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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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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2026

Satellite Optical Remote Sensing of Clouds and Aerosols: From Particle Single-Scattering and Gaseous Absorption Through Radiative Transfer to Retrieval Products

Clouds and aerosols are fundamental regulators of Earth’s radiation budget and climate system, influencing both solar and terrestrial radiation through scattering, absorption, and emission processes. Accurate characterization of their physical and radiative properties from space requires a rigorous understanding of particle single-scattering, gaseous absorption, and radiative transfer in the atmosphere, as well as reliable inversion methods. This review synthesizes the physical foundations and algorithmic implementations of satellite-based passive optical remote sensing of clouds and aerosols, spanning the ultraviolet to thermal infrared spectral range. Beginning with electromagnetic scattering theory and state-of-the-art methods for computing single-scattering by nonspherical particles and computationally efficient methods for accounting for atmospheric absorption, we discuss the radiative transfer framework underpinning cloud and aerosol retrievals. The connection between single-scattering and multiple-scattering is rigorously formulated. We then summarize operational and research-grade retrieval techniques, including cloud masking and thermodynamic phase determination, CO₂ slicing for cloud-top pressure, the Nakajima-King shortwave bi-spectral, and infrared split-window approaches for cloud optical thickness and effective particle size, inversion algorithms for determining aerosol properties from multi-spectral and/or multi-angle radiometric and polarimetric measurements, and active-passive sensing synergy. Examples of the global cloud and aerosol climatologies are illustrated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR). Furthermore, the unique strengths of active remote sensing techniques based on spaceborne lidar observations are briefly elaborated in the context of studying ice clouds composed of randomly and horizontally oriented ice crystals, which is a significant challenge for conventional passive remote sensing techniques. By connecting physical theory to practical retrievals, this review highlights both the maturity of current methodologies and the remaining challenges in reducing uncertainties in particle morphology, vertical structure, absorption, and aerosol-cloud interactions. Furthermore, the impact of artificial intelligence (AI) on atmospheric remote sensing is briefly addressed.

Aerosols↗
NASA NTRS2005

Status of the MODIS Level 1B Algorithms and Calibration Tables

The Moderate Resolution Imaging Spectroradiometer (MODIS) makes observations using 36 spectral bands with wavelengths from 0.41 to 14.4 m and nadir spatial resolutions of 0.25km, 0.5km, and 1km. It is currently operating onboard the NASA Earth Observing System (EOS) Terra and Aqua satellites, launched in December 1999 and May 2002, respectively. The MODIS Level 1B (L1B) program converts the sensor's on-orbit responses in digital numbers to radiometrically calibrated and geo-located data products for the duration of each mission. Its primary data products are top of the atmosphere (TOA) reflectance factors for the sensor's reflective solar bands (RSB) and TOA spectral radiances for the thermal emissive bands (TEB). The L1B algorithms perform the TEB calibration on a scan-by-scan basis using the sensor's response to the on-board blackbody (BB) and other parameters which are stored in Lookup Tables (LUTs). The RSB calibration coefficients are processed offline and regularly updated through LUTs. In this paper we provide a brief description of the MODIS L1B calibration algorithms and associated LUTs with emphasis on their recent improvements and updates developed for the MODIS collection 5 processing. We will also discuss sensor on-orbit calibration and performance issues that are critical to maintaining L1B data product quality, such as changes in the sensor's response versus scan-angle.

MODIS LEVEL 1B ALGORITHMS↗
DOE OSTI2025

Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin

This data package is associated with the publication “Ecosystem leaf area, gross primary production, and evapotranspiration responses to wildfire in the Columbia River Basin” submitted to Biogeosciences (Shi et al., 2024; doi: 10.22541/au.171053013.30286044/v1). In this research, data products, leaf area index (LAI), gross primary production (GPP), and evapotranspiration (ET), from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to quantify the resistance and resilience of different ecosystem types in the Columbia River Basin (CRB). A machine learning algorithm, random forest (RF), was used to examine the impacts of precipitation, vapor pressure deficit (VPD), and burn severity from Monitoring Trends in Burn Severity (MTBS) on ecosystem resilience. The data package includes the processed MODIS data products, precipitation, VPD, and burn severity in 138 fire regions in CRB and the input files for RF model training. This data package includes six folders. The MODIS products are included in three MODIS_* folders with shell scripts for data clipping and *ncl files for data processing: (1) “/MODIS_LAI_CRB”; (2) “/MODIS_GPP_CRB”; and (3) “/MODIS_ET_CRB”. All the processed data for each fire event are NetCDF formatted. The MTBS burn severity data and the shell and *ncl scripts used for data processing are in the folder named (4) “MTBS_fire”. The ERA meteorological fields and the data processing scritps are in (5) “ERA_Var_CR”. All the scripts for figure development are in the format of *ncl and in the folder (6) “paper_scripts”. See the file ending in “flmd.csv” for a list of all files contained in this data package and descriptions for each. Tabular column headers and units are described in the data dictionary file ending in “dd.csv”.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Snow ALbedo eVOlution (SALVO) Campaign Spectral Albedo and Related Measurements from April - June, 2024 in Utqiagivk, AK

A field-portable spectroradiometer, referred to herein as an ‘ASD’, was used to make spatially-distributed spectral albedo (350 – 2500 nm) measurements on tundra and sea ice surfaces. The ASD detector is carried in a backpack and controlled via a computer mounted on the front of the operator (see Figure 1). The ASD measures the spectral irradiance from a fiber optic cable that is routed from the backpack to a custom, gooseneck cosine collector mounted on the end of a 1-m long boom (Grenfell and Perovich, 2008). The boom was held at hip height (approximately 1 m) and had an integrated bubble level for levelling. To make an albedo measurement, first the operator collect an incident (down-welling) irradiance, followed by a reflected (up-welling) measurement. The time between incident and reflected measurements was typically between 11 and 26 seconds (interquartile range). For each measurement, 10 spectra are averaged together. Albedo is calculated as the ratio of the reflected to incident measurement, which obviates the need for absolute radiometric calibration. Albedo measurements were taken parallel to the 200-m albedo lines at 5-m increments (41 measurements) ~1 m south of the line. While the ASD operator was making measurements, an assistant kept notes on the scan number associated with each measurement, the surface type (see below), and collected photos of each measurement (see companion oblique photos data archive). Measurements were made within 3 hours of solar noon.

ASD Spectroradiometer↗
NASA NTRS1995

Sensitivity of Multi-Angle Remote Sensing Observations to Aerosol Sphericity

Multi-angle, multi-spectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) Multi-angle Imaging SpectroRadiometer (MISR), can distinguish spherical from non-spherical particles over calm ocean for mineral-dust-like particles with the range of sizes and column amounts expected under natural conditions. The ability to make such distinctions is critical if remote sensing of atmospheric aerosol properties is to provide significant new contributions to our understanding of the global-scale, clear-sky solar radiation balance.

MISR aerosol aerosol properties↗
NASA NTRS1999

A Spectralon BRF Data Base for MISR Calibration Application

The Multi-angle Imaging SpectroRadiometer (MISR) is an Earth observing sensor which will provide global retrievals of aerosols, clouds, and land surface parameters. Instrument specifications require high accuracy absolute calibration, as well as accurate camera-to-camera, band-to-band and pixel-to-pixel relative response determinations.

spectralon MISR spectroradiometer remote sensing↗
NASA NTRS1999

Science Quality Assessment in Support of EOS MISR Data

The Multi-angle Imaging SpectroRadiometer (MISR) instrument, scheduled to fly on board the first Earth Observing System (EOS) spacecraft, will have a data stream that produces over 100 GB of data per day, once in full operation, of information about the Earth's atmosphere, clouds, and surface.

remote sensing Multi-angle Imaging SpectroRadiomet↗
NASA NTRS2004

Performance Expectations for Future Moderate Resolution Visible and Infrared Space Instruments Based on AIRS and MODIS In-Flight Experience

Lessons learned from the Atmospheric Infrared Sounder (AIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) projects highlight areas where further technology development is needed to address future land, ocean and atmospheric measurement needs. Although not established as requirements at this time, it is anticipated that scientists will expect improvements in the areas of spatial, spectral, radiometric, polarimetric, temporal and calibration performance for future sensors. This paper addresses each of these performance areas and provides lessons learned from MODIS and AIRS. We also present expectations in performance of the system based on information from NASA Instrument Incubator Program and industry reports. Tradeoffs are presented vs orbit altitude (LEO, ME0 and GEO) and provide a 'systems' perspective to future measurement concepts.

Infrared↗
NASA NTRS2005

Evaluation of MISR Land Surface BRF Measurements: Intercomparison with Coincident Airborne and Ground Field Measurements

The bidirectional reflectance factor, BRF, retrieved by the Multiangle Imaging SpectroRadiometer, MISR, is compared with those coincidently measured from aircraft, by the Cloud Absorption Radiometer, CAR, and MISR airborne simulator, AirMISR, and on the ground, by the Portable Apparatus for Rabid Acquisition of Bidirectional Observations of Land and Atmosphere, PARABOLA Ill. The intercomparisons are made for six types of surfaces: bright desert, salt pans, grassland, forests, snow and the Dismal Swamp. The results show that MISR BRF values are mostly within +/- 10% in agreement with the corresponding airborne and ground measurements, independent of the surface types This study is part of an effort to evaluate and validate MISR surface products.

Multiangle Imaging SpectroRadiometer (MISR)↗
NASA NTRS2012

MISR 17.6 KM Gridded Cloud Motion Vectors: Overview and Assessment

The MISR (Multi-angle Imaging SpectroRadiometer) instrument on the Terra satellite has been retrieving cloud motion vectors (CMVs) globally and almost continuously since early in 2000. In February 2012 the new MISR Level 2 Cloud product was publicly released, providing cloud motion vectors at 17.6 km resolution with improved accuracy and roughly threefold increased coverage relative to the 70.4 km resolution vectors of the current MISR Level 2 Stereo product (which remains available). MISR retrieves both horizontal cloud motion and height from the apparent displacement due to parallax and movement of cloud features across three visible channel (670nm) camera views over a span of 200 seconds. The retrieval has comparable accuracy to operational atmospheric motion vectors from other current sensors, but holds the additional advantage of global coverage and finer precision height retrieval that is insensitive to radiometric calibration. The MISR mission is expected to continue operation for many more years, possibly until 2019, and Level 2 Cloud has the possibility of being produced with a sensing-to-availability lag of 5 hours. This report compares MISR CMV with collocated motion vectors from arctic rawinsonde sites, and from the GOES and MODISTerra instruments. CMV at heights below 3 km exhibit the smallest differences, as small as 3.3 m/s for MISR and GOES. Clouds above 3 km exhibit larger differences, as large as 8.9 m/s for MISR and MODIS. Typical differences are on the order of 6 m/s.

MISR (Multi-angle Imaging SpectroRadiometer)↗
NASA NTRS2012

MISR Decadal Observations of Mineral Dust: Property Characterization and Climate Applications

The Multi-angle Imaging SpectroRadiometer (MISR) provides a unique, independent source of data for studying dust emission and transport. MISR's multiple view angles allow the retrieval of aerosol properties over bright surfaces, and such retrievals have been shown to be sensitive to the non-sphericity of dust aerosols over both land and water. MISR stereographic views of thick aerosol plumes allow height and instantaneous wind derivations at spatial resolutions of better than 1.1 km horizontally and ~200m vertically. We will discuss the radiometric and stereo-retrieval capabilities of MISR specifically for dust, and demonstrate the use of MISR data in conjunction with other available satellite observations for dust property characterization and climate studies.First, we will discuss MISR non-spherical (dust) fraction product over the global oceans. We will show that over the Atlantic Ocean, changes in the MISR-derived non-spherical AOD fraction illustrate the evolution of dust during transport. Next, we will present a MISR satellite perspective on dust climatology in major dust source regions with a particular emphasis on the West Africa and Middle East and discuss MISR's unique strengths as well as current product biases. Finally, we will discuss MISR dust plume product and climatological applications.

dust sources↗
NASA NTRS2011

Capabilities and Limitations of MISR Aerosol Products in Dust-Laden Regions

Atmospheric mineral dust particles have significant effects on climate and the environment, and despite notable advances in modeling and satellite and ground-based measurements, remain one of the major factors contributing to large uncertainty in aerosol radiative forcing. We examine the Multi-angle Imaging SpectroRadiometer (MISR) 11+ year aerosol data record to demonstrate MISR's unique strengths and assess potential biases of MISR products for dust study applications. In particular, we examine MISR's unique capabilities to 1) distinguish dust aerosol from spherical aerosol types, 2) provide aerosol optical depths over bright desert source regions, and 3) provide high-resolution retrievals of dust plume heights and associated winds. We show examples of regional and global MISR data products in dusty regions together with quantitative evaluations of product accuracies through comparisons with independent data sources, and demonstrate applications of MISR data to dust regional and climatological studies, such as dust property evolution during transport, dust source climatology in relation to climatic factors, and dust source dynamics. The potential use of MISR radiance data to study dust properties is also discussed.

dust aerosol↗
NASA NTRS2013

Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data

High temporal resolution information on burned area is a prerequisite for incorporating bottom-up estimates of wildland fire emissions in regional air transport models and for improving models of fire behavior. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the evolution of nine large wildland fires. For each fire, local input parameters for the kriging model were defined using variogram analysis. The accuracy of the kriging model was assessed using high resolution daily fire perimeter data available from the U.S. Forest Service. We also assessed the temporal reporting accuracy of the MODIS burned area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared to 33% for MCD45A1 and 53% for MCD64A1.

Aqua↗
NASA NTRS2013

In-Situ Transfer Standard and Coincident-View Intercomparisons for Sensor Cross-Calibration

There exist numerous methods for accomplishing on-orbit calibration. Methods include the reflectance-based approach relying on measurements of surface and atmospheric properties at the time of a sensor overpass as well as invariant scene approaches relying on knowledge of the temporal characteristics of the site. The current work examines typical cross-calibration methods and discusses the expected uncertainties of the methods. Data from the Advanced Land Imager (ALI), Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), Moderate Resolution Imaging Spectroradiometer (MODIS), and Thematic Mapper (TM) are used to demonstrate the limits of relative sensor-to-sensor calibration as applied to current sensors while Landsat-5 TM and Landsat-7 ETM+ are used to evaluate the limits of in situ site characterizations for SI-traceable cross calibration. The current work examines the difficulties in trending of results from cross-calibration approaches taking into account sampling issues, site-to-site variability, and accuracy of the method. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The results show that cross calibrations with absolute uncertainties lesser than 1.5 percent (1 sigma) are currently achievable even for sensors without coincident views.

Advanced Spaceborne Thermal Emission and Reflectio↗