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At least 577 records · Page 32

Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) Science Plan

Coastal cities provide the opportunity to characterize marine clouds and the substantial effects of manmade particles on cloud properties and processes. La Jolla lies to the north of San Diego, California, but it is often about a day directly downwind of the major pollution sources located in the ports of Los Angeles and Long Beach. The large dynamic range of aerosol particle concentrations combined with the multi-hour to multi-day persistence of stratocumulus cloud layers makes the site ideal for investigating the seasonal changes in cloud and aerosol properties as well as the quantitative relationships between cloud and aerosol properties. The focus of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) is to characterize the extent, radiative properties, aerosol interactions, and precipitation characteristics of stratocumulus clouds in the Eastern Pacific across all four seasons at a coastal location, the Scripps Pier and the Scripps Mt. Soledad sites in La Jolla. An important enhancement to this study will be the collection of simultaneous in-cloud aerosol and droplet measurements to investigate the differences in these cloud properties during regional polluted and clean marine conditions. The combined observations will provide an unprecedented set of constraints for the following questions: 1. Cloud and Aerosol Climatology: What are the seasonal and diurnal cycles of marine stratocumulus cloud and aerosol properties on the northeastern Pacific coast? 2. Cloud Radiative Fluxes: How do cloud properties, including the ratio of direct-to-diffuse radiation, change as coastal clouds are advected inland? 3. Aerosol-Cloud Interactions: Will retrieved cloud properties reflect the regional signatures of aerosol?

Eastern Pacific Cloud Aerosol Precipitation Experi↗

Preconditioning of overcast-to-broken cloud transitions by riming in marine cold air outbreaks

Marine cold air outbreaks (CAOs) commonly form overcast cloud decks that transition into broken cloud fields downwind, dramatically altering the local radiation budget. In this study, we investigate the impact of frozen hydrometeors on these transitions. We focus on a CAO case in the NW Atlantic, the location of the multi-year flight campaign ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment). We use MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, version 2) reanalysis fields to drive large eddy simulations with mixed-phase two-moment microphysics in a Lagrangian framework. We find that transitions are triggered by substantial rain (rainwater paths >25 g m−2), and only simulations that allow for aerosol depletion result in sustained breakups, as observed. Using a range of diagnostic ice nucleating particle concentrations, Ninp, we find that increasing ice progressively accelerates transitions, thus abbreviating the overcast state. Ice particles affect the cloud-topped boundary layer evolution, primarily through riming-related processes prior to substantial rain, leading to (1) a reduction in cloud liquid water, (2) early consumption of cloud condensation nuclei, and (3) early and light precipitation cooling and moistening below cloud. We refer to these three effects collectively as “preconditioning by riming”. Greater boundary layer aerosol concentrations available as cloud condensation nuclei (CCN) delay the onset of substantial rain. However, cloud breakup and low CCN concentration final stages are found to be inevitable in this case, due, primarily, to liquid water path buildup. An ice-modulated cloud transition speed suggests the possibility of a negative cloud–climate feedback. To address prevailing uncertainties in the model representation of mixed-phase processes, the magnitude of ice formation and riming impacts and, thereby, the strength of an associated negative cloud–climate feedback process, requires further observational evaluation by targeting riming hot spots with in situ imaging probes that allow for both the characterization of ice particles and abundance of supercooled droplets.

Marine cold air outbreaks↗

Numerous Wildfire Smoke Plumes in Northwest Ontario, Canada

The height at which smoke is lofted into the atmosphere affects how long it will stay aloft, how far it will travel, and how much of an impact it will have on air quality downwind, and regional climate. Parallax, the change in apparent plume position relative to the surface, as observed by NASA's Multi0angle Imaging Spectroradiometer (MISR) instrument, makes it possible to map the height of smoke, dust and volcanic plumes near-source, where plume features are visible in the multi-angle views.

wildfire smoke↗

Hydraulic Jump Dynamics Above Supercell Thunderstorms

The strongest supercell thunderstorms typically feature an above-anvil cirrus plume (AACP), which is a plume of ice and water vapor in the lower stratosphere that occurs downwind of the ambient stratospheric flow in the lee of overshooting deep convection. AACP-origin hydration of the stratosphere has a poorly constrained role in ozone destruction and surface warming. In this study, we use large eddy simulations corroborated by radar observations to understand the physics of AACP generation. We show that the overshooting top of a simulated supercell can act as a topographic obstacle and drive a hydraulic jump downstream at the tropopause, similar to a windstorm moving down the slope of a mountain but without solid topography. Once the jump is established, water vapor injection deep into the stratosphere may exceed 7 tonnes per second.

Gerald M Heymsfield↗

Wintertime Formaldehyde: Airborne Observations and Source Apportionment Over the Eastern United States

Formaldehyde (HCHO) is generated from direct urban emission sources and secondary production from the photochemical reactions of urban smog. HCHO is linked to tropospheric ozone formation, and contributes to the photochemical reactions of other components of urban smog. In this study pollution plume intercepts during the Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign were used to investigate and characterize the formation of HCHO in relation to several anthropogenic tracers. Analysis of aircraft intercepts combined with detailed chemical box modeling downwind of several cities suggest that the most important contribution to observed HCHO was primary emission. A box model analysis of a single plume suggested that secondary sources contribute 21±10% of observed HCHO. Ratios of HCHO/CO observed in the northeast U.S., from Ohio to New York, ranging from 0.2-0.6%, are consistent with direct emissions combined with at most modest photochemical production. Analysis of the nocturnal boundary layer and residual layer from repeated vertical profiling over urban influenced areas indicate a direct HCHO emission flux of 1.3 x 10 14 molecules cm -2 h -1 . In a case study in Atlanta, GA, nighttime HCHO exhibited a ratio to CO (0.6 – 1.8%) and was anti-correlated with O 3 . Observations were consistent with mixing between direct HCHO emissions in urban air masses with those influenced by more rapid HCHO photochemical production. The HCHO/CO emissions ratios determined from the measured data are 2.3 - 15 times greater than the NEI 2017 emissions database. The largest observed HCHO/CO was 1.7 – 1.8%, located near co-generating power stations.

Formaldehyde↗

Consequences of Insufficient Production of Temporary NOx Reservoirs on Ozone Production in Models During KORUS-AQ

The advent of geostationary satellites, starting with GEMS over South Korea, offer the potential for additional insight into urban air quality. In preparation for these satellites, the joint NIER-NASA KORUS-AQ field campaign in 2016 obtained a large dataset for understanding local air quality and the contribution of local emissions to ozone and PM2.5 pollution. Models partitioned NOx primarily into inorganic nitrate (HNO3 + nitrate aerosol) while observations suggest that acyl peroxy nitrates (PNs) should be an important sink. Models tended to produce ozone too efficiently, which may be due to insufficient alkyl/multifunctional nitrate (ANs) production. Models are unable to simulate the transport of NOx away from the urban center and its impact on ozone production downwind.

Katherine R Travis↗

Simultaneous Characterization of Wildfire Smoke and Surface Properties With Imaging Spectroscopy During the FIREX-AQ Field Campaign

We introduce and evaluate an approach for the simultaneous retrieval of aerosol and surface properties from Airborne Visible/Infrared Imaging Spectrometer Classic (AVIRIS-C) data collected during wildfires. The joint National Aeronautics and Space Administration (NASA) National Oceanic and Atmospheric Administration Fire Influence on Regional to Global Environments and Air Quality field campaign took place in August 2019, and involved two aircraft and coordinated ground-based observations. The AVIRIS-C instrument acquired data from onboard NASA's high altitude ER-2 research aircraft, coincident in space and time with aerosol observations obtained from the Aerosol Robotic Network (AERONET) DRAGON mobile platform in the smoke plume downwind of the Williams Flats Fire in northern Washington in August 2019. Observations in this smoke plume were used to assess the capacity of optimal-estimation based retrievals to simultaneously estimate aerosol optical depth (AOD) and surface reflectance from Visible Shortwave Infrared (VSWIR) imaging spectroscopy. Radiative transfer modeling of the sensitivities in spectral information collected over smoke reveal the potential capacity of high spectral resolution retrievals to distinguish between sulfate and smoke aerosol models, as well as sensitivity to the aerosol size distribution. Comparison with ground-based AERONET observations demonstrates that AVIRIS-C retrievals of AOD compare favorably with direct sun AOD measurements. Our analyses suggest that spectral information collected from the full VSWIR spectral interval, not just the shortest wavelengths, enables accurate retrievals. We use this approach to continuously map both aerosols and surface reflectance at high spatial resolution across heterogeneous terrain, even under relatively high AOD conditions associated with wildfire smoke.

FIREX-AQ↗

Update on AeroCom Biomass Burning Emission Injection Height experiment (BBEIH)

In BBEIH, we introduced the biomass burning injection heights based on MISR stereo-derived plume-height retrievals (Val Martin et al., 2010; 2018) in four participating CTMs. Specifically, we proposed 4 simulations for the year 2008: 1) BASE: using the biomass burning emissions from Global Fire Emissions Database version 4 with small fires (GFED4s) and the model default fire emission injection height; 2) BBIH: Same as BASE, but using the injection height derived from the seasonally and regionally varying MISR-retrieved plume heights; 3) NOBB: no fire emission; 4) Same as BASE, but using Fire Energetics and Emissions Research version 1.0 (FEER 1.0). We will address the following scientific questions: 1) To what extent are the model simulations sensitive to the assumed biomass burning injection height? 2) In which regions/seasons/surface-types are the aforementioned sensitivities most important? We will update the multi-model inter-comparison with a focus on the vertical aerosol distribution in near-source characteristics and downwind plume evolution." In order to test the sensitivity of model results to smoke injection height, we proposed the biomass burning emission injection height experiment (BBEIH) in the AeroCom 2019 workshop. The description of implementation methods and input data for BBEIH can be found in https://wiki.met.no/aerocom/phase3-experiments#biomass_burning_emission_injection_height_experiment_bbeih.

Xiaohua Pan↗

Updated assessment of TROPOMI NO2 and HCHO columns using airborne spectrometers during the MOOSE and TRACER-AQ field campaigns

Airborne spectrometer data offers the opportunity to evaluate satellite product performance without the impact of subpixel heterogeneity between the different satellite and ground-based measurement footprints. Previous measurements during the Long Island Sound Tropospheric Ozone Study were used to evaluate TROPOMI’s v1.3 NO2 product and found very strong relationships (r2=0.96) between the airborne spectrometer and TROPOMI with a systematic low bias mostly attributed to the coarse a priori profile assumption within the standard TROPOMI retrieval. This presentation will update that analysis using the most up-to-date version 2 TROPOMI NO2 product as well as expand analysis to the HCHO product. In summer 2021, NASA GeoCAPE Airborne Simulator (GCAS) collected measurements over southeast Michigan/western Ontario for the Michigan-Ontario Ozone Source Experiment (MOOSE) and Houston, Texas during the TRacking Aerosol Convection ExpeRiment – Air Quality (TRACER-AQ). Flight strategies for both deployments included repeated systematic sampling over common areas of interest coinciding with TROPOMI. During these flights, GCAS NO2 tropospheric columns are available at 250 m x 560 m resolution. Preliminary evaluation of GCAS NO2 retrievals with Pandora spectrometer data in Houston, Texas (3 sites) shows a median percent difference of 1.4% with an interquartile range of -15.5-14.9% (r2=0.72). Column HCHO was also retrieved at a slightly coarser resolution in Houston, Texas (750 m x 1680 m) showing distinct spatial patterns associated with secondary production through the oxidation of VOCs downwind of industrial facilities. Comparison to Pandora HCHO showed a low bias of ~25% (r2=0.29) with further investigation needed to identify the cause for this bias. This presentation will share how the GCAS/Pandora/TROPOMI NO2 and HCHO intercompare and will also extend analysis toward thinking about how these assets will contribute to the validation of future geostationary observations.

Laura Judd↗

Comparison of Dust Optical Depth From Multi-Sensor Products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) Dust Reanalysis Over North Africa, the Middle East, and Europe

Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.

Michail Mytilinaios↗

Results from InSight Robotic Arm Activities

The InSight lander carried an Instrument Deployment System (IDS) that included an Instrument Deployment Arm (IDA), scoop, five finger “claw” grapple, forearm-mounted Instrument Deployment Camera (IDC) requiring arm motion to image a target, and landermounted Instrument Context Camera (ICC), designed to image the workspace, and to place the instruments onto the surface. As originally proposed, the IDS included a previously built arm and flight spare black and white cameras and had no science objectives or requirements, or expectation to be used after instrument deployment (90 sols). During project development the detectors were upgraded to color, and it was recognized that the arm could be used to carry out a wide variety of activities that would enable both geology and physical properties investigations. During surface operations for two martian years, the IDA was used during major campaigns to image the surface around the lander, to deploy the instruments, to assist the mole in penetrating beneath the surface, to bury a portion of the seismometer tether, to clean dust from the solar arrays to increase power, and to conduct a surface geology investigation including soil mechanics and physical properties experiments. No other surface mission has engaged in such a sustained and varied campaign of arm and scoop activities directed at such a diverse suite of objectives. Images close to the surface and continuous meteorology measurements provided important constraints on the threshold friction wind speed needed to initiate aeolian saltation and surface creep. The IDA was used extensively for almost 22 months to assist the mole in penetrating into the subsurface. Soil was scraped into piles and dumped onto the seismometer tether six times in an attempt to bury the tether and ∼ 30% was entrained in the wind and dispersed downwind 1-2 m, darkening the surface. Seven solar array cleaning experiments were conducted by dumping scoops of soil from 35 cm above the lander deck during periods of high wind that dispersed the sand onto the panels that kicked dust off of the panels into suspension in the atmosphere, thereby increasing the power by ∼15% during this period. Final IDA activities included an indentation experiment that used the IDA scoop to push on the ground to measure the plastic deformation of the soil that complemented soil mechanics measurements from scoop interactions with the surface, and two experiments in which SEIS measured the tilt from the arm pressing on the ground to derive near surface elastic properties.

Mars↗

Improving Simulation of Irrigation in a Global Land Surface Model

Studies have shown that irrigated agriculture has substantial effects on local to regional hydrologic and atmospheric processes. These effects include increased evapotranspiration and near surface humidity, decreased air and ground temperature, augmented downwind precipitation, enhanced recharge, depletion of source water stocks, and overall changes to the regional water budget. However, developers of global offline and coupled modeling systems have been slow to incorporate irrigation. This presentation will describe progress towards simulating irrigation worldwide in the Land Information System (LIS) and Global Land Data Assimilation System (GLDAS). We have developed and refined the ability to simulate sprinkler irrigation, furrow irrigation, paddy irrigation, and drip irrigation. We have reconciled multiple global and national irrigation, land cover, and crop type databases in an effort to (1) distinguish irrigated and rainfed agriculture, (2) simulate the proper distribution of crops (as sub-grid tiles) in each model grid pixel, and (3) apply the most likely irrigation method in each tile based on the crop type and country or state level information on the relative usage of sprinkler, flood, and drip irrigation. Using agricultural water withdrawal data, as available, for calibration and evaluation, we show that the implemented approach is promising but that much fine tuning remains to be done. In particular, irrigation model parameters that produce good results in one location often produce less satisfying results in others.

Matthew Rodell↗

Mineral Dust Optical Properties for Remote Sensing and Global Modeling: A Review

Dust plays a key role in many Earth system processes and is ubiquitous in the Martian atmosphere. Various intensive field campaigns, laboratory analyses, space-based remote sensing missions, and global modeling efforts aim to characterize dust optical properties. This is a bountiful time for dust scientists, and yet the interpretation of retrievals and comparison to models remains complicated by various conflicting assumptions that are part of each algorithm. For example, the conversion of satellite radiance measurements into products like aerosol optical depth for model evaluation depends upon aerosol properties like particle size and shape that are often prescribed and not part of the retrieval. Conversely, the model calculation of aerosol optical depth often uses different assumptions. The goal of this review is to first document algorithmic assumptions by various satellite retrieval products and models, and identify where there is consistency and where there are differences. In general, the differences documented in this paper reflect uncertainties resulting from incomplete observational characterization of dust aerosols and limitations in our understanding. Second, we note what observations might reduce uncertainties in our knowledge and bring greater consistency to retrievals and models, allowing for a more rigorous and harmonious comparison. The lack of comprehensive and realistic shape models for dust is an outstanding issue, such that closure between forward modeling from particle refractive index, shape, and size and observed optical properties cannot be achieved. Limitations in the computational methods that must be applied to model scattering from complex shapes also makes accurate optical modeling for dust challenging. Field observations indicate the persistence of coarse and giant dust particles at higher altitudes and farther downwind from their source than previously expected. Remote sensing retrieval algorithms based on observations at visible wavelengths have limited sensitivity to these particles and generally do not consider them, although a recent product based on longwave radiances is encouraging. Current measurements of the refractive index of bulk dust and fundamental dust minerology components such as hematite vary widely, inhibiting attempts to represent the variability in dust optical properties and forcing, as expected from different major dust source regions on Earth that have varying mineralogical composition. Some remote sensing retrieval algorithms allow for limited refractive index variability in their inversion solutions through mixing with other fine mode aerosol models, or optimizing the single scattering albedo, but Earth system models surveyed for this paper assume a globally uniform, size-invariant refractive index. Although no Martian dust samples have yet been returned to Earth, remote sensing observations indicate that Martian dust is globally homogenous in composition, and a single spectral refractive index assumption has been widely adopted to represent Martian dust. The lack of comprehensive, statistically representative measurements of dust particle microphysical properties (size distribution, morphology, complex index of refraction spectra, internal structure heterogeneity), and the resulting optical properties, limits our ability to verify the fidelity of these assumptions. A chain of measurements is needed, ranging from characterizing individual dust mineralogy components (e.g., pure hematite and goethite) to in situ sampling of complex atmospheric aerosol mixtures. Such results could be applied to both remote sensing retrievals that characterize the optical properties of the total aerosol burden in the atmosphere from total radiance measurements, and to global models that represent the total aerosol burden in the atmosphere by building it up from the balance of individual aerosol sources and sinks.

Aeolian dust↗

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 those left wild. 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 established a comprehensive global consumption database directly linked to distinct fuels within various fire danger categories. This database, featuring a spatial resolution of approximately 300 meters, builds upon the foundations of the Pettinari, M. Lucrecia (2015) Global Fuelbed database, a global fuel map with standardized Fuel Characteristic Classification System (FCCS) biomass parameters. Consumption is broken down into five Fire Danger categories (Low, Moderate, High, Very High, Extreme), for both ‘new’ and ‘residual’ burning scenarios. We define ‘residual burned area’ as area burning in a region that has burned on a previous day for the same fire season, and ‘new burned area’ as area burning in a region that has not recently burned. This product serves as a valuable tool when used in conjunction with burned area data to rapidly estimate the carbon consumed and released into the atmosphere. Previously, we developed a similar emissions method utilizing satellite information, in conjunction with the FCCS 30-meter United States fuelbed dataset. We implemented this approach on fires, documented 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.

Emily Gargulinski↗

Aerosol Size Distribution Properties Associated With Cold-Air Outbreaks in the Norwegian Arctic

The aerosol particles serving as cloud condensation and ice nuclei contribute to key cloud processes associated with cold-air outbreak (CAO) events but are poorly constrained in climate models due to sparse observations. Here we retrieve aerosol number size distribution modes from measurements at Andenes, Norway, during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) and at Zeppelin Observatory, approximately 1000 km upwind from Andenes at Svalbard. During CAO events at Andenes, the sea-spray-mode number concentration is correlated with strong over-ocean winds with a mean of 8±4 cm−3 that is 71 % higher than during non-CAO conditions. Additionally, during CAO events at Andenes, the mean Hoppel minimum diameter is 6 nm smaller than during non-CAO conditions, though the estimated supersaturation is lower, and the mean number concentration of particles that likely activated in-cloud is 109±61 cm−3 with no statistically significant difference from the non-CAO mean of 99±66 cm−3. For CAO trajectories between Zeppelin Observatory and Andenes, the upwind-to-downwind change in number concentration is the largest for the accumulation mode with a mean decrease of 93±95 cm−3, likely attributable primarily to precipitation scavenging. These characteristic properties of aerosol number size distributions during CAO events provide guidance for evaluating CAO aerosol–cloud interaction processes in models.

accumulation mode particle scavenging↗

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↗

Modeling Large Dust Aerosols in the Community Earth System Model Version 2 (CESM2)

Dust aerosols have a wide size distribution from less than 0.1 to over 100 μm and dominate Earth's atmospheric aerosol mass. However, most Earth system models (ESMs) inadequately represent dust aerosols larger than 10 μm in diameter, limiting the accuracy of the simulated dust cycle and climate impacts. Here, we introduce a new modeling framework that captures the full observed size distribution of dust aerosols, incorporating recent advances into a mineral-resolved version of the Community ESM, while addressing known issues in previous versions. Comprehensive evaluation against diverse observations of bulk dust and component minerals demonstrates that the model reproduces the observed dust cycle across particle sizes. Incorporating the previously unrepresented large-dust fractions substantially alters dust budget estimates, highlighting potential changes in simulated climate impacts and underscoring the importance of comprehensive size-resolved dust modeling. Despite these advancements, uncertainties persist. Our results indicate that a size-dependent reduction in settling velocity is required to reproduce the observed dust size distribution downwind of source regions. Specifically, in the new model, the gravitational settling velocity of dust particles larger than 10 μm in diameter must be reduced by as much as 85% to achieve agreement with observations. This empirical reduction serves as a constraint on physics-based models of dust settling. Future developments should address misrepresented physical processes that hinder accurate modeling of the large dust aerosol transport. Expanding observational data sets covering the full-size distribution is also essential to better constrain the dust cycle and improve the representation of dust optical properties and climate effects.

mineral dust↗

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

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

Xiaohua Pan↗