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The 2019 Raikoke eruption: Can smoke and Sulfuric acid aerosol be separated?
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Ground-based in situ Hyperspectral Optical Measurements of Smoke Aerosols during FIREX-AQ, Relating Spectral Characteristics to Aerosol Composition, Fuels, and Fire State
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Stratospheric Smoke Optical Properties and Complex Transport after the 2019/2020 Australian Bushfires
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Stratospheric Smoke Optical Properties and Complex Transport after the 2019/2020 Australian Bushfires
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Dynamic fire and smoke detection and classification for flashover prediction
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Colorado Springs Health & Air Quality: Using Earth Observations to Monitor Wildfire Smoke and Air Pollution for Enhanced Air Quality Management in Colorado Springs, Colorado
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Self-Similar Outflows at the Source of the Fast Solar Wind: A Smoking Gun of Multiscale Impulsive Reconnection?
We present results of a quantitative analysis of structured plasma outflows above a polar coronal hole observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) spacecraft. In a 6 hr interval of continuous high-cadence SDO/AIA images, we identified more than 2300 episodes of small-scale plasma flows in the polar corona. The mean upward flow speed measured by the surfing transform technique is estimated to be 122 ± 34 km s−1, which is comparable to the local sound speed. The typical recurrence period of the flow episodes is 10–30 minutes, and the mean duration and transverse size of each episode are about 3–5 minutes and 3–4 Mm, respectively. The largest identifiable episodes last for tens of minutes and reach widths up to 40 Mm. For the first time, we demonstrate that the polar coronal-hole outflows obey a family of power-law probability distributions characteristic of impulsive interchange magnetic reconnection. Turbulent photospheric driving may play a crucial role in releasing magnetically confined plasma onto open field. The estimated occurrence rate of the detected self-similar coronal outflows is sufficient for them to make a dominant contribution to the fast-wind mass and energy fluxes and to account for the wind's small-scale structure.
Quantifying Burned Area and Smoke from Prescribed and Smaller Fires: West Palm Beach, Florida
In the Central and Southeastern U.S. (C&SE), small, short-lived fires are often underestimated by satellites due to their size, timing, cloud cover, and rapid regrowth or plowing after burns. Satellite data are essential for the National Emissions Inventory, as ground-based inventories are historically incomplete and geographically inconsistent. Agricultural burning, a widespread annual practice in many U.S. regions, significantly impacts air quality on local to regional scales. As part of NASA’s Health and Air Quality Applied Sciences (HAQAST) team, we develop a burned area inventory to account for these ‘missing’ small fires. Our study focuses on West Palm Beach, FL, near Lake Okeechobee, where agriculture fields are burned annually fall-spring for crop management and harvest. This region poses challenges for satellite detection due to frequent rain, flooding, and cloud cover.
Heat flux assumptions contribute to overestimation of wildfire smoke injection into the free troposphere
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Smoke absorption retrieval algorithm using critical reflectance method with geostationary satellite over North America
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CALIPSO inferred most probable heights of global dust and smoke layers
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Development and Application of Self-Supervised Machine Learning for Smoke Plume and Active Fire Identification from the Fire Influence on Regional to Global Environments and Air Quality Datasets
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Impact of Smoke Aerosol Loading on Lightning Characteristics of Pyrocumulonimbus Compared With Other High‐Based Thunderstorms
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Estimated impacts of forest restoration scenarios on smoke exposures among outdoor agricultural workers in California
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Aerosol Mass and Optical Properties, Smoke Influence on O 3 , and High NO 3 Production Rates in a Western U.S. City Impacted by Wildfires
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Mesoscale modeling of smoke transport from equatorial Southeast Asian Maritime Continent to the Philippines: First comparison of ensemble analysis with in situ observations
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