Search NASA⌕ Search

SEARCH · Search NASA

Results for “SUN GLINT”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2

EPIC Cloud Observations with Oxygen Bands Over Snow, Ice and Sunglint Regions

Cloud detections over snow/ice surfaces and sunglint regions are challenging with passive remote sensing instrument due to lack of contract between cold/bright surfaces in the former and glint reflectance that could exceed that of cloudy sky in the latter. We developed novel cloud detection algorithms for these regions utilizing EPIC’s unique oxygen-bands. Over the snow and ice surfaces, a dynamic threshold scheme based on the ratios of two pairs of EPIC’s oxygen bands are developed to significantly improve the existing algorithm in these regions. Over the ocean, we improved the EPIC’s ocean cloud mask algorithm by implementing a dynamic reflectance threshold and supplemental A-band ratio test for cloud detection in the sun glint regions. The new ocean cloud mask algorithm improves the diurnal cycles of cloud fraction over ocean by reducing the artificial peak at local noon time in the glint center latitudes and reducing early morning and afternoon cloud fraction in most oceanic regions.

EPIC↗

Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel Definition

The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC delivers adequate spatial resolution imagery but only in shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and longwave broadband windows. Accurate calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud properties retrievals from low earth orbit (LEO, including NASA Terra and Aqua MODIS, Suomi-NPP VIIRS, and NOAA AVHRR) and geosynchronous (GEO, including GOES east and west, METEOSAT, INSAT-3D, MTSAT-2, and Himawari-8) satellite imagers. The cloud properties are derived using the Clouds and the Earth's Radiant Energy System (CERES) mission Cloud Subsystem group algorithms. These properties have to be co-located with EPIC pixels to provide the scene identification and to select anisotropic directional models (ADMs), which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiance and cloud property parameters derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. Selection of satellite data for each 5-km pixel is based on an aggregated rating that incorporates five parameters: nominal satellite resolution, pixel time relative to the EPIC time, viewing zenith angle, distance from day/night terminator, and probability of sun glint. To provide a smoother transition in the merged output, in regions where candidate pixel data from two satellite sources have comparable aggregated rating, the selection decision is defined by the cumulative function of the normal distribution so that abrupt changes in the visual appearance of the composite data are avoided. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling.

Khlopenkov, Konstantin V.↗

Use of TEMPO as a Proxy for Hyperspectral Geostationary Ocean Color Measurements from the GeoXO OCX Instrument: Harnessing Machine Learning and Principal Component Techniques for Atmospheric and Glint Correction

Retrievals of ocean color from space are important for better understanding the ocean ecosystem. The launch of atmospheric geostationary hyperspectral sensors such as TEMPO, provides a unique opportunity to examine the diurnal variability in ocean ecology. While TEMPO does not have as high spatial resolution or full spectral coverage as planned coastal ocean sensors such as the Geosynchronous Littoral Imaging and Monitoring Radiometer (GLIMR) or GeoXO Ocean Color instrument (OCX), its hourly measurements provide coverage of regions such as Lake Erie and the Gulf of Mexico at spatial scales of approximately 5 km. These data can be useful for testing new algorithms. We will apply our newly developed machine learning based atmospheric correction approach for ocean color retrievals to TEMPO data. Our approach begins by decomposing measured radiances from hyperspectral sensors into spectral features that describe the scattering and absorption of the atmosphere as well as the underlying surface reflectance. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from collocated MODIS/VIIRS physically-based retrievals. This machine learning approach does not rely on radiative transfer modeling, and the use of MODIS/VIIRS data for training accounts for possible calibration b in hyperspectral data. Previously, we applied our approach using blue and UV wavelengths with the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can estimate ocean color properties in less-than-ideal conditions such as lightly to moderately clouded conditions as well as sun glint and thus improve the spatial coverage of ocean color measurements. TEMPO provides an opportunity to improve on this approach since it will provide collocated measurements at green and red wavelengths that were not available from OMI and TROPOMI and are important particularly for coastal waters. Additionally, our technique can be applied early in the mission and has potential to demonstrate the value of near real time ocean color products that are important for monitoring of harmful algae blooms and other oceanic phenomena.

Zachary Fasnacht↗

Atmospheric modeling related to Thematic Mapper scan geometry

A simulation study was carried out to characterize atmospheric effects in LANDSAT-D Thematic Mapper data. In particular, the objective was to determine if any differences would result from using a linear vs. a conical scanning geometry. Insight also was gained about the overall effect of the atmosphere on Thematic Mapper signals, together with the effects of time of day. An added analysis was made of the geometric potential for direct specular reflections (sun glint). The ERIM multispectral system simulation model was used to compute inband Thematic Mapper radiances, taking into account sensor, atmospheric, and surface characteristics. Separate analyses were carried out for the thermal band and seven bands defined in the reflective spectral region. Reflective-region radiances were computed for 40 deg N, 0 deg, and 40 deg S latitudes; June, Mar., and Dec. days; and 9:30 and 11:00 AM solar times for both linear and conical scan modes. Also, accurate simulations of solar and viewing geometries throughout Thematic Mapper orbits were made. It is shown that the atmosphere plays an important role in determining Thematic Mapper radiances, with atmospheric path radiance being the major component of total radiances for short wavelengths and decreasing in importance as wavelength increases. Path radiance is shown to depend heavily on the direct radiation scattering angle and on haze content. Scan-angle-dependent variations were shown to be substantial, especially for the short-wavelength bands.

Malila, W. A.↗

The determination of surface albedo from meteorological satellites

A surface albedo was determined from visible data collected by the NOAA-4 polar orbiting meteorological satellite. To filter out the major cause of atmospheric reflectivity, namely clouds, techniques were developed and applied to the data resulting in a map of global surface albedo. Neglecting spurious surface albedos for regions with persistent cloud cover, sun glint effects, insufficient reflected light and, at this time, some unresolved influences, the surface albedos retrieved from satellite data closely matched those of a global surface albedo map produced from surface and aircraft measurements and from characteristic albedos for land type and land use.

Johnson, W. T.↗

The CZCS geolocation algorithms

The Coastal Zone Color Scanner (CZCS) on board the Nimbus 7 satellite was designed to measure surface radiance upwelled from the ocean in 6 spectral bands. The CZCS spectrometer obtains its information from a rotating mirror and is timed to collect data when the mirror views the Earth surface between ca. 40 degrees to the left and right of the subsatellite track. Each scan is divided into 1968 picture elements, pixels, of 0.04 degrees scan each. In order to avoid direct reflected Sun glint, the rotating mirror shaft can be tilted so that scans across the subsatellite track up to 20 degrees forward or aft of the point directed beneath the satellite. The CZCS is the first satellite borne instrument to have this tilted scan capability and therefore poses some new problems in locating the Earth surface position of viewed pixels.

Wilson, W. H.↗

Intercomparison of wind speeds inferred by the SASS, altimeter, and SMMR

The operational theory, control algorithms, and comparisons with surface-determined wind speeds for the scatterometer (SASS), altimeter (ALT), and passive microwave radiometer (SMMR) on board the Seasat satellite are presented. Radiative scattering combining specular reflections and Bragg resonance scattering are noted to occur at tilting waves and sea foam, two conditions highly correlated with wind speed. SASS scans swaths of 70, 200, and 700 km from nadir, the SMMR covers a 150 km strip. Normalized radar sections are derived from the SASS and ALT telemetry, and brightness temperature from the SMMR. ALT winds were found to be biased about 3 m/sec low, while intercomparison between the SMMR and SASS data showed a mean difference of 0.3 m/sec with a standard deviation from measured winds of 1.7 m/sec or less. The effects of land thermal emissions, rain, and sun glint are discussed, and good viewing conditions are concluded to result in 2 m/sec accuracy.

Wentz, F. J.↗

Description of Seasat radiometer status and results

Improved geophysical algorithms are shown to be able to determine sea surface temperature (SST) to an accuracy of 1 C (1 sigma) under favorable surface and atmospheric conditions over an SST range of 10-30 C. Under similar conditions, the radiometer wind retrievals track the scatterometer winds within a scatter of 2 m/s (1 sigma) over a wind speed range of 0-25 m/s. These conditions require that contamination from land, rain, sun glint, and radio frequency interference be avoided. What is more, water vapor determinations in the midlatitudes and in the tropical Pacific are found to agree with estimates of precipitable water from radiosondes to within 10%.

Lipes, R. G.↗

The view from the Shuttle Orbiter - Observing the oceans from manned space flights

Examples of earth-looking hand-held photography and orbital sensor imagery of ocean features and phenomena in the framework of the Space Shuttle Earth Observations Project are presented. These include images of a floating substance in Capricorn Channel off northeastern Queensland, Australia; atolls in the central Maldive Islands; a spiral eddy and probable oil slick in the Caribbean Sea north of Aruba; and spiral eddies recorded in sun glint over the Mozambique Channel. It is concluded that the observation of the world's oceans during Shuttle missions with the trained eyes of the crewmen and documentation with hand-held photography add a significant dimension to the remote sensing of the ocean.

Kaltenbach, J. L.↗

Earth observing scanning polarimeter

Climate forcing by tropospheric aerosols is receiving increased attention because of the realization that the climate effects may be large, while our knowledge of global aerosol characteristics and temporal changes is very poor. Tropospheric aerosols cause a direct radiative forcing due simply to their scattering and absorption of solar radiation, as well as an indirect effect as cloud condensation nuclei which can modify the shortwave reflectivity of clouds. Sulfate aerosols tend to increase planetary albedo through both the direct and indirect effects; a cooling due to anthropogenic sulfate aerosols has been estimated of order 1 W/sq m, noting that this is similar in magnitude to the present anthropogenic greenhouse gas warming. Other aerosols, including those from biomass burning and wind-blown desert dust are also of potential climatic importance. At present, the only global monitoring of tropospheric aerosols is a NOAA operational product, aerosol optical thickness, obtained using channel-1 (0.58-0.68 mu m) radiances from the AVHRR. With this single channel radiance data, one must use an approach which is based on the inferred excess of reflected radiance owing to scattering by the aerosols over that expected from theoretical calculations. This approach is suited only for situations where the surface has a low albedo that is well known a priori. Thus, the NOAA operational product is restricted to coverage over the ocean at AVHRR scan angles well away from sun glint, and aerosol changes are subject to confusion with changes caused by either optically thin or subpixel clouds. Because optically thin aerosols have only a small effect on the radiance, accurate measurements for optical thickness less than 0.1 (which is a typical background level) are precluded. Moreover, some of the largest and most important aerosol changes are expected over land. The Earth Observing Scanning Polarimeter (EOSP) instrument, based upon design heritage and analysis techniques developed for planetary missions, will retrieve tropospheric aerosol characteristics from measurements of multispectral radiance and polarization. Moreover, the same radiance and polarization measurements will also provide very precise information on cloud properties and maps of surface characteristics for cloud-free regions. These capabilities also give EOSP the unique ability to discriminate aerosol from clouds and surface.

Travis, Larry↗

SeaWiFS technical report series. Volume 13: Case studies for SeaWiFS calibration and validation, part 1

Although the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Calibration and Validation Program relies on the scientific community for the collection of bio-optical and atmospheric correction data as well as for algorithm development, it does have the responsibility for evaluating and comparing the algorithms and for ensuring that the algorithms are properly implemented within the SeaWiFS Data Processing System. This report consists of a series of sensitivity and algorithm (bio-optical, atmospheric correction, and quality control) studies based on Coastal Zone Color Scanner (CZCS) and historical ancillary data undertaken to assist in the development of SeaWiFS specific applications needed for the proper execution of that responsibility. The topics presented are as follows: (1) CZCS bio-optical algorithm comparison, (2) SeaWiFS ozone data analysis study, (3) SeaWiFS pressure and oxygen absorption study, (4) pixel-by-pixel pressure and ozone correction study for ocean color imagery, (5) CZCS overlapping scenes study, (6) a comparison of CZCS and in situ pigment concentrations in the Southern Ocean, (7) the generation of ancillary data climatologies, (8) CZCS sensor ringing mask comparison, and (9) sun glint flag sensitivity study.

Hooker, Stanford B.↗

Validation of ISCCP cloud detections

This paper describes the validation of the International Satellite Cloud Climatology project (ISCCP)cloud detections by verifying the accuracy of the infrared clear-sky radiances. Comparison of retrieved surface temperatures to other measurements shows that bias errors are less than 2 K and random errors are about 2 K for sea surface (monthly means at 280-km scales) and that bias errors are less than 2 K and random errors are about 4 K for land surfaces (3 hourly at 280-km scales). Bias errors over a few persistently cloudy locations are sometimes -(2-4) K and over winter sea ice may be about +2 K. Surface reflectances are confirmed to be within 3% of other measurements and models for ocean, except for sun glint geometries, and to be within 3%-5% for land surfaces. Sufficiently accurate validation data are not avilable for visible reflectances of sea ice and snow-covered land, but some tests of specific cases suggest that errors are approximately 10%. These errors in clear-sky radiances suggest uncertainties in the ISCCP cloud detections of about 10% with a small (3%-6%) negative bias over land. Some specific regions exhibit both larger rms uncertainties and somewhat larger biases in cloud amount approaching 10%. ISCCP cloud detections are more in error over the polar regions than anywhere else. Based on comparisons with an anlysis of radiances measured at other wavelengths, the ISCCP analysis appears to miss 15%-25% of the clouds in summer but only 5%-10% of the winter clouds.

Rossow, William B.↗

Flight data from the PASP-Plus experiment

The photovoltaic array space power (PASP)-Plus solar cell flight experiment is described, and the observed performances of different solar cell types during the first six months of their operation, are summarized. The solar cell types include single crystal and amorphous silicon, GaAs, several multijunction cell types, indium phosphide and GaAs/GaSb concentrator cells. The radiation degradation experienced by some of the solar cell types agrees with theoretical predictions. Other samples, including silicon, are degraded less than predicted. Effects, including the increase in temperature of all the experiments and the effect of sun glint on cell measurement, are discussed.

Marvin, D. C.↗

The EOS CERES Global Cloud Mask

To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global cloud climatology data sets, such as the International Satellite Cloud Climatology Experiment (ISCCP) or CLAVR (Clouds from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a cloud 'mask.' A cloud mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The cloud imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a cloud masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting cloud using multispectral narrowband radiance data. Clouds generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the cloud types, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The cloud mask effort builds upon operational experience of several groups that will now be discussed.

Berendes, T. A.↗

An Assessment of SeaWiFS and MODIS Ocean Coverage

Ocean coverages of SeaWiFS and MODIS were assessed for three seasons by considering monthly mean values of surface winds speeds and cloud cover. Mean and maximum coverages combined SeaWiFS and MODIS by considering combined coverages for ten-degree increments of the MODIS orbital mean anomaly. From this analysis the mean and maximum combined coverages for SeaWiFS and MODIS were determined for one and four-day periods for spring, summer, and winter seasons. Loss of coverage due to Sun glint and cloud cover were identified for both the individual and combined cases. Our analyses indicate that MODIS will enhance ocean coverage for all three seasons examined. ne combined SeaWiFS/MODIS show an increase of coverage of 42.2% to 48.7% over SeaWiFS alone for the three seasons studied; the increase in maximum one day coverage ranges from 47.5% to 52.0%. The increase in four-day coverage for the combined case ranged from 31.0% to 35.8% for mean coverage and 33.1 % to 39.2% for maximum coverage. We computed meridional distributions of coverages by binning the data into five-degree latitude bands. Our analysis shows a strong seasonal dependence of coverage. In general the meridional analysis indicates that increase in coverages for SeaWiFS/MODIS over SeaWiFS alone are greatest near the solar declination.

Woodward, Robert H.↗

On-Orbit Calibration of ADEOS OCTS with an AVIRIS Underflight

The Ocean Color Temperature Scanner (OCTS) onboard the Advanced Earth Observation Satellite (ADEOS) was launched on August 17, 1996. Calibration of OCTS is required for use of the on-orbit measured data for retrieval of physical properties of the ocean. In the solar reflected portion of the electromagnetic spectrum, OCTS measures images with nominally 700-m spatial resolution through eight multispectral bands. The objective of this research was to establish the absolute radiometric calibration of OCTS on orbit through an underflight by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS is a NASA earth-observing imaging spectrometer designed, built and operated by the Jet Propulsion Laboratory (JPL). AVIRIS acquires data from 20-km altitude on a NASA ER-2 aircraft, above most of the Earth's atmosphere. AVIRIS measures the solar reflected spectrum from 370 nm to 2500 nm through 224 contiguous spectral channels. The full width at half maximum (FWHM) of the spectral channels is nominally 10-nm. AVIRIS spectra are acquired as images of 11 km by up to 800 km extent with 20-m spatial resolution. The high spectral resolution of AVIRIS data allows direct convolution to the spectral response functions of the eight multispectral bands of OCTS. The high spatial resolution of AVIRIS data allows for spatial re-sampling of the data to match the ADEOS sensors spatial resolution. In addition, the AVIRIS high spatial resolution allows assessment of the scaling effects due to environmental factors of thin cirrus clouds, sub-pixel cloud cover, white caps, ocean foam, sun-glint, and bright-target adjacency. The platform navigation information recorded by AVIRIS allows calculation of the position and observation geometry of each spectrum for matching to the OCTS measurement. AVIRIS is rigorously characterized and calibrated in the laboratory prior to and following the flight season. The stability and repeatability of AVIRIS calibration have been validated through an extensive series of inflight calibration experiments. In the OCTS portion of the spectrum, using pre-and post-flight runway calibrations of AVIRIS coupled with the on-board calibrator an absolute calibration accuracy of better than 3% spectral, 2% radiometric and 5% spatial has been achieved. An analogous satellite underflight calibration experiment was performed with AVIRIS and the Optical Sensor (OPS) onboard the Japanese Earth Resources Satellite (JERS).

Green, Robert O.↗

On-Orbit Calibration of ADEOS OCTS with an AVIRIS Underflight

The Ocean Color Temperature Scanner (OCTS) onboard the Advanced Earth Observation Satellite (ADEOS) was launched on August 17, 1996. Calibration of OCTS is required for use of the on-orbit measured data for retrieval of physical properties of the ocean. In the solar reflected portion of the electromagnetic spectrum, OCTS measures images with nominally 700-m spatial resolution through eight multispectral bands. The objective of this research was to establish the absolute radiometric calibration of OCTS on orbit through an underflight by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS is a NASA Earth-observing imaging spectrometer designed, built and operated by the Jet Propulsion Laboratory (JPL). AVIRIS acquires data from 20-km altitude on a NASA ER-2 aircraft, above most of the Earth's atmosphere. AVIRIS measures the solar reflected spectrum from 370 nm to 2500 nm through 224 contiguous spectral channels. The full width at half maximum (FWHM) of the spectral channels is nominally 10-nm. AVIRIS spectra are acquired as images of 11 km by up to 800 km extent with 20-m spatial resolution. The high spectral resolution of AVIRIS data allows direct convolution to the spectral response functions of the eight multispectral bands of OCTS. The high spatial resolution of AVIRIS data allows for spatial re-sampling of the data to match the ADEOS sensors spatial resolution. In addition, the AVIRIS high spatial resolution allows assessment of the scaling effects due to environmental factors of thin cirrus clouds, sub-pixel cloud cover, white caps, ocean foam, sun-glint, and bright-target adjacency. The platform navigation information recorded by AVIRIS allows calculation of the position and observation geometry of each spectrum for matching to the OCTS measurement. AVIRIS is rigorously characterized and calibrated in the laboratory prior to and following the flight season. The stability and repeatability of AVIRIS calibration have been validated through an extensive series of inflight calibration experiments. In the OCTS portion of the spectrum, using pre- and post-flight runway calibrations of AVIRIS coupled with the on-board calibrator an absolute calibration accuracy of better than 3% spectral, 2% radiometric, and 5% spatial, has been achieved. An analogous satellite underflight calibration experiment was performed with AVIRIS and the Optical Sensor (OPS) onboard the Japanese Earth Resources Satellite (JERS).

Green, Robert O.↗

Merging Ocean Color Data from Multiple Missions

Oceanic phytoplankton may play an important role in the cycling of carbon on the Earth, through the uptake of carbon dioxide in the process of photosynthesis. Although they are ubiquitous in the global oceans, their abundances and dynamics are difficult to estimate, primarily due to the vast spatial extent of the oceans and the short time scales over which their abundances can change. Consequently, the effects of oceanic phytoplankton on biogeochemical cycling, climate change, and fisheries are not well known. In response to the potential importance of phytoplankton in the global carbon cycle and the lack of comprehensive data, the National Aeronautics and Space Administration (NASA) and the international community have established high priority satellite missions designed to acquire and produce high quality ocean color data. Seven of the missions are routine global observational missions: the Ocean Color and Temperature Sensor (OCTS), the Polarization and Directionality of the Earth's Reflectances sensor (POLDER), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectrometer-AM (MODIS-AM), Medium Resolution Imaging Spectrometer (MERIS), Global Imager (GLI), and MODIS-PM. In addition, there are several other missions capable of providing ocean color data on smaller scales. Most of these missions contain the spectral band complement considered necessary to derive oceanic pigment concentrations (i.e., phytoplankton abundance) and other related parameters. Many contain additional bands that can provide important ancillary information about the optical and biological state of the oceans. Any individual ocean color mission is limited in ocean coverage due to sun glint and clouds. For example, one of the first proposed missions, the SeaWiFS, can provide about 45% coverage of the global ocean in four days and only about 15% in one day.

Gregg, Watson W.↗