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NASA NTRS2023

Lessons Learned From Evaluation and Mitigation of Space Charging Threat Due to Use of Isolated (Hybrid) Bearings on the Pace Ocean Color Instrument

A high precision, high resolution Ocean Color Instrument (OCI) was developed for the Plankton, Aerosol, Cloud ocean Ecosystem (PACE) mission which required the use of electrically isolated Hybrid Bearings (silicon nitride balls). While desirable for technical performance of the instrument, this application caused portions of the instrument to become electrically isolated and come under threat of space charging effects from charged particles and the resultant differential charging. An evaluation of the environment, susceptibility of the components, such as bearings and electronics, and mitigation strategies were performed. As part of that process, simulations of the charging environment, analysis of internal mechanism charging and prediction of most likely discharge paths, testing of the bearings for susceptibility as well as resulting damage were performed and analyzed. Additionally, a novel method to deal with charging was developed. Considerations for dealing with electrically isolated mechanisms, results of the above-mentioned efforts as well as lessons learned are presented.

space charging↗

NASA NTRSDate not supplied

NASA’s PACE Ocean Color Instrument Thermal Design Evolution: from Goddard’s Instrument Design Lab through Flight Development

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, set to launch in 2024, seeks to provide data continuity for the ocean color, aerosol and cloud measurements acquired by NASA’s on-orbit Earth Science observatories since the 1990s. It will accomplish this through its Ocean Color Instrument (OCI), an optical spectrometer being developed for hyper-spectral measurements in the ultraviolet-to-near-infrared band between 340 nm and 2260 nm. Although OCI’s instrument architecture will provide greater insight and resolution than its predecessors in this wavelength range, the engineering required to achieve this also poses a greater challenge. In thermal engineering, this translates to a more complex thermal control approach to address high heat dissipations, stringent stabilities, the volume of heat that requires transport, and changing thermal environments due to tilting of the entire instrument ±20° twice per orbit. This current work explores how the PACE OCI instrument design has evolved from its initial conception in NASA Goddard’s Instrument Design Laboratory (IDL) to the current iteration of its flight design. The IDL studies explored three separate instrument configurations and two spatial resolutions per configuration, which were then down selected to a single instrument type and spatial resolution for flight instrument development. OCI subsequently went through major project milestones, including Preliminary Design Review (PDR), Critical Design Review (CDR), Pre-Environmental Review (PER) and Pre-Ship Review (PSR), with significant design updates along the way. This paper aims to provide a comprehensive account of OCI’s thermal control architecture evolution and the engineering drivers that have shaped it, with the goal of identifying trends spanning the full instrument development timeline to inform and advance future instrument thermal designs.

PACE↗

NASA NTRSDate not supplied

NASA’s PACE Ocean Color Instrument Thermal Design Evolution: from Goddard’s Instrument Design Lab through Flight Development

PACE↗

NASA NTRS2019

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412, 443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 × 10−4, 5.49 × 10−4, 4.48 × 10−4, 2.51 × 10−4, 8.83 × 10−5, and 1.36 × 10−4 sr−1, respectively, and 1.09 × 10−2 mg m−3 for the chlorophyll-a concentration (Chl-a), 2.09 × 10−3 m−1 for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (ag (412)), and 3.7 mg m−3 for particulate organic carbon (POC). These Rrs values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Geostationary Ocean Color Imager (GOCI)↗

NASA NTRS2018

PACE Technical Report Series, Volume 7: Ocean Color Instrument (OCI) Concept Design Studies

Extending OCI hyperspectral radiance measurements in the ultraviolet to 320 nm on the blue spectrograph enables quantitation of atmospheric total column ozone (O3) for use in ocean color atmospheric correction algorithms. The strong absorption by atmospheric ozone below 340 nm enables the quantification of total column ozone. Other applications are possible but were not investigated due to their exploratory nature and lower priority.The first step in the atmospheric correction processing, which converts top-of-the-atmosphere radiances to water-leaving radiances, is removal of the absorbance by atmospheric trace gases such as water vapor, oxygen, ozone and nitrogen dioxide. Details of the atmospheric correction process currently used by the Ocean Biology Processing Group (OBPG) and will be employed for PACE with appropriate modifications, are described by Mobley et al. [2016]. Atmospheric ozone absorbs within the visible to near-infrared spectrum between ~450 nm and 800nm and most appreciably between 530 nm and 650 nm, a spectral region critical for maintaining NASA's chlorophyll-a climate data record and for PACE algorithms planned to characterize phytoplankton community composition and other ocean color products.While satellite-based observations will likely be available during PACE's mission lifetime, the difference in acquisition time with PACE, the coarseness in their spatial resolution, and differences in viewing geometries will introduce significant levels of uncertainties in PACE ocean color data products.

Cetinic, Ivona↗

NASA NTRS2022

Estimating pixel-level uncertainty in ocean color retrievals from MODIS

The spectral distribution of marine remote sensing reflectance, R(rs), is the fundamental measurement of ocean color science, from which a host of bio-optical and biogeochemical properties of the water column can be derived. Estimation of uncertainty in these derived properties is thus dependent on knowledge of the uncertainty in satellite-retrieved R(rs) (u(c)(R(rs))) at each pixel. Uncertainty in R(rs), in turn, is dependent on the propagation of various uncertainty sources through the R(rs) retrieval process, namely the atmospheric correction (AC). A derivative-based method for uncertainty propagation is established here to calculate the pixel-level uncertainty in R(rs), as retrieved using NASA’s multiple-scattering epsilon (MSEPS) AC algorithm and verified using Monte Carlo (MC) analysis. The approach is then applied to measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, with uncertainty sources including instrument random noise, instrument systematic uncertainty, and forward model uncertainty. The uc(Rrs) is verified by comparison with statistical analysis of coincident retrievals from MODIS and in situ Rrs measurements, and our approach performs well in most cases. Based on analysis of an example 8-day global products, we also show that relative uncertainty in R(rs) at blue bands has a similar spatial pattern to the derived concentration of the phytoplankton pigment chlorophyll-a (chl-a), and around 7.3%, 17.0%, and 35.2% of all clear water pixels (chl-a ≤ 0.1 mg/cu.m) with valid u(c)(R(rs)) have a relative uncertainty ≤ 5% at bands 412 nm, 443 nm, and 488 nm respectively, which is a common goal of ocean color retrievals for clear waters. While the analysis shows that u(c)(R(rs)) calculated from our derivative-based method is reasonable, some issues need further investigation, including improved knowledge of forward model uncertainty and systematic uncertainty in instrument calibration.

Pixel-level uncertainty↗

NASA NTRS2020

Improving Quantitative Laboratory Analysis of Phycobiliproteins to Provide High Quality Validation Data for Ocean Color Remote Sensing Algorithm

Identification and characterization of phytoplankton communities and their physiology is a primary aim of NASA's PACE satellite mission. The concentration and composition of phytoplankton pigments modulate the spectral distribution of light emanating from the ocean, which is measured by ocean color satellites, and thus provide critical information on phytoplankton community composition and physiological parameters. One diagnostic class of pigments not routinely well-characterized is the phycobiliproteins (PBPs), and NASA has a requirement to collect and distribute high quality in situ data in support of data product validation activities for ocean color missions. Phycobiliproteins are light-harvesting proteins that are the predominant photosynthetic pigments in some classes of phytoplankton including cyanobacteria, such as Synechococcus, Trichodesmium, and Microcystis. With the advance of hyperspectral ocean color sensors such as on PACE (expected to launch in late 2022), it is essential that we implement routine analysis of PBPs that satisfies several considerations: reproducible, high extraction efficiency for a variety of environments, and Suitable for large scale analysis. Published techniques for PBP analysis vary in recommendations for: collection, extraction, disruption mode, and analysis; evidence suggests the variation in results may depend at least in part on the species and even strain(s) of interest. Experiments that tested variations in these parameters have drawn very different conclusions regarding extraction efficiency and reproducibility. Cyanobacteria are more difficult to extract than other PBP-containing algae such as cryptophytes, but can be important primary producers. We used a cryptophyte (Rhodomonas salina) and cyanobacterium (Synechococcus sp.) to compare extraction efficiencies of water samples concentrated via centrifugation to filtered samples using two different extraction buffers (phosphate and asolectin-CHAPS). Samples were analyzed on a fluorometer configured for PC and PE detection. The results have important implications for collection and storage of samples for routine analysis; some previous studies (although not all) have suggested that filtered samples have a much lower extraction efficiency than whole water samples.

Kenemer, Christopher↗

NASA NTRS1997

Analysis of Photosynthetic Rate and Bio-Optical Components from Ocean Color Imagery

Our research over the last 5 years indicates that the successful transformation of ocean color imagery into maps of bio-optical properties will require continued development and testing of algorithms. In particular improvements in the accuracy of predicting from ocean color imagery the concentration of the bio-optical components of sea as well as the rate of photosynthesis will require progress in at least three areas: (1) we must improve mathematical models of the growth and physiological acclimation of phytoplankton; (2) we must better understand the sources of variability in the absorption and backscattering properties of phytoplankton and associated microparticles; and (3) we must better understand how the radiance distribution just below the sea surface varies as a function sun and sky conditions and inherent optical properties.

Kiefer, Dale A.↗

NASA NTRS1987

Future U.S. ocean color missions - OCI, MODIS and HIRIS

NASA has been working to develop an Ocean Color Imager (OCI). The Earth Observing Satellite Company (EOSAT) is considering flying an ocean and land wide-field color instrument which would meet specified requirements on Landsat 6 or 7 planned for launch in 1989 and 1991, respectively. It would provide eight ocean color channels for improved atmospheric correction and in-water algorithms, global coverage and near real-time data for operational uses. In the mid 1990's NASA is planning to fly a Moderate Resolution Imaging Spectrometer (MODIS) and a High Resolution Imaging Spectrometer (HIRIS) as part of the Earth Observing System on the Polar Platform of the Space Station. These instruments are array spectrometers which would provide full spectral resolution in the visible and infrared. This opens the possibility of separating different groups of phytoplankton, suspended sediments and other substances in the water.

Davis, C. O.↗

NASA NTRS2023

The Impact and Estimation of Uncertainty Correlation for Multi-Angle Polarimetric Remote Sensing of Aerosols and Ocean Color

Multi-angle polarimetric (MAP) measurements contain rich information for characterization of aerosol microphysical and optical properties that can be used to improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere-ocean system, although uncertainty correlation among measurements is generally ignored due to lack of knowledge on its strength and characterization. In this work, we provide a practical framework to evaluate the impact of the angular uncertainty correlation from retrieval results and a method to estimate correlation strength from retrieval fitting residuals. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on neural network forward models, is used to conduct the retrievals and uncertainty quantification. In addition, we also discuss a flexible approach to include a correlated uncertainty model in the retrieval algorithm. The impact of angular correlation on retrieval uncertainties is discussed based on synthetic AirHARP and HARP2 measurements using a Monte Carlo uncertainty estimation method. Correlation properties are estimated using auto-correlation functions based on the fitting residuals from both synthetic AirHARP and HARP2 data and real AirHARP measurement, with the resulting angular correlation parameters found to be larger than 0.9 and 0.8 for reflectance and DoLP, respectively, which correspond to correlation angles of 10° and 5°. Although this study focuses on angular correlation from HARP instruments, the methodology to study and quantify uncertainty correlation is also applicable to other instruments with angular, spectral, or spatial correlations, and can help inform laboratory calibration and characterization of the instrument uncertainty structure.

PACE↗

NASA NTRS2016

Atmospheric Correction for Satellite Ocean Color Radiometry

This tutorial is an introduction to atmospheric correction in general and also documentation of the atmospheric correction algorithms currently implemented by the NASA Ocean Biology Processing Group (OBPG) for processing ocean color data from satellite-borne sensors such as MODIS and VIIRS. The intended audience is graduate students or others who are encountering this topic for the first time. The tutorial is in two parts. Part I discusses the generic atmospheric correction problem. The magnitude and nature of the problem are first illustrated with numerical results generated by a coupled ocean-atmosphere radiative transfer model. That code allow the various contributions (Rayleigh and aerosol path radiance, surface reflectance, water-leaving radiance, etc.) to the topof- the-atmosphere (TOA) radiance to be separated out. Particular attention is then paid to the definition, calculation, and interpretation of the so-called "exact normalized water-leaving radiance" and its equivalent reflectance. Part I ends with chapters on the calculation of direct and diffuse atmospheric transmittances, and on how vicarious calibration is performed. Part II then describes one by one the particular algorithms currently used by the OBPG to effect the various steps of the atmospheric correction process, viz. the corrections for absorption and scattering by gases and aerosols, Sun and sky reflectance by the sea surface and whitecaps, and finally corrections for sensor out-of-band response and polarization effects. One goal of the tutorial-guided by teaching needs- is to distill the results of dozens of papers published over several decades of research in atmospheric correction for ocean color remote sensing.

MODIS↗

NASA NTRS1985

Radiometric comparison of two ocean color scanners Nimbus-7/CZCS and OSTA-1/OCE

On November 14, 1981 the area around the Gibraltar Strait was observed by two different ocean color scanners: a Space Shuttle-borne Ocean Color Experiment and Coastal Zone Color Scanner (Nimbus-7/CZCS). This presented an opportunity to study the gradual degradation of the CZCS sensitivity by comparing the two sensors. Upwelling radiances from eleven targets were compared. The results of the analysis indicate that the CZCS sensitivities at channels 1 and 2 are down to 65 percent and 78 percent. However, the evidence for channels 3 and 4 deterioration could not be found.

Kim, H. H.↗

NASA NTRSDate not supplied

Optical and Detector Design of the Ocean Color Instrument for the NASA Pace Mission

The Ocean Color Instrument (OCI) on NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem mission is a hyperspectral imager with high SNR, precision and dynamic range, and with a very low striping artifact level in the 342-887 nm wavelength range with a spectral resolution of 5 nm in 2.5 nm steps, providing a significant technological advancement over previous ocean imagers. To achieve this, OCI is designed with specialized optical imaging and opto-electronic detection systems that push the boundaries of several state-of-the-art technologies. This paper provides an overview of these systems together with their achieved performances and discussions of their key design challenges.

Remote sensing↗

NASA NTRSDate not supplied

Optical and Detector Design of the Ocean Color Instrument for the NASA Pace Mission

Remote sensing↗

NASA NTRS1981

Preliminary analysis of ocean color scanner data from Superflux III

The ocean color scanner collected data Superflux III Experiment Single channel gray scale data products generated 5 minutes after the scanner data were collected showed details of the Chesapeake Plume structure, suggesting that this quick-look capability could have potential use to experimenters in real time. The Chesapeake Bay Plume extended offshore between 5 and 7 nautical miles on two occasions. The scanner data also show many other water features within the lower bay itself.

Ohlhorst, C. W.↗

NASA NTRS2002

Scale Closure in Upper Ocean Optical Properties: From Single Particles to Ocean Color

Predictions of chlorophyll concentration from satellite ocean color are an indicator of primary productivity, with implications for foodwebs, fisheries, and the global carbon cycle. Models describing the relationship between optical properties and chlorophyll do not account for much of the optical variability observed in natural waters, because of the presence of seawater constituents that do not covary with phytoplankton pigments. in order to understand variability in these models, the optical contributions of seawater constituents were investigated. A combination of Mie theory and flow cytometry was used to determine the diameter, complex refractive index, and optical cross-sections of individual particles. In New England continental shelf waters, eukaryotic phytoplankton were the main particle contributors to absorption and scaftering. Minerals were the main contributor to backscattering (bb) in the spring, whereas in the summer both minerals and detritus contributed to bb. Synechococcus and heterotrophic bacteria were relatively unimportant optically. Seasonal differences in the spectral shape of remote sensing reflectance, Rrs, were contributed to approximately equally by eukaryotic phytoplankton absorption, dissolved absorption, and non-phytoplankton bb. Differences between measurements of bb and Prs and modeled values based on chlorophyll concentration were caused by higher dissolved absorption and non-phytoplankton bb than were assumed by the model.

Green, Rebecca E.↗

NASA NTRS2002

Seasonal to Decadal-Scale Variability in Satellite Ocean Color and Sea Surface Temperature for the California Current System

Support for this project was used to develop satellite ocean color and temperature indices (SOCTI) for the California Current System (CCS) using the historic record of CZCS West Coast Time Series (WCTS), OCTS, WiFS and AVHRR SST. The ocean color satellite data have been evaluated in relation to CalCOFI data sets for chlorophyll (CZCS) and ocean spectral reflectance and chlorophyll OCTS and SeaWiFS. New algorithms for the three missions have been implemented based on in-water algorithm data sets, or in the case of CZCS, by comparing retrieved pigments with ship-based observations. New algorithms for absorption coefficients, diffuse attenuation coefficients and primary production have also been evaluated. Satellite retrievals are being evaluated based on our large data set of pigments and optics from CalCOFI.

Mitchell, B. Greg↗

NASA NTRS1973

Research needs in ocean color data analysis

The success of the effort to extract several subsurface oceanographic parameters from remotely sensed ocean color data will depend to a great extent upon the existence of adequate theoretical models relating the desired oceanographic parameters to the upwelling radiances to be observed. In order to guide the development of these models, and to check their accuracies, a considerable amount of experimental work must be performed. The theoretical and experimental work needed to develop techniques for the quantitative analysis of satellite ocean color data is described.

Mccluney, W. R.↗