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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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NASA NTRS1982

Fabry-Perot interferometer measurements of thermospheric neutral wind gradients and reversals at Arecibo

Direct measurements of the meridional neutral winds in the thermosphere made with the Fabry-Perot interferometer at the Arecibo Observatory show the postmidnight meridional wind reversal that was inferred from previous incoherent scatter radar ion-drift data and airglow intensity maps and observed in-situ with the Atmosphere Explorer-E satellite. Data for three nights between October 29 and December 9, 1981, are presented. For this period, the meridional wind is observed to be northward after sunset and to turn south before midnight; the velocities often exceed 100 m/sec. After midnight, its direction is seen to reverse to northward for one to two hours. The reversal after midnight is recurrent and propagates from the equator, as predicted on the basis of previous meridional airglow intensity measurements.

Friedman, J. F.↗
NASA NTRS1980

Coordinated study of equatorial scintillation and in situ and radar observations of nighttime F region irregularities

A coordinated set of Atmospheric Explorer E (AE-E) satellite in situ, VHF radar backscatter, and scintillation measurements performed during 1977 over a common ionospheric volume is used to study the relationship between the plasma depletions or bubbles, the extended 3-m irregularity structures known as plumes, and bursts of scintillation activity or patches in the nighttime equatorial F region. The implications of the observed spatial structures and the level of ambient concentration on the generation of 3-m irregularities and scintillation modeling are discussed.

Basu, S.↗
NASA NTRS2024

Maximizing the Volume of Collocated Data from Two Coordinated Suborbital Platforms

Suborbital (e.g., airborne) campaigns that carry advanced remote sensing and in situ payloads provide detailed observations of atmospheric processes, but can be challenging to use when it is necessary to geographically collocate data from multiple platforms that make repeated observations of a given geographic location at different altitudes. This study reports on a data collocation algorithm that maximizes the volume of collocated data from two coordinated suborbital platforms and demonstrates its value using data from the NASA Aerosol Cloud Meteorology Interactions Over the western Atlantic Experiment (ACTIVATE) suborbital mission. A robust data collocation algorithm is critical for the success of the ACTIVATE mission goal to develop new and improved remote sensing algorithms, and quantify their performance. We demonstrate the value of these collocated data to quantify the performance of a recently developed vertically resolved lidar + polarimeter–derived aerosol particle number concentration (Na ) product, resulting in a range-normalized mean absolute deviation (NMAD) of 9% compared to in situ measurements. We also show that this collocation algorithm increases the volume of collocated ACTIVATE data by 21% compared to using only nearest-neighbor finding algorithms alone. Additional to the benefits demonstrated within this study, the data files and routines produced by this algorithm have solved both the critical collocation and the collocation application steps for researchers who require collocated data for their own studies. This freely available and open-source collocation algorithm can be applied to future suborbital campaigns that, like ACTIVATE, use multiple platforms to conduct coordinated observations, e.g., a remote sensing aircraft together with in situ data collected from suborbital platforms.

Atmosphere↗
DOE OSTI2022

Evaluation and Optimization of Snow Albedo Scheme in Noah-MP Land Surface Model Using In Situ Spectral Observations in the Colorado Rockies

The Biosphere-Atmosphere Transfer Scheme (BATS) ground snow albedo algorithm is commonly used in land-surface models (LSM), weather forecasting and research applications. This study addresses key uncertainties in BATS simulated ground snow albedo within the Noah-MP LSM framework through evaluation and optimization of the Noah-MP BATS ground snow albedo formulation using 2-band (visible and near-infrared (NIR)) in situ albedo observations at Rocky Mountain field stations. The Noah-MP BATS ground snow albedo scheme is extremely sensitive to its input parameters. Namely, an ensemble generated by varying BATS input parameters within potentially plausible ranges provides an average daily range (maximum ensemble member minus minimum ensemble member) of ground snow albedo exceeding 0.45 in visible and NIR bands. Parameter optimization improves agreement between simulated and in situ observed ground snow albedo in visible, NIR and broadband spectrums. Importantly, optimized parameters result in reduced biases relative to observed fresh-snow albedo and better agreement with observed albedo decay. Our analysis across different sites supports that the optimized BATS ground snow albedo parameters are appropriate to transfer in space and time, at least within the region studied (the central-southern Rocky Mountains). The primary error source remaining after parameter optimization is that observed fresh-snow albedo is highly variable, particularly in the NIR spectrum, whereas BATS fresh-snow albedo is constant, an issue which requires further investigation. This study shows significant correlations between observed fresh-snow albedo and surface meteorological conditions (e.g., downward shortwave radiation and temperature) which can support future model development that attempts to include a time-varying formulation for fresh-snow albedo.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Tropospheric chemical models

The differences in atmospheric composition over the globe and the short- and long-term variations in this composition are the net effect of several atmospheric and biospheric processes: biospheric emissions, atmospheric circulation, atmospheric chemical transformations and finally deposition back to the surface. Accurate and realistic atmospheric chemistry and circulation models are essential to interpret the observed global distributions and trends of atmospheric species in terms of these underlying processes. Comparisons between model predictions and observations test current understanding of these processes and models used in conjunction with inverse methods allow deductions of the rates of these processes from the observations. With the planned inclusion of at least CO and CH4 observations on the Earth Observing System (EOS) satellites, together with the large global data set expected from in situ observations under the International Global Atmospheric Chemistry (IGAC) Project, the further development of global three-dimensional high-resolution atmospheric chemistry and circulation models in order to interpret this new data is a high-priority endeavor.

Prinn, R. G.↗
DOE OSTI2024

The Modeled Seasonal Cycles of Surface N 2 O Fluxes and Atmospheric N 2 O

Nitrous oxide (N 2 O) is a greenhouse gas and stratospheric ozone-depleting substance with large and growing anthropogenic emissions. Previous studies identified the influx of N 2 O-depleted air from the stratosphere to partly cause the seasonality in tropospheric N 2 O (aN 2 O), but other contributions remain unclear. Here, we combine surface fluxes from eight land and four ocean models from phase 2 of the Nitrogen/N 2 O Model Intercomparison Project with tropospheric transport modeling to simulate aN 2 O at eight remote air sampling sites for modern and pre-industrial periods. Models show general agreement on the seasonal phasing of zonal-average N 2 O fluxes for most sites, but seasonal peak-to-peak amplitudes differ several-fold across models. The modeled seasonal amplitude of surface aN 2 O ranges from 0.25 to 0.80 ppb (interquartile ranges 21%–52% of median) for land, 0.14–0.25 ppb (17%–68%) for ocean, and 0.28–0.77 ppb (23%–52%) for combined flux contributions. The observed seasonal amplitude ranges from 0.34 to 1.08 ppb for these sites. The stratospheric contributions to aN 2 O, inferred by the difference between the surface-troposphere model and observations, show 16%–126% larger amplitudes and minima delayed by ~1 month compared to Northern Hemisphere site observations. Land fluxes and their seasonal amplitude have increased since the pre-industrial era and are projected to grow further under anthropogenic activities. Our results demonstrate the increasing importance of land fluxes for aN 2 O seasonality. Considering the large model spread, in situ aN 2 O observations and atmospheric transport-chemistry models will provide opportunities for constraining terrestrial and oceanic biosphere models, critical for projecting carbon-nitrogen cycles under ongoing global warming.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Accelerating TEMPO Air Quality Science Through STAQS

Soon after the launch of Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission, NASA is supporting the Synergistic TEMPO Air Quality Science field study (STAQS) in summer 2023. This study’s main objective is to accelerate science with geostationary air quality observations from TEMPO to better understand its use in air pollution research and applications. Science objectives include, but are not limited to, TEMPO L2 product evaluation, the interpretation of the spatiotemporal evolution of TEMPO data during air quality events, assessment of anthropogenic emissions, contributions to chemical transport modeling, and environmental justice applications. These objectives can be accomplished through the integration of satellite data with systematically repeated high-resolution aircraft- and ground-based measurements in multiple urban environments. The primary urban cities considered include Los Angeles, New York City, and Chicago in June-August 2023. Measurements consist of airborne remote sensing observations of air quality constituents of nitrogen dioxide (NO2), formaldehyde (HCHO), ozone, and aerosols using the GeoCape Airborne Simulator and High-Spectral Resolution Lidar 2/Differential Absorption Lidar (HSRL2/DIAL) on the NASA JSC G-V aircraft, greenhouse gas observations from Airborne Visible InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG) and High Altitude Lidar Observatory (HALO) on the NASA LaRC G-III aircraft, and ground-based remote sensing and in situ observations of ozone, NO2, and HCHO from the Tropospheric Ozone Lidar Network (TOLNet), Pandora spectrometers, and ground-based monitoring networks. Key partnership studies providing in situ airborne observations include the NOAA Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) field study on the NASA DC-8 in the same primary target areas as STAQS and Greater New York Oxidant, Tropospheric Halogens, and Aerosol Measurements and Modeling (GOTHAMM) field study on the NSF C-130 near New York City. This presentation will include a current status update of the STAQS mission and an overview of its measurement strategies and science objectives with the goal of promoting continued discussions for building and strengthening collaborations prior to the mission.

Laura Judd↗
NASA NTRS2024

SiC Charged Particle Telescope GRC Independent Research and Development (IRAD) Program End of Project Final Report

In an advancement over the state-of-the art, NASA Glenn Research Center (GRC) has developed a large area silicon carbide (SiC)-based charged particle telescope through an Independent Research and Development (IRAD) project. The telescope has been demonstrated to have improved noise characteristics and resolution than previous SiC detectors. This improvement will meet the challenges of compact multidirectional robust radiation detector systems to study a wide range of elementary particle mass and energies. In order to provide a complete understanding of how energetic processes internal and external to the solar system shape magnetospheres, atmospheres, and surfaces, in situ particle observations should include measurements of Solar Energetic Particles (SEP) and Galactic Cosmic Rays (GCR), along with solar wind and plasma. The potential temperature stability, tolerance to high radiation environments, and low noise characteristics expected in SiC-based detectors can have advantages over the state-of-the-art silicon detectors. These advantages will allow the detectors to be deployed in small compact systems on a variety of platforms, enabling compact structures for small satellite platforms with improved data quality.

Field and particle detectors↗
NASA NTRS1975

An auroral F-region study using in situ measurements by the Atmosphere Explorer-C satellite

The ion densities observed as the Atmosphere Explorer-C satellite passed through an aurora at F-region altitudes are compared to those calculated from photochemical theory using in situ measurements of atmospheric parameters (ionic and neutral composition; electron flux; neutral temperature; ion temperature) along the satellite track together with current values for reaction rates. Good agreement is obtained for the ions O2(+), NO(+), and N2(+). The atomic nitrogen densities calculated from the observed NO(+)/O2(+) ratio are found to account for about 60% of the N(+) production through electron impact on N and the resonant charge exchange of O(+)(2P) with N(4S). The N density at about 280 km, the region of the most intense electron fluxes (20 erg/sq cm/sec), is between 20 and 70 million/cu cm.

Torr, M. R.↗
NASA NTRS2017

Status and Plans for Reanalysis at NASA/GMAO

Reanalysis plays a critical role in GMAOs goal to enhance NASA's program of Earth observations, providing vital data sets for climate research and the development of future missions. As the breadth of NASAs observations expands to include multiple components of the Earth system, so does the need to assimilate observations from currently uncoupled components of the system in a more physically consistent manner. GMAOs most recent reanalysis of the satellite era, MERRA-2, has completed the period 1980-present, and is now running as a continuing global climate analysis with two- to three-week latency. MERRA-2 assimilates meteorological and aerosol observations as a weakly coupled assimilation system as a first step toward GMAOs longer term goal of developing an integrated Earth system analysis (IESA) capability that will couple assimilation systems for the atmosphere, ocean, land and chemistry. The GMAO strategy is to progress incrementally toward an IESA through an evolving combination of coupled systems and offline component reanalyses driven by, for example, MERRA-2 atmospheric forcing. Most recently, the GMAO has implemented a weakly coupled assimilation scheme for analyzing ocean skin temperature within the existing atmospheric analysis. The scheme uses background fields from a near-surface ocean diurnal layer model to assimilate surface-sensitive radiances plus in-situ observations along with all other observations in the atmospheric assimilation system. In addition, MERRA-2-driven simulations of the ocean (plus sea ice) and atmospheric chemistry (for the EOS period) are currently underway, as is the development of a coupled atmosphere-ocean assimilation system. This talk will describe the status of these ongoing efforts and the planned steps toward an IESA capability for climate research.

MERRA-2↗
NASA NTRS2019

SST Improvements in the NASA GMAO Weather Analysis and Prediction System

It is well known that the sea surface temperature (SST) exhibits a diurnal cycle. Since January 2017, the NASA GMAO's Weather Analysis & Prediction System (https://gmao.gsfc.nasa.gov/weather_prediction/) includes a model for this diurnal cycle, a cool-skin layer and assimilates for skin SST. Data assimilation for the skin SST is carried out along with the 3-D state of the atmosphere, primarily using infrared radiance measurements, that are sensitive to the cool-skin and diurnal warming. In the context of Numerical Weather Prediction (NWP), this implies that the skin SST from our system is tightly coupled to the overlaying atmosphere and constrained by all the available atmospheric and surface-sensitive observations (in situ and satellite brightness temperatures). Comparisons of the SST diurnal cycle with other SST retrievals (SEVIRI (Spinning Enhanced Visible & InfraRed Imager) and AMSR-2 (Advanced Microwave Scanning Radiometer-2)) has shown mostly similar diurnal variation, however, the former decays at a faster rate. This poster presents our SST plus atmosphere assimilation methodology, and recent improvements to the skin SST model to address the known issues. Global, hourly estimates of the cool-skin and diurnal warm layer fields would be of interest to the SST retrieval community.

Akella, Santha↗
NASA NTRS2022

VIPRE: A Tool Aiding the Design for Entry Probe Missions

Exploring planetary atmospheres uncovers important information for how our solar system formed and evolved. While remote sensing is extensively used, some crucial observations require in-situ measurements by an atmospheric probe. Given their scientific importance, probe missions to Saturn, Uranus and Neptune are considered for the coming decades. In anticipation of future probe missions, the software tool VIPRE was developed as proof-of-concept to facilitate selection of probe entry locations. Currently, there is no analytical way to identify which interplanetary trajectory from thousands of feasible launch opportunities is optimal for a considered mission concept. The search and decision process for that solution is complex and relies on the intuition of mission designers, who focus on a subset of trajectories to make the trade space manageable. The idea of VIPRE is to (1) generate a multi-dimensional data cube showing relevant engineering and science parameters simultaneously for thousands of trajectories, and (2) visualize the data for all entry sites over the body's envelope. VIPRE lays the foundation to make the data available for browsing in a 3-D visualization to identify the best family of solutions for a given mission. The paper introduces the validated and verified core algorithms of VIPRE, published on GitHub. VIPRE serves as a basic framework to be used and extended for different purposes. The paper presents the motivation for the development and algorithms. It explains the computation and data visualization strategy, and gives a list of suggested functionalities to extend and further develop VIPRE to fully leverage its potential.

Ice Giants↗
NASA NTRSDate not supplied

The Role of Isotopes in Understanding of the Formation and Evolution of the Solar System

Comparative planetology via isotope geochemistry has played a critical role in advancing our understanding of the inventories of both volatiles and organics in the atmospheres of solar system bodies. For example, the 12 C/ 13 C measured from atmospheric methane in Titan provided upper limits on the amount of time that methane has been present in the atmosphere, demonstrating that methane was only present in Titan’s atmosphere during at most the last 1 billion years (Gyr). As another example, measurements of 14 N/ 15 N in atmospheric HCN and N 2 provide direct evidence of how photochemistry influences stable isotopes. These observations were used to determine that Titan’s nitrogen originated as NH 3 in the protosolar nebula, thus constraining the origin and delivery of volatiles to the Saturnian moon Titan. These measurements of 12 C/ 13 C and 14 N/ 15 N in Titan’s atmosphere were obtained with remote and in situ observations from the Cassini spacecraft in Saturn orbit. However, combining spacecraft observations like these throughout the solar system with Earth-based telescope observations, including both ground-based and from orbiting telescopes, produces far more powerful results. For example, the lower limit obtained for 14 N/ 15 N in HCN in Pluto’s atmosphere by ALMA combined with New Horizons observations of the atmospheric composition provides a valuable tool for determining the origin of nitrogen for Pluto if the influences of condensation and aerosol trapping on isotopes can be constrained. Isotopes measured at Jupiter and Saturn and their moons, combined with composition measurements from comets provide information on giant planet formation processes and primordial conditions when the solar system was forming. In all of these studies, measurements of isotope ratios in comets have served as a reference for processes in the protosolar nebula.

Kathleen E. Mandt↗
NASA NTRS2019

Investigating Sources of Variability and Error in Simulations of Carbon Dioxide in an Urban Region

Greenhouse gas (GHG) emissions estimation methods that use atmospheric trace gas observations, including inverse modeling techniques, perform better when carbon dioxide (CO2) fluxes are more accurately transported and dispersed in the atmosphere by a numerical model. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric CO2 from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations).

CO2↗
NASA NTRSDate not supplied

Evaluation of single-footprint AIRS CH4 Profile Retrieval Uncertainties Using Aircraft Profile Measurements

We evaluate the uncertainties of methane optimal estimation retrievals from single footprint thermal infrared observations from the Atmospheric Infrared Sounder (AIRS). These retrievals are primarily sensitive to atmospheric methane in the mid-troposphere through the lower stratosphere (~2 to ~17 km). We compare to in situ observations made from aircraft during the Hiaper Pole to Pole Observations (HIPPO), the NASA Atmospheric Tomography Mission (ATom) campaigns, and from the NOAA ESRL aircraft network, between the surface and 5-13 km, across a range of years, latitudes between 60 S to 80 N, and over land and ocean. After a global, pressure dependent bias correction, we find that the land and ocean have similar biases and that the reported observation error (combined measurement and interference errors) of ~27 ppb is consistent with the standard deviation between aircraft and individual AIRS observations. A single measurement has measurement (noise related) uncertainty of ~17 ppb, a ~20 ppb uncertainty from radiative interferences (e.g. from water, temperature, etc.), and ~ 30 ppb due to “smoothing error”, which is partially removed when making comparisons to in situ measurements or models in a way that account for this regularization. We estimate a 16 ppb validation error because the aircraft typically did not measure methane at altitudes where the AIRS measurements have some sensitivity, e.g. the stratosphere. Daily averaged AIRS measurements of at least 9 observations over spatio-temporal domains of < 1 degree and 1 hour have a standard deviation of ~17 ppb versus aircraft, likely because the observation errors from temperature and water vapor (for example) are only partly reduced through averaging. Seasonal averages can reduce this ~17 ppb uncertainty further to ~10 ppb, as determined through comparison with NOAA aircraft, likely because uncertainties related to radiative effects of temperature and water vapor can be reduced when averaged over a season.

Susan Kulawik↗
DOE OSTI2026

BNF C-band Scanning ARM Precipitation Radar 2nd Generation (CSAPR-2) Extracted Radar Columns and In-Situ Sensors (RadCLss)

Corrected Moments in Antenna Coordinates (CMAC) calculates quantitative precipitation estimates (QPE) from empirical relationships based on equivalent radar reflectivity factor, specific differ- ential phase, and specific attenuation. To evaluate these empirical relationships, the Extracted Radar Columns and In-Situ Sensors (RADclss) product was developed. Utilizing Py-ART, RAD- clss extracts CMAC radar columns above various ARM and partner locations. These columns are then spatiotemporally synced with in-situ observations at the surface utilizing the Atmospheric data Community Toolkit (ACT; Theisen et al. 2025), allowing direct comparison of radar parameters with rain gauges and laser disdrometers for further investigation.

bankhead↗
NASA NTRS2023

Dynamical Core Damping of Thermal Tides in Martian Atmosphere

Atmospheric oscillations with daily periodicity are observed in in-situ near-surface pressure, temperature, and winds observations, and also in remotely sensed temperature and pressure observations of the Martian atmosphere. Such oscillations are interpreted as thermal tides driven by the diurnal cycle of solar radiation and occur at various frequencies, with the most prominent being the diurnal, semidiurnal, terdiurnal and quadiurnal tides. Mars global circulation models reproduce these tides with varying levels of success. Until recently, both the MarsWRF and newly developed MarsMPAS models were able to produce realistic diurnal and semidiurnal tide amplitudes but predicted higher-order mode amplitudes that were significantly weaker than observed. We use linear wave analysis to show that the divergence damping applied within both MarsWRF and MarsMPAS is responsible for suppressing the amplitude of thermal tides with frequency greater than 2 per sol, despite being designed to suppress only acoustic wave modes. Decreasing the strength of the divergence damping in MarsWRF and MarsMPAS allows for excellent prediction of the higher order tidal modes. This finding demonstrates that care must be taken when applying numerical dampers and filters that may eliminate some desired dynamical features in planetary atmospheres.

Yuan Lian↗
NASA NTRS2014

On-Orbit Radiometric Characterization of OLI (Landsat 8) for Applications in Aquatic Remote Sensing

Landsat-8 carries two separate sensors, namely the Operational Land Imager (OLI) and the Thermal Infrared Radiometer Suite (TIRS), that image the earth surface throughout the visible and thermal portions of the spectrum. Compared to Landsat heritage sensors, the OLI has enhanced features, which include its 12-bit radiometric resolution and the addition of a band centered at 443 nm. The dramatically improved data quality/quantity expands existing applications of Landsat imagery in aquatic sciences from the retrieval of bio-geochemical properties, such as near-surface concentrations of chlorophyll-a (CHL) and total suspended solids (TSS), to benthic mapping. This study offers analysis of OLI's absolute radiometric performance over bodies ofwater using benchmark observations, namely the top-of-atmosphere (TOA) ocean color observations and marine in situ radiometric measurements. Sensor-to-sensor comparisons are performed to derive gain factors (g1) from near-concurrent observations in TOA radiance and reflectance domains. The gains in the radiance domain were further validated/adjusted by determining a second set of gains (g2) via analysis of OLI-derived water-leaving radiance, i.e., L(sub w) (gamma), against in situ measurements made either at the Ocean Color AErosol RObotic NETwork (AERONETOC) sites or during field campaigns. The analyses yield the OLI calibration uncertainties that need to be accounted forwhen studying aquatic environments. Itwas found that, for the visible and near-infrared channels, the OLI radiometric responses, on average, are well in agreement (b 2 % discrepancies) with the TOA radiances estimated by ocean color satellites or those predicted by models based onmeasurements of aquatic and atmospheric properties. However, the TOA radiance at the new 443-nm band is found to be, on average, 3.4 % larger than the reference observations. The inter-sensor comparisons in the reflectance domain, however, indicated slightly different results with the OLI responses being low in the blue bands. To enhance the retrieval accuracy of aquatic-science products from OLI datasets, sets of temporally averaged gains (radiance and reflectance) are derived and recommended for use prior to the retrieval of in-water products.

Remote Sensing↗