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NASA NTRSDate not supplied

International Satellite Cloud Climatology Project (ISCCP) Stage DX Pixel Level Cloud Product - Revised Algorithm in Native (NAT) Format (ISCCP_DX_NAT)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=TROPOSPHERE] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=30 Km; Longitude_Resolution=30 Km; Temporal_Resolution=3 Hourly].

CLOUD ICE↗
NASA NTRSDate not supplied

Electroluminescence Imaging: A Quantitative Characterization Technique to Measure Dust Occlusion of Solar Cells

Electroluminescence (EL) imaging is a qualitative characterization technique that is typically used to identify cracks, corrosion, and other defects in solar cells. It consists of imaging a cell under forward bias, where the solar cell emits photons due to radiative electron-hole pair recombination. Over the past few years, our team has expanded this into a quantitative technique with the help of image processing. We have primarily used this method to investigate lunar dust occlusion of solar cells and arrays. Lunar dust accumulation on solar cells is a major concern because it directly limits light accessible to the cell, decreasing power output. Many teams are working to develop dust mitigation technology to protect these arrays on the surface of the Moon, but thoroughly characterizing their efficacy is important to ensure their success prior to launch. Here, we present EL as a quantitative characterization technique to observe dust coverage on solar cells that, when coupled with IV performance measurements, can offer unique insights into how dust coverage impacts power output. Quantitative electroluminescence imaging works by running EL images through an image processing script that first grayscales the image then plots a histogram of the brightness of each pixel. On its own, it does not offer much insight into a solar cell’s performance. However, when comparing images to a baseline pristine, undamaged, or uncoated solar cell, it can quickly provide information about the impacts of surface contaminants or damage to the cell. Here, we present a case study where quantitative EL is used to measure the efficacy of dust mitigation technology for flexible solar arrays and discuss the lessons learned about dust mitigation, testing with lunar simulant, and this characterization technique.

photovoltaics↗
NASA NTRS2012

In-Flight Performance of the TES Loop Heat Pipe Rejection System: Seven Years in Space

The Tropospheric Emission Spectrometer (TES) is an infrared, high spectral resolution Fourier transform spectrometer with a 3.3 to 15.4 micron wavelength coverage. TES is a scanning instrument intended for determining the chemical state of the Earth's lower atmosphere (troposphere) from the surface to 30+ km. TES produces vertical profiles of important pollutant and greenhouse gases such as carbon monoxide, ozone, methane, and water vapor on a global scale every other day. TES was launched into orbit onboard NASA's earth Observing System Aura spacecraft on July 15, 2004 from Vandenberg Air Force Base, California.

tropospheric emission spectrometer↗
NASA NTRS2015

Soil Moisture Active and Passive (SMAP) White-Painted Expanded Polystyrene (EPS) Radome Survivability Test

NASA's SMAP Mission launched in January 2015 into a 685 km near-polar, sun-synchronous orbit. The SMAP instrument architecture incorporates an L-band radar and radiometer which share a common feedhorn and mesh reflector. The instrument rotates about the nadir axis at approximately 15 rpm, thereby providing a conically scanning wide swath antenna beam that is capable of achieving global coverage within three days. The radiometer and its associated electronics have tight thermal stability requirements in order to meet the required surface emittance measurement precision from space. Maintaining the thermal stabilities is quite challenging because the radiometer is located on a spinning platform that can either be in full sunlight or eclipse, and thus exposed to a highly transient environment. Stability requirements were met by integrating a light-weight Expanded Polystyrene (EPS) radome into the design to prevent solar illumination of the feed horn interior. The radome was painted white since the thermo-optical properties of bare sunlit EPS degrade rapidly over the three-year mission. Milling of the EPS and solvent within the white paint created cavities on the EPS surface which may introduce localized hot spots possibly violating the EPS glass transition temperature of 96degC and leading to structural integrity concerns. A three-day thermal test was conducted in a vacuum chamber to verify survivability of the radome during a simulated non-spin fault condition at end of mission. A portable solar simulator illuminated the test article and the beam irradiance was kept nearly constant during the entire 50 hour test, except during the first hour which simulated the expected 79degC on-orbit surface temperature of the radome. The test article survived based on the established pass criteria for three separate metrics: dimensional, optical property, and color. If any hot spots exist locally, they did not cause any observable permanent deformation when compared to pre- and post-test images. The test results increase confidence that there is a high probability that the radome will survive the worst-case scenario of a no-spin fault condition at the end of mission.

Mikhaylov, Rebecca↗
NASA NTRS2019

Assessment of Satellite Sea Surface Salinity Products Using a Coupled ENSO Prediction Model

Much work has gone into revising and updating algorithms for converting satellite-measured radiances to useful ocean variables like sea surface salinity (e.g. SMOS - Boutin et al., 2017, SMAP - Fore et al., 2016 and Aquarius - Meissner et al., 2018). As part of our Ocean Salinity Science Team work, we utilize an intermediate-complexity air/sea coupled model as a transfer function to test if more mature satellite SSS model algorithms actually improve ENSO forecast skill. For initialization of the coupled forecast, we demonstrate that the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10S-5N. In addition, salting near the ITCZ leads to a deepening of the mixed layer and thermocline near 8N. These patterns together provide the background state to amplify equatorial Kelvin waves and improve ENSO hindcasts (Hackert et al., 2019). Here we extend this work to compare the impact of various pairs of original and improved satellite SSS algorithms. For instance we compare SMAP V4.1 with the latest, SMAP V4.2, to see what impact algorithm improvements may have on ENSO forecasts. SSS observations are tested on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts by initializing twelve-month forecasts for each month of available data. All experiments assimilate satellite sea level (SL), sea surface temperature (SST), and in situ subsurface temperature and salinity observations (Tz, Sz). Additionally various satellite, blended, and in-situ SSS products are assimilated. We find that including satellite SSS significantly improves Niño3.4 sea surface temperature anomaly validation, more mature SSS model algorithms are generally improving ENSO forecasts over time, and more satellite SSS data coverage helps to extend useful forecasts.

Ocean↗
NASA NTRS2022

Identifying Chemical Aerosol Signatures Using Optical Suborbital Observations: How Much Can Optical Properties Tell us about Aerosol Composition?

Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models. In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation. We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements. This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).

Meloe S F Kacenelenbogen↗
NASA NTRSDate not supplied

Using PACE Aerosol Optical and Microphysical Properties to Capture Aerosol Composition

Improvements in air quality and Earth’s climate predictions can only be achieved through improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (e.g., clean marine, dust, polluted continental). We investigate the relative skill of various combinations of aerosol optical properties used as tools to define air mass aerosol types and how much these optical properties can capture dominant aerosol speciation.

Meloe Shenandoah Kacenelenbogen↗
NASA NTRS1981

Time variability of Martian bolometric albedo

A time series of calibrated bolometric albedo maps of Mars is presented which establish accurate values of surface bolometric albedo and demonstrate changes in the bolometric appearance of specific regions with time of year and atmospheric conditions. The maps were constructed from Viking infrared thermal mapping data and provide global coverage at latitudes between -60 and +60 deg at 1 x 1 deg spatial resolution for a period spanning a Martian year and including the global dust storms of 1977. During dust-free periods, the bolometric albedo maps are found to be similar to classical earth-based visual albedo maps. A distinctly bimodal distribution of bolometric surface albedos is obtained even during the dust storms, with typical Lambert albedos of 0.27 and 0.16 for the bright and dark Martian surfaces, respectively. Atmospheric effects including dust storms are found to influence strongly apparent surface albedos, especially for dark areas, while neither bright nor dark regions show measurable long-term variations of bolometric albedo during clear periods.

Pleskot, L. K.↗
NASA NTRS2014

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

Blankenship, Clay B.↗
NASA NTRS1999

Radar Reconnaissance of Near-Earth Asteroids

Groundbased radar observations of NEAs can help identify space resources with commercial potential and can dramatically reduce the cost and risk of the initial spacecraft missions to those objects. The near-Earth asteroid (NEA) population is thought to contain approximately 1500 objects as large as a kilometer, approximately 300,000 as large as 100 meters, and more than 100,000,000 as large as 10 meters. More than 10% of the NEAs are more accessible in terms of mission delta-V (i.e., fuel required) than the Moon, Mars, or the moons of Mars. Fewer than 1000 NEAs have been found, but the discovery rate is increasing rapidly. Once an asteroid is discovered (necessarily by wide-field optical telescopes), radar can provide otherwise unavailable information about its size, shape, spin state, and surface properties if it approaches within the range of the Goldstone (California) or Arecibo (Puerto Rico) radar telescopes. Asteroids generally appear as unresolved points through groundbased optical telescopes, but radar measurements of the distribution of echo power in time delay (range) and Doppler frequency (radial velocity) can yield images with resolution as fine as a decameter. Image sequences that furnish adequate orientational coverage can be inverted to construct geologically detailed 3-D models, to define the rotation state precisely, and to constrain the object's internal density distribution. Estimates of radar scattering properties characterize the surface's cm-to-m-scale roughness as well as its bulk density, which for asteroids depends primarily on porosity and metal concentration. A useful spin-off of radar detection is orbit refinement that simplifies navigation of flyby and rendezvous spacecraft.

Ostro, S. J.↗
NASA NTRS1999

Radar Reconnaissance of Near-Earth Asteroids

Groundbased radar observations of NEAs can help identify space resources with commercial potential and can dramatically reduce the cost and risk of the initial spacecraft missions to those objects. The near Earth asteroid (NEA) population is thought to contain approx. 1500 objects as large as a kilometer, approx. 300,000 as large as 100 meters, and more than 100,000,000 as large as 10 meters. More than 10% of the NEAs are more accessible in terms of mission delta-V (i.e., fuel required) than the Moon, Mars, or the moons of Mars. Fewer than 1000 NEAs have been found, but the discovery rate is increasing rapidly. Once an asteroid is discovered (necessarily by wide-field optical telescopes), radar can provide otherwise unavailable information about its size, shape, spin state, and surface properties if it approaches within the range of the Goldstone (California) or Arecibo (Puerto Rico) radar telescopes. Asteroids generally appear as unresolved points through groundbased optical telescopes, but radar measurements of the distribution of echo power in time delay (range) and Doppler frequency (radial velocity) can yield images with resolution as fine as a decameter. Image sequences that furnish adequate orientational coverage can be inverted to construct geologically detailed 3-D models, to define the rotation state precisely, and to constrain the object's internal density distribution. Estimates of radar scattering properties characterize the surface's cm-to-m-scale roughness as well as its bulk density, which for asteroids depends primarily on porosity and metal concentration. A useful spin-off of radar detection is orbit refinement that simplifies navigation of flyby and rendezvous spacecraft.

Ostro, S. J.↗
NASA NTRS1992

Mars observer radio science (MORS) observations in polar regions

MORS observations will focus on two major areas of study: (1) the gravity field of Mars and its interpretation in terms of internal structure and history and (2) the structure of the atmosphere, with emphasis on both temperature-pressure profiles of the background atmosphere and small scale inhomogeneities resulting from turbulence. Scattering of cm wavelength radio signals from Mars' surface at highly oblique angles will also be studied during the primary mission; nongrazing scattering experiments may be possible during an extended mission. During the MORS primary mission, measurements of the spacecraft distance and velocity with respect to Earth based tracking stations will be used to develop models of the global gravity field. The improvement in knowledge of the gravity field will be especially evident in polar regions. The spatial and temporal coverage of atmospheric radio occultation measurements are determined by the geometry of the spacecraft orbit and the direction to the Earth. Profiles of atmospheric temperature and pressure will extend from the surface to altitudes of 50 to 70 km.

Simpson, Richard A.↗
NASA NTRS1990

Spot temperatures and area coverages on active dwarf stars

Two active K dwarfs are examined to determine the temperatures of the stars and to estimate the locations and sizes of cool spots on the stellar surfaces. Two wavelength regions with TiO absorption bands at different temperature sensitivities are modeled simultaneously using the method developed by Huenemoerder and Ramsey (1987). The spectrum of BD +26deg730 shows excess absorption in the TiO band, and the absence of the 8860 A band in HD 82558 indicates that its spots are warmer than those of BD +26deg730.

Sarr, Steven H.↗
NASA NTRSDate not supplied

IMERG Multi-Satellite Products Across Two Decades

The Version 06 Global Precipitation Measurement (GPM) mission products were completed over the last year, capping five years of development since the launch of the GPM Core Observatory, and covering the joint Tropical Rainfall Measuring Mission (TRMM) and GPM eras with consistently processed algorithms. The U.S. GPM team’s Integrated Multi-satellitE Retrievals for GPM (IMERG) merged precipitation product enforces a consistent intercalibration for all precipitation products computed from individual satellites with the TRMM and GPM Core Observatory sensors as the TRMM- and GPM-era calibrators, respectively, and incorporates monthly surface gauge data in the Final (research) product. Mid-latitude calibrations during the TRMM era necessarily are more approximate because TRMM only covered the latitude band 35°N-S, while GPM covers 65°N-S. Starting in V06, IMERG employs precipitation motion vectors (used to drive the quasi-Lagrangian interpolation, or “morphing”) that are computed by tracking the vertically integrated vapor as analyzed in MERRA2 and GEOS FP. This approach covers the entire globe, expanding coverage beyond the 60°N-S latitude band provided by IR-based vectors in previous versions, although we choose to mask out microwave-based precipitation over snowy/icy surfaces as unreliable. We will provide examples of performance for the V06 IMERG products, including comparison with the long-term record of GPCP and TMPA, showing higher values by about 8% in the latitude band 50°N-S over oceans; diurnal cycle, demonstrating improvement over previous versions; and daily precipitation PDFs for the entire record, showing a shift at the TRMM/GPM boundary, as well as interannual variations. These analyses have important implications for the utility of V06 IMERG data for long-record calculations. Finally, we will review the retirement of the predecessor TMPA multi-satellite dataset.

George J. Huffman↗
NASA NTRS2001

Validation of Surface Bio-Optical Properties in the Gulf of Maine as a Means for Improving Satellite Primary Production Estimates

One of the greatest challenges in providing sea-truth data for various ocean color sensors is climatology. This is particularly true in the Gulf of Maine since it is cloudy and foggy more than it is clear; the climatology shows on average, about one in four to five days has clear skies with clear days slightly more frequent in the late summer and early fall. Our strategy has been to use a ship of opportunity where one has choice of the sampling days. This provides much better flexibility to sample during clear periods with good satellite coverage. Our Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) contract has been to use the M/S Scotia Prince ferry as a ship of opportunity, running between Portland, Maine and Yarmouth, NS. Measurements include continuous, surface, along-track fluorescence, two independent measures of backscattering, total light scattering, absorption, beam attenuation, above-water remote sensing reflectance, calcite-dependent light scattering, temperature, and salinity. Expendable bathythermography (XBT) drops allow acquisition of vertical temperature information, useful for defining isopycnal slope, which affects primary production. These data are comparable to a previous program from early 1982, where a ship of opportunity program (SOOP) was run on the truck ferry, M/V Marine Evangeline, which ran along the same transect. These surface data were combined with satellite-derived sea surface temperature fields to examine the Maine coastal current. Unfortunately, this program stopped in 1982. The ongoing SIMBIOS results will dovetail nicely with the previous work (which also had Coastal Zone Color Scanner (CZCS) coverage) for looking at any long-term changes in the Gulf of Maine hydrography, bio-optics, and biogeochemistry.

Balch, William M.↗
NASA NTRSDate not supplied

MISR Level 1B2 Terrain Data (MI1B2T_V1)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The Terrain data are re-projected to the terrain altitude. In this product, surface data from all cameras will appear in the same geographic location. Thus, this product is the primary input to Level 2 aerosol/surface processing, which requires co-registration of the L1B2 imagery at the surface. Clouds will still be displaced due to their elevation above the surface, but this time with respect to the terrain rather than the ellipsoid. (The mountain location T is now assigned the geographic location at T, and the Cloud at F appears at the geographic location T.) In Level 2 aerosol/surface processing, algorithms are applied to screen out the clouds. Terrain data only exist for MISR blocks containing some land. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=563.2 km (cross-track); Longitude_Resolution=140.8 km (along-track).; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

NEAR IR WAVELENGTHS↗
NASA NTRS2010

AXTAR: Mission Design Concept

The Advanced X-ray Timing Array (AXTAR) is a mission concept for X-ray timing of compact objects that combines very large collecting area, broadband spectral coverage, high time resolution, highly flexible scheduling, and an ability to respond promptly to time-critical targets of opportunity. It is optimized for sub-millisecond timing of bright Galactic X-ray sources in order to study phenomena at the natural time scales of neutron star surfaces and black hole event horizons, thus probing the physics of ultra-dense matter, strongly curved spacetimes, and intense magnetic fields. AXTAR s main instrument, the Large Area Timing Array (LATA) is a collimated instrument with 2 50 keV coverage and over 3 square meters effective area. The LATA is made up of an array of super-modules that house 2-mm thick silicon pixel detectors. AXTAR will provide a significant improvement in effective area (a factor of 7 at 4 keV and a factor of 36 at 30 keV) over the RXTE PCA. AXTAR will also carry a sensitive Sky Monitor (SM) that acts as a trigger for pointed observations of X-ray transients in addition to providing high duty cycle monitoring of the X-ray sky. We review the science goals and technical concept for AXTAR and present results from a preliminary mission design study

Ray, Paul S.↗
NASA NTRSDate not supplied

MISR radiometric camera-by-camera Cloud Mask (MIRCCM_V4)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The RCCM is derived from the radiance values, and is calculated independently for each camera. Therefore, the amount of apparent cloudiness will vary with view angle, with the oblique view angles generally being more cloudy than the near-nadir ones. Since the RCCM is calculated primarily from the radiance values, it does not work well over snow and ice and will usually confuse clear snow/ice with cloud. It works the best over clear-sky ocean, but other surface types are also of quite good quality. The RCCM product also contains a glint mask for each camera, and this mask is set to true whenever the scattering angles indicate that glint could be possible. This glint mask is not masked out over land; users must do this step themselves. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

SUN GLINT↗