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At least 451 records · Page 25

Corrections to MODIS Terra Calibration and Polarization Trending Derived from Ocean Color Products

Remotely sensed ocean color products require highly accurate top-of-atmosphere (TOA) radiances, on the order of 0.5% or better. Due to incidents both prelaunch and on-orbit, meeting this requirement has been a consistent problem for the MODIS instrument on the Terra satellite, especially in the later part of the mission. The NASA Ocean Biology Processing Group (OBPG) has developed an approach to correct the TOA radiances of MODIS Terra using spatially and temporally averaged ocean color products from other ocean color sensors (such as the SeaWiFS instrument on Orbview-2 or the MODIS instrument on the Aqua satellite). The latest results suggest that for MODIS Terra, both linear polarization parameters of the Mueller matrix are temporally evolving. A change to the functional form of the scan angle dependence improved the quality of the derived coefficients. Additionally, this paper demonstrates that simultaneously retrieving polarization and gain parameters improves the gain retrieval (versus retrieving the gain parameter only).

Polarization↗

Hemispherical Pluto and Charon Color Composition From New Horizons

New Horizons flew by Pluto and its moons on July 14, 2015 [1]. In the days prior to the closest approach (C/A), panchromatic and color observations of Pluto and Charon were made covering a fully complete range of longitudes. Although only a fraction of this "late-approach" data series has been transmitted to the ground, the results indicate Pluto's latitudinal coloring trends seen on the encounter hemisphere continues on the far side. Charon's red pole is visible from a multitude of longitudes and its colors are uniform with longitude at lower latitudes.

Pluto↗

Regional Changes in Earths Color and Texture as Observed From Space Over a 15-Year Period

Earth-observing satellites provide global observations of many geophysical variables. As these variables are derived from measured radiances, the underlying radiance data are the most reliable sources of information for change detection. Here, we identify statistically significant trends in the color and spatial texture of the Earth as viewed from multiple directions from the Multi-angle Imaging SpectroRadiometer (MISR), which has been sampling the angular distribution of scattered sunlight since 2000. Globally, our results show that the Earth has been appearing relatively bluer (up to 1.6 % per decade from both nadir and oblique views) and smoother (up to 1.5 % per decade only from oblique views) over the past 15 years. The magnitude of the global blueing trends is comparable to that of uncertainties in radiometric calibration stability. Regional shifts in color and texture, which are significantly larger than global means, are observed, particularly over polar regions, along the boundaries of the subtropical highs, the tropical western Pacific, Southwestern Asia, and Australia. We demonstrate that the large regional trends cannot be explained either by uncertainties in radiometric calibration or variability in total or spectral solar irradiance; hence, they reflect changes internal to the Earths climate system. The 15-year-mean true color composites and texture images of the Earth at both nadir and oblique views are also presented for the first time.

regional trends↗

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

Li, Yonghong↗

Charon's Light Curves, as Observed by New Horizons' Ralph Color Camera (MVIC) on Approach to the Pluto System.

Light curves produced from color observations taken during New Horizons approach to the Pluto-system by its Multi-spectral Visible Imaging Camera (MVIC, part of the Ralph instrument) are analyzed. Fifty seven observations were analyzed, they were obtained between 9th April and 3rd July 2015, at a phase angle of 14.5 degrees to 15.1 degrees, sub-observer latitude of 51.2 degrees North to 51.5 degrees North, and a sub-solar latitude of 41.2 degrees North. MVIC has four color channels; all are discussed for completeness but only two were found to produce reliable light curves: Blue (400-550 nm) and Red (540-700 nm). The other two channels, Near Infrared (780-975 nm) and Methane-Band (860-910 nm), were found to be potentially erroneous and too noisy respectively. The Blue and Red light curves show that Charon's surface is neutral in color, but slightly brighter on its Pluto-facing hemisphere. This is consistent with previous studies made with the Johnson B and V bands, which are at shorter wavelengths than that of the MVIC Blue and Red channel respectively.

Howett, C. J. A.↗

Ocean Color Instrument Integration and Testing

This paper describes the plans, flows, key facilities, components and equipment necessary to fully integrate, functionally test, qualify and calibrate the Ocean Color Instrument (OCI) on the Plankton, Aerosols, Clouds, and oceans Ecosystem (PACE) observatory. PACE is currently in the design phase of mission development. It is scheduled to launch in 2022, extending and improving NASA's twenty-year record of satellite observations of global ocean biology, aerosols and clouds. PACE will advance the assessment of ocean health by measuring the distribution of phytoplankton, which are small plants and algae that sustain the marine food web. It will also continue systematic records of key atmospheric variables associated with air quality and the Earth's climate. PACE's primary sensor, the OCI, is a highly advanced optical spectrometer that will be used to measure properties of light over portions of the electromagnetic spectrum. It will enable continuous measurement of light at finer wavelength resolution than previous NASA satellite sensors, extending key system ocean color data records for climate studies. The color of the ocean is determined by the interaction of sunlight with substances or particles present in seawater such as chlorophyll. By monitoring global phytoplankton distribution and abundance with unprecedented detail, the OCI will contribute to a better understanding of the complex systems that drive ocean ecology and it's impacts on global fisheries. This paper will focus on the Integration and Test (I&T) activities for OCI while it is at the NASA Goddard Space Flight Center. The OCI integration consists of assembly and alignment of the rotating telescope, electronics box integration, fixed deck assembly integration, thermal systems integration and the final assembly and testing. This I&T phase will be followed by the OCI calibration and characterization, environmental tests which include electromagnetic interference (EMI)/electromagnetic compatibility (EMC), vibration with sine sweep, acoustics, shock, thermal balance, thermal vacuum, mass properties and center of gravity. This paper will briefly discuss OCI shipment and delivery to the spacecraft vendor for observatory level I&T as well as some launch preparation activities.

Petro, Susanna↗

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↗

Vicarious Calibration of GOCI for the SeaDAS Ocean Color Retrieval

A key on-orbit calibration step for satellite remote sensing of ocean color is the vicarious calibration. This establishes the final gains for each spectral band on the sensor that minimize bias in the retrieved ocean color signal. The vicarious calibration is specific to the instrument and the atmospheric correction algorithm. The vicarious calibration gains for the Geostationary Ocean Color Imager (GOCI) are presented here, which were derived to optimize the performance ofNASA's standard atmospheric correction algorithm as implemented in the l2gen code and distributed through the SeaDAS open-source software package. Following NASA's protocols, the near-infrared(NIR) bands were calibrated first, and the visible bands were then calibrated relative to this fixed NIR calibration. The gain for the 745-nm NIR band was derived using a fixed aerosol model, which waschosen based on the Angstrom Coefficients derived from MODIS onAqua (MODISA). For the vicarious gains of the visible bands, twosources for the target water-leaving radiances were tested: matchupsfrom MODISA and climatological data from SeaWiFS. A validation analysis using AERONET-OC data shows an improvement in sensor performance when compared with results using the current vicarious gains and results using no vicarious calibration. Good agreement was found in vicarious gains derived using both concurrent MODISA and climatological SeaWiFS as vicarious calibration data sources. These results support the use of a concurrent sensor for the vicarious calibration when in situ data are not available and demonstrate that using climatology from a well-calibrated sensor like SeaWiFSfor the vicarious calibration is a valid alternative when it is not possible to use a concurrent sensor or in situ data. We recommend using the gains derived from concurrent GOCI matchups with MODISA for GOCI processing in SeaDAS/l2gen.

Concha, Javier↗

Transfer Learning to Generate True Color Images from GOES-16

Along with scientific applications, Geostationary imagery is often used to learn about weather patterns through true color visualizations. NOAA/NASA's GOES-R series of satellites uses the advanced baseline imager with 16-bands which, unlike previous generations, does not include the green wavelength (500-565 nm) and hence cannot directly generate true color images. However, Himawari, Japan's geostationary satellite, uses a similar 16-band advanced Himawari imager that does include a green band (but missing cirrus). In this work, we show how transfer learning with convolutional neural networks can be applied across satellites to generate "virtual sensors". We apply this approach to generate a green band for GOES-16 and present near true color images.

transfer learning↗

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↗

Surface Plasmon Tunable Color Filter and Projection Display

A novel projection display, based on a new phenomenon of voltage-induced color-selective absorption with surface plasmons, are able to generate bright image on a large screen with high efficiency. In addition, neither color filters or nor phosphors are needed to generate the color.

surface↗

The color and binarity of (486958) 2014 MU69 and other long-range New Horizons Kuiper Belt targets

The Hubble Space Telescope (HST) measured the colors of eight Kuiper Belt Objects (KBOs) that will be observed by the New Horizons spacecraft including its 2019 close fly-by target the Cold Classical KBO (486958) 2014 MU(69). We find that the photometric colors of all eight objects are red, typical of the Cold Classical dynamical population within which most reside. Because 2014 MU(69) has a similar color to that of other KBOs in the Cold Classical region of the Kuiper Belt, it may be possible to use the upcoming high-resolution New Horizons observations of 2014 MU(69) to draw conclusions about the greater Cold Classical population. Additionally, HST found none of these KBOs to be binary within separations of ~0.06 arcsec (~2000 km at 44 AU range) and Δm ≤ 0.5. This conclusion is consistent with the lower fraction of binaries found at relatively wide separations. A few objects appear to have significant photometric variability, but our observations are not of sufficient signal-to-noise or time duration for further interpretation.

S.D. Benecchi↗

Assessing Net Growth of Phytoplankton Biomass on Hourly to Annual Timescales Using the Geostationary Ocean Color Instrument

Questions of whether diurnal changes in carbon fixation affect the global carbon budget cannot be answered using the present generation of polar orbiting ocean color sensors that can only retrieve one image daily. Here, we present novel satellite-derived indices of chlorophyll-based production based on the Geostationary Ocean Color Imager (GOCI), whose hourly imaging capability offer the potential for direct estimates of net phytoplankton growth over hourly to seasonal time scales. Our results reveal large variations in net chlorophyll growth in the GOCI study region, both over the day and between seasons. Hourly changes in chlorophyll concentration are highest during spring while growth rates show maxima during the winter. We show seasonal relationships between growth and photon flux. Our study suggests that Geostationary Ocean Color data can be used to constrain phytoplankton productivity on diurnal time scales and be an essential tool to better understand diurnal growth patterns over large spatial regions.

Joseph E. Salisbury↗

Performance Metrics for the Assessment of Satellite Data Products: An Ocean Color Case Study

Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coefficient of determination (r2), root mean square error, and regression slopes, are most appropriate for Gaussian distributions without outliers and, therefore, are often not ideal for ocean color algorithm performance assessment, which is often limited by sample availability. In contrast, metrics based on simple deviations, such as bias and mean absolute error, as well as pair-wise comparisons, often provide more robust and straightforward quantities for evaluating ocean color algorithms with non-Gaussian distributions and outliers. This study uses a SeaWiFS chlorophyll-a validation data set to demonstrate a framework for satellite data product assessment and recommends a multimetric and user-dependent approach that can be applied within science, modeling, and resource management communities.

remote sensing↗

An assessment of the impact of system spectral response parameters on spectral shape and algal bloom detection for the GeoXO ocean color instrument (OCX)

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral ocean color instrument (OCX) in geostationary orbit slated for operations by the early 2030s. Shared international focus has led to a diverse legacy of space-based remote sensing ocean color missions that have and will continue to provide ocean color products into the future at a variety of spatial, temporal, and spectral resolutions. This work reports on an investigation of the impacts of system spectral response parameters on spectral shape and algal bloom detection for the planned OCX instrument. A large dataset in-situ spectra, from a variety of locations and water cases collected with an above water spectrometer, was used to simulate OCX observations of varying system spectral response parameters. The OCX Performance Operational Requirements Document (PORD) level spectral resolution and sampling are varied concurrently and the location of band centers is varied independently. The impacts to the spectral shape using hyperspectral signature analysis, as well as the impacts to two heritage multispectral algal bloom detection algorithms – red band difference (RBD) and Karenia brevis bloom index (KBBI) – are assessed considering both changes in resolution/sampling and band center location. This work provides a quantitative assessment of the impacts of system spectral response requirements on both the spectral shape of observations as well as the algal bloom detection to provide insight on how various instrument performance parameters influence science and operational utility of OCX.

Monica Cook↗

Effective Visualization of Radar Data for Users Impacted By Color Vision Deficiency

Color Vision Deficiency (CVD) is a decreased ability to discern between particular colors. Eight percent of genetic males and half a percent of genetic females have some form of CVD, with many in the radar community falling into this group. When presenting data on a two-dimensional plane, it is common to use colors to represent values via a colormap. Colormap choice in the radar community is influenced by the ability to highlight scientifically interesting features in data, institutional choices, and domain dominance of legacy colormaps. The problem with these current colormaps is that many do not project well for those with CVD (i.e., green next to red). In working with the CVD community to address this problem, multiple colormaps for moments such as equivalent reflectivity factor and Doppler velocity were created for users with forms of CVD such as deuteranomaly, protanomaly, protanopia, and deuteranopia using Python tools such as colorspacious and viscm. We show how these colormaps can improve interpretability for four cases: a mesoscale convective system, a pyrocumulonimbus storm, a wintertime mid-latitude cyclone, and widespread storms with a large bird migration. These new radar equivalent reflectivity factor, Doppler velocity, and polarization colormaps are designed to highlight rain, frozen precipitation, non-meteorological targets, velocity-based items, be perceptually uniform, and visually friendly for those with CVD.

Zachary Sherman↗

Evaluation of Vertical Patterns in Chlorophyll-A Derived From A Data Assimilating Model of Satellite-Based Ocean Color

Satellite-based sensors of ocean color have become the primary tool to infer changes in surface chlorophyll, while BGC-Argo floats are now filling the information gap at depth. Here we use BGC-Argo data to assess depth-resolved information on chlorophyll-a derived from an ocean biogeochemical model constrained by the assimilation of surface ocean color remote sensing. The data-assimilating model replicates well the general seasonality and meridional gradients in surface and depth-resolved chlorophyll-a inferred from the float array in the Southern Ocean. On average, the model tends to overestimate float-based chlorophyll, particularly at times and locations of high productivity such as the beginning of the spring bloom, subtropical deep chlorophyll maxima, and non-iron limited regions of the Southern Ocean. The highest model RMSE in the upper 50 m with respect to the float array is of 0.6 mg Chl m −3 , which should allow the detection of seasonal changes in float-based biomass (varying between 0.01 and >1 mg Chl m −3 ) but might hinder the identification of subtle changes in chlorophyll at narrow local scales. Both model and float profiling data show good agreement with in situ data from station ALOHA, with model estimates showing a slight accuracy edge in inferring depth-resolved observations. Uncertainties in float bio-optical estimates impede their use as a reliable benchmark for validation, but the general qualitative agreement between model and float data provides confidence in the ability of model to replicate biogeochemical features below the surface, where data is not directly constrained by the assimilation of satellite ocean color.

Lionel A Quintero↗

Can color-mixed system technology improve lighting quality and energy efficiency?

LEDs have made tremendous inroads in the architectural lighting market but have yet to reach their potentials for energy efficiency or delivering benefit to building occupants. Progress in color-mixed systems can contribute to both goals with anticipated benefits for luminous efficacy, application efficacy, human health, plant growth, and general satisfaction. These benefits can be achieved because unlike static, broadband white light emitters that are ubiquitous today, color-mixed systems offer spectral flexibility. The prospect of widespread implementation of tunable lighting by the 2030s is exciting, but it will require overcoming several challenges and greater responsibility from the specifier. Now is the time to begin planning and developing effective strategies for deploying color-mixed LED systems. Here we examine the pros, cons, and development path for this technology.

Royer, Michael P.↗