scenario (SSP585). In this work, we applied the Pareto optimality concept and used observed teleconnection patterns (causal relationships between ocean regions and CA precipitation) to mechanistically constrain CMIP6 projected CA precipitations. We estimated that precipitation will robustly increase by 0.4–1.3 mm d –1 (10–34%) over northern CA and increase by 0.1–0.5 mm d –1 (7–32%) over central-southern CA by the end of the 21st century compared with present-day. Up to 71% of ESM projection uncertainties were reduced mainly due to the strong and consistent causal relationship between North American west coast sea level pressure and CA precipitation in both observations and CMIP6 models. Our results suggest that teleconnection patterns are powerful mechanistic constraints that can help explain and reduce uncertainties in ESM projections.

54 ENVIRONMENTAL SCIENCES↗