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NASA NTRSDate not supplied

PACE UV-VIS Polarimetric Remote Sensing of Atmosphere-Ocean Systems: Sensitivity to Variations in Brown Carbon

The NASA Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission, scheduled for launch in 2024, will carry two instruments that measure ultraviolet (UV) radiance emerging from the top of the atmosphere: the Ocean Color Instrument (OCI) and the Spectro-Polarimeter for Planetary Exploration (SPEXone) instrument. OCI will provide single-view, hyperspectral radiometric data, whereas SPEXone will provide multi-angle, multispectral polarimetric data. Together, these instruments will be the most advanced in NASA’s history for the combined observation of ocean color and atmospheric aerosols in the UV, and they will therefore provide unprecedented research opportunities for the ocean color and atmospheric aerosol communities. In particular, UV observations are best suited to retrieve properties of Colored Dissolved Organic Matter (CDOM) in the ocean, and of Brown Carbon (BrC) aerosols in the atmosphere. However, both CDOM and BrC exhibit very similar absorption spectra in the UV and the visible (VIS) spectrum; hence, care must be taken in accurately modeling these spectra for analyses of OCI and SPEXone measurements. In this presentation, we summarize a simple but highly accurate three-parameter model for complex refractive index spectra of BrC in the UV and VIS. We apply this model to simulations of PACE-like total and polarized multiangle radiance in the UV, and demonstrate that the impact of BrC and CDOM variations can be similar in total radiance, but is easy to distinguish in polarized radiance.

PACE↗

NASA NTRS2013

Microradiometers Reveal Ocean Health, Climate Change

When NASA researcher Stanford Hooker is in the field, he pays close attention to color. For Hooker, being in the field means being at sea. On one such research trip to the frigid waters of the Arctic, with a Coast Guard icebreaker looming nearby and the snow-crusted ice shelf a few feet away, Hooker leaned over the edge of his small boat and lowered a tethered device into the bright turquoise water, a new product devised by a NASA partner and enabled by a promising technology for oceanographers and atmospheric scientists alike. Color is a function of light. Pure water is clear, but the variation in color observed during a visit to the beach or a flight along a coastline depends on the water s depth and the constituents in it, how far down the light penetrates and how it is absorbed and scattered by dissolved and suspended material. Hooker cares about ocean color because of what it can reveal about the health of the ocean, and in turn, the health of our planet. "The main thing we are interested in is the productivity of the water," Hooker says. The seawater contains phytoplankton, microscopic plants, which are the food base for the ocean s ecosystems. Changes in the water s properties, whether due to natural seasonal effects or human influence, can lead to problems for delicate ecosystems such as coral reefs. Ocean color can inform researchers about the quantities and distribution of phytoplankton and other materials, providing clues as to how the world ocean is changing. NASA s Coastal Zone Color Scanner, launched in 1978, was the first ocean color instrument flown on a spacecraft. Since then, the Agency s ocean color research capabilities have become increasingly sophisticated with the launch of the SeaWiFS instrument in 1997 and the twin MODIS instruments carried into orbit on NASA s Terra (1999) and Aqua (2002) satellites. The technology provides sweeping, global information on ocean color on a scale unattainable by any other means. One issue that arises from satellite observation, however, is that the instruments must be continuously calibrated over time to maintain the quality of the data they gather from orbit. To validate and calibrate the satellites, researchers must also gather data at sea level.

Source record↗

NASA NTRS2008

The Aerosol/Cloud/Ecosystems Mission (ACE)

The goals and measurement strategy of the Aerosol/Cloud/Ecosystems Mission (ACE) are described. ACE will help to answer fundamental science questions associated with aerosols, clouds, air quality and global ocean ecosystems. Specifically, the goals of ACE are: 1) to quantify aerosol-cloud interactions and to assess the impact of aerosols on the hydrological cycle and 2) determine Ocean Carbon Cycling and other ocean biological processes. It is expected that ACE will: narrow the uncertainty in aerosol-cloud-precipitation interaction and quantify the role of aerosols in climate change; measure the ocean ecosystem changes and precisely quantify ocean carbon uptake; and, improve air quality forecasting by determining the height and type of aerosols being transported long distances. Overviews are provided of the aerosol-cloud community measurement strategy, aerosol and cloud observations over South Asia, and ocean biology research goals. Instruments used in the measurement strategy of the ACE mission are also highlighted, including: multi-beam lidar, multiwavelength high spectra resolution lidar, the ocean color instrument (ORCA)--a spectroradiometer for ocean remote sensing, dual frequency cloud radar and high- and low-frequency micron-wave radiometer. Future steps for the ACE mission include refining measurement requirements and carrying out additional instrument and payload studies.

Schoeberl, Mark↗

NASA NTRS1972

Measurements of ocean color

An airborne instrument for determining ocean color and measurements made with the instrument are discussed. It was concluded that a clear relationship exists between the chlorophyll concentration and the color of the water. High altitude measurements from 50,000 feet are described and the effects of atmospheric scattering on the energy reaching the sensor are examined. The measured spectrum of ocean color at high and low altitudes is plotted.

Hovis, W. A.↗

NASA NTRS2015

GOCI Level-2 Processing Improvements and Cloud Motion Analysis

The Ocean Biology Processing Group has been working with the Korean Institute of Ocean Science and Technology (KIOST) to process geosynchronous ocean color data from the GOCI (Geostationary Ocean Color Instrument) aboard the COMS (Communications, Ocean and Meteorological Satellite). The level-2 processing program, l2gen has GOCI processing as an option. Improvements made to that processing are discussed here as well as a discussion about cloud motion effects.

Robinson, Wayne↗

NASA NTRS2015

GOCI Level-2 Processing Improvements and Cloud Motion Analysis

Robinson, Wayne D.↗

NASA NTRSDate not supplied

Pace OCI Crosstalk Characterization Based on Pre-Launch Testing

Scheduled to launch in 2024, the Ocean Color Instrument (OCI) onboard the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will collect hyperspectral data from 315 nm – 895 nm via two grating spectrometers (in both the blue and red spectral regions) and 9 multi-spectral bands in the short-wave infrared (940 nm – 2260 nm). The increased spectral resolution and radiometric accuracy is expected to improve upon data collected by heritage sensors such as SeaWiFs, MODIS, and VIIRS, allowing new applications in ocean color, aerosol, and cloud science. During ground testing, higher than expected spatial-spectral crosstalk was measured for the hyperspectral bands in the blue spectrograph. Using a monochromatic-collimated light source, light from a single science pixel (1km x 1km) was found to produce crosstalk signals over 31 pixels in the cross-track direction. This spatial augmentation is caused by the spectral crosstalk’s asynchronous spatial movement during Time Delay Integration (TDI). To fully characterized the magnitude and spectral dependency from this, a crosstalk model was developed by synthesizing data collected from monochromatic-collimated light and monochromatic light that filled the OCI optical aperture. The model was validated by showing good agreement between predicted values and other relevant test data collected using both monochromatic and white light sources.

PACE↗

NASA NTRS2018

Hawkeye Radiometric Calibration Methodology

Hawkeye is an ocean color instrument designed, manufactured and characterized at Cloud land Instruments, CA. It is a push broom instrument that has 8spectral bands similar to SeaWiFS and a spatial resolution of 120 m. Each spectral band has 1800 detectors (pixels) and all 14,000 detectors (pixels) need to be calibrated independently. This paper describes the preliminary design of on-orbit calibration method to correct for the instrument response's temperature sensitivity,scan angle dependency in radiometric sensitivity, relative spectral response (RSR),non linearity, and polarization sensitivity. We will provide a brief description on how each of the calibration parameters are used to address the instrument characteristics and how the calibration parameters are derived from instrument test data and use to retrieve ocean color products.

Lee, Shihyan↗

NASA NTRS2021

Linear Systems LSK389 and LSK489 Dual N-Channel JFET Amplifier Total Ionizing Dose and Single-Event Effects Test Report

The purpose of these tests was to characterize the susceptibility of the LSK389 and LSK489 Dual N-Channel JFET from Linear Systems to Single-Event Latchup due to heavy ions and to Total Ionizing Dose (TID) degradation at -65 °C and intermediate dose rate. The test was carried out to assess suitability of the amplifiers for the Ocean Color instrument (OCI) on the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) spacecraft.

Ray Ladbury↗

NASA NTRS2024

PACE OCI Calibration and Geolocation Operational Algorithm Description

This technical report describes the software implementation of the calibration and geolocation processing algorithms for the Ocean Color Instrument (OCI) on the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. PACE was launched on February 8, 2024. The first Earth-viewing data were collected on February 25, and commissioning was completed on April 5. All PACE science data are acquired and processed by the Science Data Segment (SDS). The first processing stages are Level 0-to-1A and Level 1A-to-1B. The calibration and geolocation processing is performed during the latter stage. The L1B products are the inputs for geophysical retrieval processing (Level 2). This report is organized as follows. The pertinent characteristics of OCI for calibration and geolocation processing are described in Section II. Section III describes the implementation of the geolocation processing algorithms, and the calibration processing is described in Section IV. The Level 1B product format is described in Section V.

Ivona Cetinic↗

NASA NTRSDate not supplied

On-Orbit OCI Characterization Measurements from the first 6 Months of the PACE Mission

The Ocean Color Instrument (OCI) on NASA’s Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission has been providing data to the science community since April 2024. OCI is a hyperspectral imager, providing almost daily global coverage, at a spatial resolution of 1.2km. Its design specifications were optimized for ocean color and atmospheric applications, but terrestrial studies could benefit from its hyperspectral coverage as well. The ocean color requirements called for very high radiometric accuracy, which could benefit a wide variety of applications. This paper presents results from the first 6 months of on-orbit calibration and characterization measurements, including absolute calibration, spectral registration, temporal trending of radiometric sensitivity, signal to noise ratio, and linearity, with a focus on the commissioning results obtained in the first 2 months after launch.

calibration↗

NASA NTRSDate not supplied

On-Orbit OCI Characterization Measurements from the first 6 Months of the PACE Mission

calibration↗

NASA NTRS2022

PACE: How One NASA Mission Aligns With the United Nations Decade of Ocean Science for Sustainable Development (Ocean Shot #2)

The PACE satellite observatory will follow a Sun synchronous, polar orbit at an altitude of 676.5 km with a local 13:00 Equatorial crossing time. Its payload consists of three instruments, a primary hyperspectral imaging radiometer being built at NASA Goddard Space Flight Center and two multispectral, multiangle polarimeters, the combination of which advances far beyond heritage capabilities. The Ocean Color Instrument (OCI) offers one-day global coverage with a ground sample distance of 1 km2 at nadir. As described in this OceanShot, this leap in technology will enable improved understanding of aquatic ecosystems and biogeochemistry, as well as provide new information on phytoplankton community composition and improved detection of algal blooms. OCI will be complemented by two small multi-angle polarimeters with spectral ranges that span the visible to near infrared spectral region. When sunlight interacts with clouds or aerosols, it comes away from that interaction changed. By measuring changes in how reflected light oscillates within a geometric plane (i.e., its viewing angle-specific polarization), we can infer useful properties of the clouds or aerosols. This information is crucial to deciphering the way sunlight is reflected and absorbed by our planet and how aerosols affect cloud formation. The polarimeters include the Spectro-polarimeter for Planetary Exploration (SPEXone) and the Hyper Angular Research Polarimeter (HARP2), both of which will significantly improve aerosol and cloud characterizations and provide opportunities for novel ocean color atmospheric correction. (Figure 3). These instruments offer complementary capabilities: SPEXone is hyperspectral, multiangular, and narrow swath to support advanced atmospheric aerosol characterizations, whereas HARP2 is multispectral, hyper-angular, and wide swath to advance cloud property retrievals. In total, the combined PACE instrument suite will revolutionize studies of global biogeochemistry, carbon cycles, and air–sea exchanges in the ocean–atmosphere system.

Ocean color↗

NASA NTRS2017

Atmospheric Correction for Hyperspectral Ocean Color Retrieval with Application to the Hyperspectral Imager for the Coastal Ocean (HICO)

The classical multi-spectral Atmospheric Correction (AC) algorithm is inadequate for the new generation of spaceborne hyperspectral sensors such as NASA's first hyperspectral Ocean Color Instrument (OCI) onboard the anticipated Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission. The AC process must estimate and remove the atmospheric path radiance contribution due to the Rayleigh scattering by air molecules and scattering by aerosols from the measured top-of-atmosphere (TOA) radiance, compensate for the absorption by atmospheric gases, and correct for reflection and refraction of the air-sea interface. In this work, we present and evaluate an improved AC for hyperspectral sensors developed within NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Analysis System software package (SeaDAS). The improvement is based on combining the classical AC approach of multi-spectral capabilities to correct for the atmospheric path radiance, extended to hyperspectral, with a gas correction algorithm to compensate for absorbing gases in the atmosphere, including water vapor. The SeaDAS-hyperspectral version is capable of operationally processing the AC of any hyperspectral airborne or spaceborne sensor. The new algorithm development was evaluated and assessed using the Hyperspectral Imager for Coastal Ocean (HICO) scenes collected at the Marine Optical BuoY (MOBY) site, and other SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and AERosol Robotic NETwork - Ocean Color (AERONET-OC) coastal sites. A hyperspectral vicarious calibration was applied to HICO, showing the validity and consistency of HICO's ocean color products. The hyperspectral AC capability is currently available in SeaDAS to the scientific community at https://oceancolor.gsfc.nasa.gov/.

Ocean Color↗

NASA NTRS2020

Radiometric approach for the detection of picophytoplankton assemblages across oceanic fronts

Cell abundances of Prochlorococcus, Synechococcus, and autotrophic picoeukaryotes were estimated in surface waters using principal component analysis (PCA) of hyperspectral and multispectral remote-sensing reflectance data. This involved the development of models that employed multilinear correlations between cell abundances across the Atlantic Ocean and a combination of PCA scores and sea surface temperatures. The models retrieve high Prochlorococcus abundances in the Equatorial Convergence Zone and show their numerical dominance in oceanic gyres, with decreases in Prochlorococcus abundances towards temperate waters where Synechococcus flourishes, and an emergence of picoeukaryotes in temperate waters. Fine-scale in-situ sampling across ocean fronts provided a large dynamic range of measurements for the training dataset, which resulted in the successful detection of fine-scale Synechococcus patches. Satellite implementation of the models showed good performance (R(exp 2) > 0.50) when validated against in-situ data from six Atlantic Meridional Transect cruises. The improved relative performance of the hyperspectral models highlights the importance of future high spectral resolution satellite instruments, such as the NASA PACE mission’s Ocean Color Instrument, to extend our spatiotemporal knowledge about ecologically relevant phytoplankton assemblages.

Priscila Kienteca Lange↗

NASA NTRSDate not supplied

Simultaneous Aerosol and Ocean Polarimeter Products Using Coupled Atmosphere-Ocean Vector Radiative Transfer and Neural Networks: The PACE-MAPP Algorithm

We describe the PACE-MAPP algorithm that simultaneously retrieves aerosol and ocean optical parameters using multiangle and multi-channel polarimeter measurements from the SPEXone, Hyper-Angular Rainbow Polarimeter 2 (HARP2), and Ocean Color Instrument (OCI) instruments onboard the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) observing system PACE-MAPP is adapted from the Research Scanning Polarimeter (RSP) Microphysical Aerosol Properties from Polarimetry (RSP-MAPP) algorithm. A key feature of the MAPP family of algorithms is the use of a coupled vector radiative transfer model such that the atmosphere and ocean are always considered together as one system. Consequently, conservation of energy ensures that negative water-leaving radiances do not occur. PACE-MAPP uses optimal estimation to simultaneously characterize the optical and microphysical properties of aerosol and ocean constituents, find the optimal solution, and reliably account for the uncertainties of each parameter. This coupled approach, together with multiangle, multi-channel polarimeter measurements, will enable retrievals of aerosol and water properties across the Earth’s oceans. The PACE-MAPP algorithm provides aerosol and ocean products for both the open ocean and coastal areas and is designed to be accurate, modular, and efficient by using fast neural networks that replace the time-consuming vector radiative transfer calculations. We provide an overview of the PACE-MAPP framework and also describe its modular components including its aerosol and hydrosol models, ocean bio-optical models, and thin cirrus model.

Snorre Stamnes↗

NASA NTRSDate not supplied

PACE OCI Lunar Calibration: Initial Results

Launched in February 2024, the Ocean Color Instrument (OCI) onboard NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission has started performing its monthly lunar calibrations at ±7degreeslunar phase angle in March 2024. In this paper, we will describe the OCI lunar calibration methodology and show the results of lunar calibration events during the initial months of PACE/OCI operation. A key difference of OCI lunar calibration from heritage sensors is that the lunar disk integrated irradiance is computed from lunar pixel radiance and sampling distance instead of the instrument’s IFOV. PACE provided a near constant sweep rate during lunar calibration allowing accurate determination of OCI pixel sampling extent. OCI performs lunar calibration in baseline science mode with 282 hyperspectral bands from 315 –895 nm and 7 shortwave infrared bands(940 -2260 nm). For each OCI band, we compute the integrated lunar disk irradiance, and compare the result with a lunar irradiance model (ROLO)prediction. The early results presented here clearly show that OCI’s lunar image acquisition is working as intended and will provide accurate data for OCI’s on-orbit radiometric characterization. The hyperspectral lunar irradiances provided by OCI are expected to become a valuable data set for the evaluation of lunar irradiance models.

calibration↗

NASA NTRSDate not supplied

PACE OCI Straylight and Crosstalk Evaluation using Moon

The Ocean Color Instrument (OCI) onboard NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission has performed three monthly lunar calibrations. The moon is an extended source over a large dark background, making it an ideal target for evaluating OCI’s straylight and crosstalk performance. The lunar data analysis showed the straylight and crosstalk to be lower than the prelaunch measurements, especially in the along-track direction, where very little straylight is detected. Based on lunar data, the prelaunch measured crosstalk coefficients were reduced, and a crosstalk correction was tested on both lunar and solar calibration data. Applying the revised crosstalk correction, the crosstalk contaminations are significantly reduced to under 0.1% at 2-3 pixels away from the lunar boundary for bands above 350 nm. Below 350 nm, the crosstalk correction residuals gradually increase due to a lack of high-quality prelaunch measurements. Lastly, applying the crosstalk correction changes the calibrated radiance for all science data. This is due to the different spectral shapes between the solar diffuser and the observed scenes. For the moon, the crosstalk correction has an impact of ~0.4% on the overall calibrated radiance for the 400 – 600 nm bands and up to 20% impact on the UV bands.

Shihyan Lee↗