SEARCH · Search NASA

Results for “Wildfire Modeling”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

NASA NTRS2014

NLDAS Views of North American 2011 Extreme Events

2011 was marked as one of the most extreme years in recent history. Over the course of the year, weather-related extreme events, such as floods, heat waves, blizzards, tornadoes, and wildfires, caused tremendous loss of human life and property. The North American Land Data Assimilation System (NLDAS, http:ldas.gsfc.nasa.govnldas) data set, with high spatial and temporal resolutions (0.125 x 0.125, hourly) and various water- and energy-related variables, is an excellent data source for case studies of extreme events. This presentation illustrates some extreme events from 2011 in North America, including the Groundhog Day Blizzard, the July heat wave, Hurricane Irene, and Tropical Storm Lee, all utilizing NLDAS Phase 2 (NLDAS-2) data.

hydrology↗

NASA NTRS2022

Compound Effects of Climate Change on Future Transboundary Water Issues in the Middle East

The Middle East is one of the world’s most vulnerable areas to climate change, which has exacerbated environmental, agricultural, water conflict, and public health issues in the region. Here we analyze the latest climate model projections of precipitation and temperature for the very high emissions scenario, SSP5-8.5,to detect potential future changes in this region. A baseline period (1981-2010) is compared with the middle(2040-2069) and end (2070-2099) of the 21stcentury. The results, representing the worst-case scenario, identify the Tigris-Euphrates headwaters as the hotspot of future compounding effects of climate change in the Middle East. Those effects result from the coincidence of elevated temperature, reduced precipitation, and enhanced interannual variability of precipitation. The hotspot overlays the location of the Southeastern Anatolia Project (in Turkish, GAP) irrigation initiative. In this climate context, risks to GAP viability and downstream water security, and associated potential for water-related conflicts and migration are considerable and demand a reconsideration of the risk-benefit assessment of GAP. This need has become more urgent after the recent widespread and deadly climate-related conflicts and wildfires in summer 2021 across the Middle East that further underlined vulnerability of the region to climate extremes.

Tigris-Euphrates headwater↗

NASA NTRSDate not supplied

What (and How) MERRA-2 Reanalysis Data are Used in Applied Sciences

The Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) is the global atmospheric data reanalysis for the satellite era produced by NASA’s Global Modeling and Assimilation Office (GMAO), using the Goddard Earth Observing System Model (GEOS)version 5.12.4. The data are officially distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data have been widely used by the Earth sciences and application community. Since MERRA-2 data were released in early 2016, the number of registered data users has grown steadily from 1,252 in 2016 to 6477 in 2020. By the end of October 2021, ~16 petabytes (over 360 million files) of data have been distributed to more than 18,900 users. Searching in Google Scholar (https://scholar.google.com/), we have found over 7,000 articles, published between January 2017 and May 2021, involving the use ofMERRA-2 data. The figure shows the numbers for various application areas in which theMERRA-2 data have been used, covering almost all of the application areas defined in NASA Applied Sciences (http://appliedsciences.nasa.gov). The largest number of articles are found in disaster research, with the subcategories ordered in flood, wildfires, hurricanes and cyclones, and other forms of severe weather. In this presentation, we will discuss the preliminary findings from a review of the selected literature that uses MERRA-2 data in applied sciences. The current analytic and interoperable data services at GES DISC are listed, such as the on-the-fly subset and analysis service, NASA Giovanni; THREDDS Data Server(TDS); and Python Jupyter notebooks. In addition, we will introduce two new services for supporting the open sciences: My Dashboard and Related Publications.

data management↗

NASA NTRS2015

Trend Estimates of AERONET-Observed and Model-Simulated AOTs Between 1993 and 2013

Recently, temporal changes in Aerosol Optical Thickness (AOT) have been investigated based on model simulations, satellite and ground-based observations. Most AOT trend studies used monthly or annual arithmetic means that discard details of the generally right-skewed AOT distributions. Potentially, such results can be biased by extreme values (including outliers). This study additionally uses percentiles (i.e., the lowest 5%, 25%, 50%, 75% and 95% of the monthly cumulative distributions fitted to Aerosol Robotic Network (AERONET)-observed and ECHAM/MESSy Atmospheric Chemistry (EMAC)-model simulated AOTs) that are less affected by outliers caused by measurement error, cloud contamination and occasional extreme aerosol events. Since the limited statistical representativeness of monthly percentiles and means can lead to bias, this study adopts the number of observations as a weighting factor, which improves the statistical robustness of trend estimates. By analyzing the aerosol composition of AERONET-observed and EMAC-simulated AOTs in selected regions of interest, we distinguish the dominant aerosol types and investigate the causes of regional AOT trends. The simulated and observed trends are generally consistent with a high correlation coefficient (R = 0.89) and small bias (slope+/-2(sigma) = 0.75 +/- 0.19). A significant decrease in EMAC-decomposed AOTs by water-soluble compounds and black carbon is found over the USA and the EU due to environmental regulation. In particular, a clear reversal in the AERONET AOT trend percentiles is found over the USA, probably related to the AOT diurnal cycle and the frequency of wildfires. In most of the selected regions of interest, EMAC-simulated trends are mainly attributed to the significant changes of the dominant aerosols; e.g., significant decrease in sea salt and water soluble compounds over Central America, increase in dust over Northern Africa and Middle East, and decrease in black carbon and organic carbon over Australia.

AERONET↗

NASA NTRS2017

Mitigating Satellite-Based Fire Sampling Limitations in Deriving Biomass Burning Emission Rates: Application to WRF-Chem Model over the Northern sub-Saharan African Region

Largely used in several independent estimates of fire emissions, fire products based on MODIS sensors aboard the Terra and Aqua polar-orbiting satellites have a number of inherent limitations, including (a) inability to detect fires below clouds, (b) significant decrease of detection sensitivity at the edge of scan where pixel sizes are much larger than at nadir, and (c) gaps between adjacent swaths in tropical regions. To remedy these limitations, an empirical method is developed here and applied to correct fire emission estimates based on MODIS pixel level fire radiative power measurements and emission coefficients from the Fire Energetics and Emissions Research (FEER) biomass burning emission inventory. The analysis was performed for January 2010 over the northern sub-Saharan African region. Simulations from WRF-Chem model using original and adjusted emissions are compared with the aerosol optical depth (AOD) products from MODIS and AERONET as well as aerosol vertical profile from CALIOP data. The comparison confirmed an 30-50% improvement in the model simulation performance (in terms of correlation, bias, and spatial pattern of AOD with respect to observations) by the adjusted emissions that not only increases the original emission amount by a factor of two but also results in the spatially continuous estimates of instantaneous fire emissions at daily time scales. Such improvement cannot be achieved by simply scaling the original emission across the study domain. Even with this improvement, a factor of two underestimations still exists in the modeled AOD, which is within the current global fire emissions uncertainty envelope. Plain Language Summary Polar-orbiting satellites sensors, such as MODIS, have limitations in detecting fires under clouds or when viewing angles are large or in the gaps among satellites' different ground swaths. Here we developed an empirical method to mitigate the effect of these limitations in fire emission estimate. The method is applied to a fire emission inventory (FEER) based on MODIS. We show that, with our method, the adjusted emission inventory improves WRF-Chem simulation of smoke transport and distribution.

emissions properties↗

NASA NTRS2011

Reducing the Uncertainties in Direct Aerosol Radiative Forcing

Airborne particles, which include desert and soil dust, wildfire smoke, sea salt, volcanic ash, black carbon, natural and anthropogenic sulfate, nitrate, and organic aerosol, affect Earth's climate, in part by reflecting and absorbing sunlight. This paper reviews current status, and evaluates future prospects for reducing the uncertainty aerosols contribute to the energy budget of Earth, which at present represents a leading factor limiting the quality of climate predictions. Information from satellites is critical for this work, because they provide frequent, global coverage of the diverse and variable atmospheric aerosol load. Both aerosol amount and type must be determined. Satellites are very close to measuring aerosol amount at the level-of-accuracy needed, but aerosol type, especially how bright the airborne particles are, cannot be constrained adequately by current techniques. However, satellite instruments can map out aerosol air mass type, which is a qualitative classification rather than a quantitative measurement, and targeted suborbital measurements can provide the required particle property detail. So combining satellite and suborbital measurements, and then using this combination to constrain climate models, will produce a major advance in climate prediction.

Kahn, Ralph A.↗

NASA NTRS2014

Stereoscopic Retrieval of Smoke Plume Heights and Motion from Space-Based Multi-Angle Imaging, Using the MISR INteractive eXplorer(MINX)

Airborne particles desert dust, wildfire smoke, volcanic effluent, urban pollution affect Earth's climate as well as air quality and health. They are found in the atmosphere all over the planet, but vary immensely in amount and properties with season and location. Most aerosol particles are injected into the near-surface boundary layer, but some, especially wildfire smoke, desert dust and volcanic ash, can be injected higher into the atmosphere, where they can stay aloft longer, travel farther, produce larger climate effects, and possibly affect human and ecosystem health far downwind. So monitoring aerosol injection height globally can make important contributions to climate science and air quality studies. The Multi-angle Imaging Spectro-Radiometer (MISR) is a space borne instrument designed to study Earths clouds, aerosols, and surface. Since late February 2000 it has been retrieving aerosol particle amount and properties, as well as cloud height and wind data, globally, about once per week. The MINX visualization and analysis tool complements the operational MISR data products, enabling users to retrieve heights and winds locally for detailed studies of smoke plumes, at higher spatial resolution and with greater precision than the operational product and other space-based, passive remote sensing techniques. MINX software is being used to provide plume height statistics for climatological studies as well as to investigate the dynamics of individual plumes, and to provide parameterizations for climate modeling.

aerosols↗

NASA NTRS2011

Emissions of Black Carbon, Organic, and Inorganic Aerosols From Biomass Burning in North America and Asia in 2008

Reliable assessment of the impact of aerosols emitted from boreal forest fires on the Arctic climate necessitates improved understanding of emissions and the microphysical properties of carbonaceous (black carbon (BC) and organic aerosols (OA)) and inorganic aerosols. The size distributions of BC were measured by an SP2 based on the laser-induced incandescence technique on board the DC-8 aircraft during the NASA ARCTAS campaign. Aircraft sampling was made in fresh plumes strongly impacted by wildfires in North America (Canada and California) in summer 2008 and in those transported from Asia (Siberia in Russia and Kazakhstan) in spring 2008. We extracted biomass burning plumes using particle and tracer (CO, CH3CN, and CH2Cl2) data. OA constituted the dominant fraction of aerosols mass in the submicron range. The large majority of the emitted particles did not contain BC. We related the combustion phase of the fire as represented by the modified combustion efficiency (MCE) to the emission ratios between BC and other species. In particular, we derived the average emission ratios of BC/CO = 2.3 +/- 2.2 and 8.5 +/- 5.4 ng/cu m/ppbv for BB in North America and Asia, respectively. The difference in the BC/CO emission ratios is likely due to the difference in MCE. The count median diameters and geometric standard deviations of the lognormal size distribution of BC in the BB plumes were 136-141 nm and 1.32-1.36, respectively, and depended little on MCE. These BC particles were thickly coated, with shell/core ratios of 1.3-1.6. These parameters can be used directly for improving model estimates of the impact of BB in the Arctic.

Kondo, Y.↗

NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

The impact of wildfire incidents has been growing in recent years, posing a serious threat to communities at the urban-wildland interface. To address this problem, there have been growing calls to use UAVs to increase the capacity of responsible agencies to quickly and effectively suppress fires and to reduce risks associated with firefighting. One of the opportunities associated with UAVs is the ability to rapidly and autonomously operate from limited-access air bases where fires are expected to burn. This study provides an approach to determine where these air bases should be placed in order to most rapidly extinguish fires, given provided fuel distributions. This approach uses an integrated simulation of fire propagation and UAV-based suppression actions to determine how much of a given environment was burned over a range of scenarios. It then uses an optimization method to explore the space and determine the location with the least burned area. Results show the approach to efficiently and effectively provide optimal bases for single-base placements over a range of scenarios, though future work is required to adequately calibrate the model and study how it can be used in multiple-base placement problems.

Daniel Hulse↗

NASA NTRSDate not supplied

Determining Optimal Asset Location for Rapid and Efficient Wildfire Suppression: A Simulation-Based Approach

Daniel Hulse↗

NASA NTRS2005

Automated Wildfire Detection Through Artificial Neural Networks

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.

Miller, Jerry↗

NASA NTRS2008

A View of Earth's Aerosol System from Space to Your Office Chair

Aerosols are tiny particles and droplets suspended in the air. Each day you breathe in about 10 billion of them, about a half a million per breath. They are formed in nature by volcanoes, dust storms, sea spray, and emissions from vegetation. Humans create aerosols and alter their natural sources by burning fossil fuels and modifying land cover. Fires are another important source of aerosols; some are natural, such as wildfires started by lightning strikes, while others are from human-caused burning of vegetation for cooking, heating, and land clearing. Aerosols have complex effects on Earth's climate. In general, they cool the surface by reflecting (scattering) radiation from the sun back into space. Dust and smoke absorb solar radiation and heat the atmosphere where they are concentrated. Aerosols change the properties of clouds. Indeed, it would be very difficult to form clouds in the atmosphere without aerosols to act as 'seeds' for water to condense on. In aerosol polluted environments clouds tend to have smaller droplets than clouds formed in cleaner environments; these polluted clouds appear brighter from space because they reflect more sunlight, and they may persist longer and not rain as intensely. Aerosols also affect local air quality and visibility. Data collected by NASA satellites over the past decade have provided an unprecedented view of Earth's aerosol distribution and dramatically increased our understanding of where aerosols come from and just how far they travel in the atmosphere. In this talk I will discuss observations of aerosols from space and how they inform numerical transport models attempting to simulate the global aerosol system.

Colarco, Peter↗

NASA NTRSDate not supplied

Openet: Applications of Satellite-Based Evapotranspiration Data for Water Resources Management in the Western United States

Advancing water security in overallocated river basins globally requires consistent and reproducible information on consumptive use of water that can anchor the development of data-driven solutions to the challenge of balancing water supply and demand. OpenET is a fully automated system for field-scale (30 m), satellite-based mapping of evapotranspiration (ET) at daily, monthly and annual timesteps. OpenET currently provides spatially contiguous data throughout the 23 westernmost states in the continental US, and includes both current information as well as multi-year timeseries of ET. The OpenET consortium has implemented an ensemble of satellite-based ET models (ALEXI/DisALEXI, eeMETRIC, PT-JPL, geeSEBAL, SIMS and SSEBop) on Google Earth Engine, which provides a shared computing platform for collaboration on processing of data from Landsat and other satellites, land cover and meteorological inputs, leading to increased consistency and accuracy across the ensemble of models. Earth Engine also facilitates hosting and distribution of data via open data collections and an application programming interface. We provide updates on the OpenET framework, open data services and data access tools, approach to geographic expansion, recent accuracy assessments, and describe how a user-driven design approach has facilitated successful applications of OpenET data for a wide range of water resource management activities. Applications to date include: use of ET data to improve quantification of ET and consumptive use in Oregon, Utah and the Upper Colorado River Basin; streamlining of water use reporting requirements in the California Delta; support for calculation of water budgets for the implementation of the Sustainable Groundwater Management Act in California; and integration into decision support tools for irrigation management. The use cases demonstrate how satellite-derived ET data that are easily accessed and seen as broadly accepted can accelerate adoption of innovative water management practices at scale, and support advances in the sustainability of water supplies. Uptake and use of data by the OpenET science community has also led to advances in our understanding of the impacts of landcover change, irrigation intensification and wildfire events on hydrology and the water security.

Applications↗

NASA NTRS2023

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential for mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. For this project, NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail travel and U.S.-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986-2022. Using data from Landsat 5 and 8, Sentinel-2, NAIP, and PlanetScope, the team computed NDVI, NDMI, MSAVI2, EVI, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on vegetation indices and spectral bands before running k-means clustering and random forest classification algorithms. Between all datasets, the team found that the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants, and this project can serve as a jumping off point for future invasive species monitoring. The NPS’s collection of ground data for 2022-2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive species spread over time.

Coronado National Memorial↗

NASA NTRSDate not supplied

Ensemble Forecasting/Assimilation/Emissions Estimation with WRF-Chem/DART: Accomplishments, Lessons Learned, and Future Plans

Over the past ten years, we have been conducting research on regional ensemble atmospheric composition forecasting/data assimilation/emissions estimation with WRF-Chem/DART. WRF- Chem/DART integrates the Weather Research and Forecasting model (WRF) with online chemistry (WRF-Chem) into the Data Assimilation Research Testbed (DART). DART is an ensemble data assimilation system based on the ensemble adjustment Kalman filter (EAKF) with adaptive inflation, localization (physical and state space), and an optional non-Gaussian formulation of the EAKF. DART includes assimilation of meteorological and limited chemical observations. WRF-Chem/DART extends DART to include assimilation of: MOPITT CO; IASI CO and O3; MODIS AOD; OMI O3, NO2, and SO2; TROPOMI CO, O3, NO2, and SO2, TES CO, CO2 (research mode), O3, NH3, and CH4 (research mode); CrIS CO, O3, NH3, CH4 (research mode), and PAN; SCIAMACHY NO2; GOME2a NO2; MLS O3 and HNO3; and proxy TEMPO O3, and NO2 satellite retrievals as raw retrievals or as ‘compact phase space retrievals’ (CPSRs) for profile retrievals. WRF-Chem/DART also assimilates in situ atmospheric composition measurements and uses the ‘state augmentation method’ for emissions estimation. In our presentation, we will provide an overview of WRF-Chem/DART: • applications and results; • lessons learned from: (i) independent versus joint assimilation; (ii) total/partial column versus profile retrieval assimilation; (iii) joint in situ and retrieval assimilation; (iv) assimilation at grid resolutions ranging from 100 km to 4 km; (v) dynamic emissions estimation; and • future work related to wildfire emissions estimation and intercomparison of CMAQ (online)/JEDI and CMAQ (online and offline)/DART.

WRF-Chem/DART↗

NASA NTRSDate not supplied

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential in mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail walking and US-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986 to 2022. Using data from Landsat 5 and 8, Sentinel-2, the National Agriculture Imagery Program, and PlanetScope, the team computed vegetation indices including the Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Modified Soil Adjusted Vegetation Index 2, Enhanced Vegetation Index, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on the vegetation indices and spectral bands before running k-means++ clustering and random forest classification algorithms. Between all datasets, we found the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use the end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants. The NPS’s collection of ground data for 2022–2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive spread over time.

Carson Schuetze↗

NASA NTRSDate not supplied

Towards Real-time Global Assessment of Post-fire Debris Flow Hazard

As the risk of wildfires increases worldwide, burned steeplands are vulnerable to the secondary hazard of widespread sediment mobilization through debris flows. Following an initial burn, sediment and soil previously restrained by vegetation are no longer consolidated, allowing for easy mobilization into channels and along steep hillslopes through runoff. Sufficiently powerful rainfall incorporates entrained material into turbulent flows and serves as the primary trigger for debris flow initiation. There is thus an ongoing need to establish the relationship between rainfall and debris flow initiation based on a variety of spatiotemporal preconditions. Previous work establishes regional and local thresholds to constrain the effect of rainfall in recently burned areas, but no empirical or numerical solution has worldwide application. Building from regionally-based efforts in the U.S., this work considers how remote sensing data can be applied to better approximate the post-fire debris flow hazards worldwide using freely available global datasets and software. Our work assesses the utility of remote sensing resources for analyzing burn characteristics, topography, rainfall intensity/duration, and, thus, debris flow initiation. Early results show that global observations are sufficient to delineate background rainfall rates from storms likely to cause debris flows across a variety of burn severity and topographic conditions. However, the dearth of publicly-available post-fire debris flow inventories globally limit the ability to test how the model framework performs within different climatologic and morphologic areas. This work will present preliminary analysis over the Western United States and demonstrate the feasibility of a global, near-real time model to provide situational awareness of potential hazards within recently burned areas worldwide. Future work will also consider how global or regional precipitation forecasts may increase the lead time for improved early warning of these hazards.

Elijah Orland↗

NASA NTRSDate not supplied

Latest Progress and Results in LEO-GEO and GEO-GEO Stereo AMVs

Atmospheric motion vectors (AMVs), derived by tracking patterns, represent the winds in a layer characteristic of the pattern. AMV height (or pressure), important for applications in atmospheric research and operational meteorology, is usually assigned using observed IR brightness temperatures with a modeled atmosphere and can be inaccurate. Stereoscopic tracking provides a direct geometric height measurement of the pattern that an AMV represents. We extend our previous work with multi-angle imaging spectro–radiometer (MISR) and GOES to moderate resolution imaging spectroradiometer (MODIS) and the GOES-R series advanced baseline imager (ABI). MISR is a unique satellite instrument for stereoscopy with nine angular views along track, but its images have a narrow (380 km) swath and no thermal IR channels. MODIS provides a much wider (2330 km) swath and eight thermal IR channels that pair well with all but two ABI channels, offering a rich set of potential applications. Given the similarities between MODIS and VIIRS, our methods should also yield similar performance with VIIRS. Our methods, as enabled by advanced sensors like MODIS and ABI, require high-accuracy geographic registration in both systems but no synchronization of observations. AMVs are retrieved jointly with their heights from the disparities between triplets of ABI scenes and the paired MODIS granule. We validate our retrievals against MISR-GOES retrievals, operational GOES wind products, and by tracking clear-sky terrain. We demonstrate that the 3D-wind algorithm can produce high-quality AMV and height measurements for applications from the planetary boundary layer (PBL) to the upper troposphere, including cold-air outbreaks, wildfire smoke plumes, and hurricanes.

Atmospheric motion vectors↗