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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 NTRS2022

Determining the Primary Sources of Uncertainty in Retrieval of Marine Remote Sensing Reflectance From Satellite Ocean Color Sensors

Uncertainties in the retrieval of the remote sensing reflectance, R_rs, from Ocean Color (OC) satellite sensors have a strong impact on the performance of algorithms for the estimation of chlorophyll-a, mineral concentrations, and inherent optical properties (IOPs). The uncertainties are highest in the blue bands. The total radiance measured at the top of the atmosphere captures the instantaneous state of the atmosphere-ocean system: the in-water conditions, sky and Sun glint reflected from the wind-roughened ocean surface, as well as light scattered from molecules and aerosols in the atmosphere. Each of these components has associated uncertainties, and when combined with the additional uncertainties from the instrument noise and the atmospheric correction process, they contribute to the total uncertainty budget for the retrieved R_rs. We analyzed the contribution of each component uncertainties to the total R_rs uncertainties in SNPP-VIIRS level 2 products, taking advantage of the spectral differences between the components. We examined multiple scenes in the open ocean and coastal waters at spatial resolutions ranging from 2250 to 5250 m by comparing the retrieved R_rs to in situ measurements made at several AERONET-OC sites and at the MOBY site. It was shown that uncertainties associated with the molecular (Rayleigh) scattering play the most significant role, while the contributions of other components are usually smaller. Uncertainties in Rayleigh scattering are primarily attributed to the variability of Rayleigh optical thickness (ROT) with a standard deviation of approximately 1.5% of ROT, which can largely explain the frequency of negative R_rs retrievals as observed using the current standard atmospheric correction process employed by NASA. Variability of the sky light reflected from the ocean surface in some conditions also contributed to uncertainties in the blue; water variability proportional to R_rs had a very pronounced peak in the green at coastal sites.

remote sensing reflectance↗
NASA NTRS2021

Development and Validation of an Empirical Ocean Color Algorithm with Uncertainties: A Case Study with the Particulate Backscattering Coefficient

We explored how algorithm (model) and in situ measurement (observation) uncertainties can effectively be incorporated into empirical ocean color model development and assessment. In this study we focused on methods for deriving the particulate backscattering coefficient at 555 nm, b(bp)(555)/(m). We developed a simple empirical algorithm for deriving b(bp)(555) as a function of a remote sensing reflectance line height (LH) metric. Model training was performed using a high-quality bio-optical dataset that contains coincident in situ measurements of the spectral remote sensing reflectances, R(rs)(λ)/(sr), and the spectral particulate backscattering coefficients, b(bp)(λ). The LH metric used is defined as the magnitude of Rrs(555) relative to a linear baseline drawn between R(rs)(490) and R(rs)(670). Using an independent validation dataset, we compared the skill of the LH-based model with two other models. We used contemporary validation metrics, including bias and mean absolute error (MAE), that were corrected for model and observation uncertainties. The results demonstrated that measurement uncertainties do indeed impact contemporary validation metrics such as mean bias and MAE. Zeta-scores and z-tests for overlapping confidence intervals were also explored as potential methods for assessing model skill.

ocean color↗
NASA NTRS1988

Ocean color remote sensing systems - Radiometric requirements

A methodology for specifying the radiometric requirements for ocean color remote sensing systems is described. Consideration is given to the noise equivalent radiance, the saturation radiance, the polarization sensitivity, and the calibration and stability. The degree of polarization across a scan line for the CZCS and MODIS orbits is presented.

Gordon, Howard R.↗
NASA NTRS2022

Infrared Spectral Responses of the Ocean Color Instrument (OCI) Pre-assembly and Integration

Spectral characterizations were made of the Ocean Color Instrument (OCI) short-wave infrared (SWIR) Detection Subassembly (SDS) responses (940–2260 nm) prior to their integration. Using modulated output light from a Fourier transform spectrometer, the in-band relative spectral responses of the nine different configurations of SDSs were found along with out-of-band (OOB) sensitivity. From these spectral responses, the center wavelengths (λ0), full widths at half of the maximum, full widths at 1% of the maximum, and OOB rejection ratios were determined. All spectral parameters are within requirements. There are 2–8 repeats of each configuration, and the 1 σ spread among repeats is largest for the 1250 nm and 1615 nm high-gain configurations and is greater than 1 nm. The engineering requirement is for these values to be within ±4 nm and ±10 nm, respectively, of 19 the nominal λ0. There is also a λ0 temperature dependence, which is expected. This temperature dependence is nearly a linear function of wavelength with a 9.5 × 10−3 nm K−1 relationship on average.

PACE↗
NASA NTRSDate not supplied

Pre-Launch Analysis and Test of the Ocean Color Instrument Modulation Transfer Function

Launched in February 2024, the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. The Ocean Color Instrument (OCI) is the primary instrument supporting PACE by collecting accurate radiometric data of the Earth by observing the top of atmosphere reflectance and is a combination hyperspectral (ultra-violet to near infrared) / multiband imager (shortwave infrared). An important aspect of the radiometry is the ability of OCI to resolve contrast from scene to scene to achieve data accuracy requirements. This paper reviews the analysis that was performed to verify the modulation transfer function requirement levied against the instrument and presents the supportive test data collected during pre-launch instrument testing to supplement the analysis. The requirements levied against OCI drove to a 1.2 km2 ground resolution leading to a Nyquist period of 2.4 km (0.417 cycles / km). The analysis is comprehensive with incorporation of as many contributors as practical to provide the clearest possible picture of the margin against requirements. The analysis provided input for additional design trade studies and insight into the aspects of the design that required the most attention during the implementation phase. We describe four separate MTF contributor networks based on the instrument design and mutual exclusivity of contributing factors. The various networks represent the hyperspectral and multiband detection systems separately as well as the along track and cross track imaging dimensions. Ground-test was performed against the MTF primary contributors and the results were used to validate the analysis as will be presented here.

OCI↗
NASA NTRSDate not supplied

Pre-Launch Analysis and Test of the Ocean Color Instrument Modulation Transfer Function

Launched in February 2024, the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. The Ocean Color Instrument (OCI) is the primary instrument supporting PACE by collecting accurate radiometric data of the Earth by observing the top of atmosphere reflectance and is a combination hyperspectral (ultra-violet to near infrared) / multiband imager (shortwave infrared). An important aspect of the radiometry is the ability of OCI to resolve contrast from scene to scene to achieve data accuracy requirements. This paper reviews the analysis that was performed to verify the modulation transfer function requirement levied against the instrument and presents the supportive test data collected during pre-launch instrument testing to supplement the analysis. The requirements levied against OCI drove to a 1.2 km2 ground resolution leading to a Nyquist period of 2.4 km (0.417 cycles / km). The analysis is comprehensive with incorporation of as many contributors as practical to provide the clearest possible picture of the margin against requirements. The analysis provided input for additional design trade studies and insight into the aspects of the design that required the most attention during the implementation phase. We describe four separate MTF contributor networks based on the instrument design and mutual exclusivity of contributing factors. The various networks represent the hyperspectral and multiband detection systems separately as well as the along track and cross track imaging dimensions. Ground-test was performed against the MTF primary contributors and the results were used to validate the analysis as will be presented here.

OCI↗
NASA NTRS2021

Adaptive Data Screening for Multi-Angle Polarimetric Aerosol and Ocean Color Remote Sensing Accelerated by Automatic Differentiation

Remote sensing measurements from multi-angle polarimeters (MAPs) contain rich aerosol microphysical property information, and these sensors have been used to perform retrievals in optically complex atmosphere and ocean systems. Previous studies have concluded that, generally, five moderately separated viewing angles in each spectral band provide sufficient accuracy for aerosol property retrievals, with performance gradually saturating as angles are added above that threshold. The Hyper-Angular Rainbow Polarimeter (HARP) instruments provide high angular sampling with a total of 90-120 unique angles across four bands, a capability developed mainly for liquid cloud retrievals. In practice, not all view angles are optimal for aerosol retrievals due to impacts of clouds, sun glint, and other impediments. The many viewing angles of HARP can provide resilience to these effects, if the impacted views are screened from the dataset, as the remaining views may be sufficient for successful analysis. In this study, we discuss how the number of available viewing angles impacts aerosol and ocean color retrieval uncertainties, as applied to two versions of the HARP instrument. AirHARP is an airborne prototype that was deployed in the ACEPOL field campaign, while HARP2 is an instrument in development for the upcoming NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Based on synthetic data, we find that a total of 20-30 angles across all bands (i.e. five to eight viewing angles per band) are sufficient to achieve good retrieval performance. Following from this result, we develop an adaptive multi-angle polarimetric data screening (MAPDS) approach to evaluate data quality by comparing measurements with their best-fitted forward model. The FastMAPOL retrieval algorithm is used to retrieve scene geophysical values, by matching an efficient, deep learning-based, radiative transfer emulator to observations. The data screening method effectively identifies and removes viewing angles affected by thin cirrus clouds and other anomalies, improving retrieval performance. This was tested with AirHARP data, and we found agreement with the High Spectral Resolution Lidar-2 (HSRL-2) aerosol data. The data screening approach can be applied to modern satellite remote sensing missions, such as PACE, where a large amount of multi-angle, hyperspectral, polarimetric measurements will be collected.

multi-angle polarimeter↗
NASA NTRSDate not supplied

New Global Ocean Color Sensor: OCI on PACE

- OCI will provide TOA radiances at ~1km spatial resolution, from 340nm (315nm?) to 2260nm, hyperspectral from 340nm to 890nm, 2 day global coverage - OCI will continue and enhance NASA’s earth system data records for ocean color (heritage sensors: SeaWiFS, MODIS, VIIRS) - OCI flight unit is close to being ready for testing (planned for March 2022 to September 2022) - OCI ETU (Engineering Test Unit) completed testing summer 2021, results look promising (see next presentation) - On-orbit calibration will combine successful trending approaches from previous sensors (2 solar diffusers, QVD, lunar gain trending, spectral trending) - New calibration approaches for OCI: large QVD, dim diffuser for linearity trending, lunar hysteresis trending - OCI will be characterized prelaunch with an ambitious goal of 0.5% relative uncertainty; absolute uncertainty will be about 2% (before vicarious calibration); expected on-orbit gain trending accuracy is 0.2% or better - More info on PACE and OCI can be found at https://pace.oceansciences.org/

radiometer↗
NASA NTRS1983

The ocean color experiment (OCE) on the second orbital flight test of the Space Shuttle (OSTA-1)

The Ocean Color Experiment was one of the six remote-sensing experiments which for the first time were launched and successfully operated on board of the second flight of the Space Shuttle during November 1981. The experiment consists of a multispectral image scanner dedicated to the measurement of water color and its interpretation in terms of major water constituents and circulation patterns. The objectives of the experiment, the test site selection, and associated activities are described. The actual mission and results of an initial data analysis is discussed.

Van Der Piepen, H.↗
NASA NTRSDate not supplied

Pre-Launch Characterization of the Hyperspectral Ocean Color Instrument on NASA’s Pace Mission

Launched in February 2024, the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. Like its predecessors, OCI provides two day global coverage of top-of-atmosphere radiances. Unlike its predecessors, OCI covers a spectral range from 340 nm to 2260 nm. Below 900 nm, OCI provides hyperspectral radiances sampled every 2.5 nm or 1.25nm, with a bandwidth of 5 nm for each channel. Its spatial resolution is about 1.2km. The high radiometric accuracy of OCI was made possible by a thorough and extensive prelaunch characterization campaign, conducted at NASA’s Goddard Space Flight Center. This presentation describes the prelaunch radiometric characterization (approach and results) of OCI, such as e.g. the linearity correction, signal to noise ratio, polarization, IFOV, relative spectral response, radiometric gain, temperature sensitivity, optical crosstalk, and response versus scan angle.

Gerhard Meister↗
NASA NTRS1980

A design study for an advanced ocean color scanner system

Along with a colorimetric data analysis scheme, the instrumental parameters which need to be optimized in future spaceborne ocean color scanner systems are outlined. With regard to assessing atmospheric effects from ocean colorimetry, attention is given to computing size parameters of the aerosols in the atmosphere, total optical depth measurement, and the aerosol optical thickness. It is suggested that sensors based on the use of linear array technology will meet hardware objectives.

Kim, H. H.↗
NASA NTRS1987

Ocean color spectral variability studies using solar-induced chlorophyll fluorescence

It is suggested that chlorophyll-induced ocean color spectral variability can be studied using only a passive airborne spectroradiometer instrument, with solar-induced chlorophyll fluorescence used as the standard against which all correlations are performed. The intraspectral correlation (ISC) method is demonstrated with results obtained during an airborne mapping mission in the New York Bight. The curvature algorithm is applied to the solar-induced chlorophyll fluorescence at about 690 nm, and good agreement is found with results obtained using active-passive correlation spectroscopy. The ISC method has application to spectral variability and resulting chlorophyll concentration measurement in different environmental conditions and in different water types.

Hoge, Frank E.↗
NASA NTRS1990

Radiometric considerations for ocean color remote sensors

A methodology for determination of the effects of radiometric noise on the performance of ocean color sensors is developed and applied to the Coastal Zone Color Scanner on Nimbus 7 and the Moderate Resolution Imaging Spectrometer planned for the Earth Observing System.

Gordon, Howard R.↗
NASA NTRS2001

Covariation of Mesoscale Ocean Color and Sea-Surface Temperature Patterns in the Sargasso Sea

During the lifetime of the Coastal Zone Color Scanner, there were 21 instances in which both satellite-derived ocean color and sea-surface temperature are simultaneously available over large areas of the Sargasso Sea. These images reveal close correspondence between mesoscale structures observed in temperature and pigment fields. In general, higher (lower) pigment biomass occurs in mesoscale features consisting of cold (warm) temperature anomalies. This relationship is consistent with the idea that upward displacement of isopycnals at the base of the euphotic zone by mesoscale eddies is an important mechanism of nutrient supply in the region.

McGillicuddy, Dennis J., Jr.↗
NASA NTRS2001

Covariation of Mesoscale Ocean Color and Sea-Surface Temperature Patterns in the Sargasso Sea

During the lifetime of the Coastal Zone Color Scanner, there were 21 instances in which both satellite-derived ocean color and sea-surface temperature are simultaneously available over large areas of the Sargasso Sea. These images reveal close correspondence between mesoscale structures observed in temperature and pigment fields. In general, higher (lower) pigment biomass occurs in mesoscale features consisting of cold (warm) temperature anomalies. This relationship is consistent with the idea that upward displacement of isopycnals at the base of the euphotic zone by mesoscale eddies is an important mechanism of nutrient supply in the region.

McGillicuddy, D. J.↗
NASA NTRS2000

Validation of Ocean Color Remote Sensing Data using a Moored Databuoy

NASA's Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) aims to measure global ocean color from space to within 5% to provide insights into fundamental ocean processes. SeaWiFS must be backed by comprehensive calibration and validation programs if the mission is to achieve this. In situ measurements of normalized water-leaving radiance (L(sub wn)) made simultaneously with satellite measurements can complement on-orbit methods of tracking changes in the calibration of the satellite radiometer and allow end-to-end vicarious validation of the remotely-sensed data. A moored optical databuoy was developed at Plymouth Marine Laboratory, UK to measure L(sub wn) in the western English Channel. Tests indicate that the buoy is capable of measuring spectral incident irradiance with less than 10% error and water-leaving radiance with less than 20% error; these errors are reduced by averaging and show no bias. There were 24 match-ups with good quality SeaWiFS data at the buoy site during the ten months of deployment within the period May 1997 and September 1998. The differences between the buoy and SeaWiFS measurements of L(sub wn) were found to be variable and often large. The root-mean-square (RMS) differences varied from 102% at 412 nm to 50% at 555 nm. The RMS differences in measurements of L(sub wn) could be reduced to less than 18% by a combination of increasing the calibration coefficients of SeaWiFS by between 0.2 and 4.3% in the visible bands and by tuning the extrapolation of aerosol radiances from the near infrared to the visible wavelengths. These results imply that the monitoring of the absolute calibration of the SeaWiFS bands is imperfect and errors remain in the extrapolation of aerosol radiances for atmospheric correction.

Lavender, Samantha↗
NASA NTRS1983

Ocean color algorithm for remote sensing of chlorophyll

An algorithm for the remote detection of chlorophyll a in the ocean was tested during a Nantucket Shoals experiment conducted by NASA. A set of Multichannel Ocean Color Sensor (MOCS) data selected from one flight for each of the two altitudes flown was used to calibrate the algorithm for chlorophyll a concentration. The equations were then applied to all unsaturated MOCS data collected during the 8-day experiment to generate contour maps of chlorophyll a concentration over the shoals. One additional flight was conducted away from the shoals both on and off the Continental Shelf. Although no solar elevation or environmental corrections were made to the original conversions, the equations in these tests determined chlorophyll a concentrations to an accuracy better than 1.0 micron g/L despite the fact that the solar elevation varied between 20 deg and 56 deg during the data collection periods of the experiments.

Grew, G. W.↗