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NASA NTRSDate not supplied

Utilizing Libya-4 to Intercalibrate Overlapping Sensors in the Same Sun-Synchronous Orbit

The NASA CERES observed SW and LW broadband fluxes are utilized by the climate community for monitoring the Earth’s energy imbalance and for climate model validation. The SNPP and NOAA20 CERES instruments and associated VIIRS imagers were launched into the same 1:30 PM mean local time sun-sun-synchronous orbits as well as the future NOAA22 Libera broadband instrument and VIIRS imager. The overlapping sensor records need to be intercalibrated to enable consistent broadband fluxes and imager cloud retrievals. The overlapping satellites are typically placed a half an orbit apart, thus preventing any simultaneous nadir overpass (SNO) events required for time-matched inter-calibration strategies. A Pseudo Invariant Calibration Site (PICS), such as Libya-4, can provide overlapping sensor radiometric scaling factors without the use of SNOs. The clear-sky Libya-4 observed radiances were characterized both spectrally and angularly and corrected for atmospheric effects. The Libya-4 natural variability was found to be consistent across the CERES and VIIRS records. This fact reveals that the sensor onboard calibration anomalies are smaller than the Libya-4 natural variability. By mitigating the Libya-4 natural variability will reduce the radiometric scaling factor uncertainty needed to provide both broadband flux and cloud retrieval continuity across the overlapping sensor records.

D R Doelling↗
NASA NTRS1990

Interpretation of satellite-measured bidirectional reflectance from Cirrus cloudy atmospheres

The interpretation of the observed bidirectional reflectance from cirrus cloudy atmospheres is presented. A theoretical model was developed for the computation of the transfer of solar radiation in an anisotropic medium with particular applications to oriented ice crystals in cirrus clouds. In this model, the adding principle for radiative transfer was used with modifications to account for the anisotropy of scattering particles and the associated scattering phase matrix. The single-scattering properties, including the phase function, single-scattering albedo, and extinction cross sections, were used for randomly and horizontally oriented hexagonal ice crystals in radiative transfer computations. The radiative transfer model developed for the cirrus clouds was modified to account for the scattering contributions from the atmosphere and the surface. In order to test the relevance and significance of the ice crystal model for the interpretation of observed bidirectional reflectance from satellites, visible radiances collected on the half hour by the GOES series were selected. The data are calibrated and corrected with the proper filter functions, then navigated to match selected landmark data. A number of clear and cloudy cases during the cirrus IFO of the Fire experiment were chosen for theoretical analyses. The cloud particle shape and size distributions that were taken during satellite overpasses are used in radiative transfer calculations. The sensitivities of the shape, orientation, and size distribution of ice crystals on the reflected intensities at the top of the atmosphere are investigated. Finally, the relative importance of these cloud microphysical properties in the interpretation of satellite bidirectional reflectance are assessed and presented.

Takano, Y.↗
NASA NTRS2014

Assessment of Satellite Ocean Colour Radiometry and Derived Geophysical Products

Standardization of methods to assess and assign quality metrics to satellite ocean color radiometry and derived geophysical products has become paramount with the inclusion of the marine reflectance and chlorophyll-a concentration (Chla) as essential climate variables (ECV; [1]) and the recognition that optical remote sensing of the oceans can only contribute to climate research if and when a continuous succession of satellite missions can be shown to collectively provide a consistent, long-term record with known uncertainties. In 20 years, the community has made significant advancements toward that objective, but providing a complete uncertainty budget for all products and for all conditions remains a daunting task. In the retrieval of marine water-leaving radiance from observed top-of-atmosphere radiance, the sources of uncertainties include those associated with propagation of sensor noise and radiometric calibration and characterization errors, as well as a multitude of uncertainties associated with the modeling and removal of effects from the atmosphere and sea surface. This chapter describes some common approaches used to assess quality and consistency of ocean color satellite products and reviews the current status of uncertainty quantification in the field. Its focus is on the primary ocean color product, the spectrum of marine reflectance Rrs, but uncertainties in some derived products such as the Chla or inherent optical properties (IOPs) will also be considered.

Ocean↗
NASA NTRS2016

The Characterization of a DIRSIG Simulation Environment to Support the Inter-Calibration of Spaceborne Sensors

Climate change studies require long-term, continuous records that extend beyond the lifetime, and the temporal resolution, of a single remote sensing satellite sensor. The inter-calibration of spaceborne sensors is therefore desired to provide spatially, spectrally, and temporally homogeneous datasets. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) tool is a first principle-based synthetic image generation model that has the potential to characterize the parameters that impact the accuracy of the inter-calibration of spaceborne sensors. To demonstrate the potential utility of the model, we compare the radiance observed in real image data to the radiance observed in simulated image from DIRSIG. In the present work, a synthetic landscape of the Algodones Sand Dunes System is created. The terrain is facetized using a 2-meter digital elevation model generated from NASA Goddard's LiDAR, Hyperspectral, and Thermal (G-LiHT) imager. The material spectra are assigned using hyperspectral measurements of sand collected from the Algodones Sand Dunes System. Lastly, the bidirectional reflectance distribution function (BRDF) properties are assigned to the modeled terrain using the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product in conjunction with DIRSIG's Ross-Li capability. The results of this work indicate that DIRSIG is in good agreement with real image data. The potential sources of residual error are identified and the possibilities for future work are discussed..

Ambeau, Brittany L.↗
NASA NTRS2006

Coloration Determination of Spectral Darkening Occurring on a Broadband Earth Observing Radiometer: Application to Clouds and the Earth's Radiant Energy System (CERES)

It is estimated that in order to best detect real changes in the Earth s climate system, space based instrumentation measuring the Earth Radiation Budget (ERB) must remain calibrated with a stability of 0.3% per decade. Such stability is beyond the specified accuracy of existing ERB programs such as the Clouds and the Earth s Radiant Energy System (CERES, using three broadband radiometric scanning channels: the shortwave 0.3 - 5microns, total 0.3. > 100microns, and window 8 - 12microns). It has been shown that when in low earth orbit, optical response to blue/UV radiance can be reduced significantly due to UV hardened contaminants deposited on the surface of the optics. Since typical onboard calibration lamps do not emit sufficient energy in the blue/UV region, this darkening is not directly measurable using standard internal calibration techniques. This paper describes a study using a model of contaminant deposition and darkening, in conjunction with in-flight vicarious calibration techniques, to derive the spectral shape of darkening to which a broadband instrument is subjected. Ultimately the model uses the reflectivity of Deep Convective Clouds as a stability metric. The results of the model when applied to the CERES instruments on board the EOS Terra satellite are shown. Given comprehensive validation of the model, these results will allow the CERES spectral responses to be updated accordingly prior to any forthcoming data release in an attempt to reach the optimum stability target that the climate community requires.

Matthews, Grant↗
NASA NTRS2020

SNPP and N20 VIIRS Solar Vector Orientation Knowledge Error Detected by SDSM Sun Views

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a passive scanning Earth observing satellite radiometer. The VIIRS has 22 spectral bands with design center wavelengths from 0.41 to 12.01 μm, providing data to generate more than 20 Earth’s biogeophysical parameters. Fourteen of the 22 VIIRS bands are the reflective solar bands (RSBs), detecting Earth reflected sunlight. To ensure data quality, regular on-orbit radiometric calibrations of the RSBs are performed, mainly through observations of an onboard solar diffuser (SD). The spectral radiance provided by the sunlit SD depends on the SD screen transmittance which is a function of the solar vector orientation. Additionally, on orbit the SD’s bidirectional reflectance distribution function (BRDF) changes its value due to solar bombardment. The BRDF change is derived from the SD stability monitor (SDSM) measurements. The SDSM views the Sun through a screen with through holes (the SDSM screen) and the SD at almost the same time. The time series of the ratio of the signal strengths is a measure of the SD BRDF on-orbit change. Hence the measurements of the on-orbit SD BRDF change depends on the SDSM screen relative transmittance which is also solar vector orientation dependent. In this paper for both the SNPP and the NOAA-20 VIIRS instruments we examine the solar vector orientation knowledge error through matching the SDSM screen relative effective transmittances derived from the calibration data collected on the yaw maneuver and the regular orbits.

SNPP↗
NASA NTRS2000

SeaWiFS Postlaunch Calibration and Validation Analyses

The effort to resolve data quality issues and improve on the initial data evaluation methodologies of the SeaWiFS Project was an extensive one. These evaluations have resulted, to date, in three major reprocessings of the entire data set where each reprocessing addressed the data quality issues that could be identified up to the time of the reprocessing. Three volumes of the SeaWiFS Postlaunch Technical Report Series (Volumes 9, 10, and 11) are needed to document the improvements implemented since launch. Volume 10 continues the sequential presentation of postlaunch data analysis and algorithm descriptions begun in Volume 9. Chapter 1 of Volume 10 describes an absorbing aerosol index, similar to that produced by the Total Ozone Mapping Spectrometer (TOMS) Project, which is used to flag pixels contaminated by absorbing aerosols, such as, dust and smoke. Chapter 2 discusses the algorithm being used to remove SeaWiFS out-of-band radiance from the water-leaving radiances. Chapter 3 provides an itemization of all significant changes in the processing algorithms for each of the first three reprocessings. Chapter 4 shows the time series of global clear water and deep-water (depths greater than 1,000m) bio-optical and atmospheric properties (normalized water-leaving radiances, chlorophyll, atmospheric optical depth, etc.) based on the eight-day composites as a check on the sensor calibration stability. Chapter 5 examines the variation in the derived products with scan angle using high resolution data around Hawaii to test for residual scan modulation effects and atmospheric correction biases. Chapter 6 provides a methodology for evaluating the atmospheric correction algorithm and atmospheric derived products using ground-based observations. Similarly, Chapter 7 presents match-up comparisons of coincident satellite and in situ data to determine the accuracy of the water-leaving radiances, chlorophyll a, and K(490) products.

Hooker, Stanford B.↗
NASA NTRS2020

Performance of NOAA-20 VIIRS Solar Diffuser and Solar Diffuser Stability Monitor

Visible Infrared Imaging Radiometer Suite (VIIRS) radiometrically calibrates its reflective solar bands (RSBs) primarily through a sunlit onboard solar diffuser (SD). The sunlit SD provides a known radiance under the condition that the absolute product of the SD screen transmittance and the bidirectional reflectance distribution function (BRDF) along the SD-to-telescope direction is accurately known. The BRDF changes due to solar exposure. The change, referred to as the H-factor, is monitored by the onboard SD stability monitor (SDSM). The accuracy of the retrieved H-factor propagates to the retrieved F-factor which corrects the scene spectral radiance. High accuracy of the retrieved H-factor relies on high accuracies in the SDSM screen relative effective transmittance and the relative product of the SD screen effective transmittance and the BRDF at the mission start, and a high SDSM detector signal-to-noise ratio (SNR). This article briefly reviews the algorithms used for the NOAA-20 (N20) VIIRS RSB on-orbit radiometric calibration. Additionally, we show the performance of the N20 VIIRS SDSM, giving the SDSM detector SNRs and the SDSM detector gain temporal changes. We develop a model for the SNRs. The model shows that the decreased SNRs in time are due to the detector gain decreases. We also show the N20 VIIRS SD on-orbit performance, measured by the retrieved H-factor and the estimated standard deviation of its error. The H-factor for the telescope view is obtained from the H-factor for the SDSM view, multiplied by an H-factor angular dependence term. We use an innovative method to determine the angular dependence, using the dependence obtained for the Suomi National Polar-orbiting Partnership (SNPP) VIIRS.

VIIRS↗
NASA NTRS1993

AVIRIS calibration using the cloud-shadow method

More than 90 percent of the signal at an ocean-viewing, satellite sensor is due to the atmosphere, so a 5 percent sensor-calibration error viewing a target that contributes but 10 percent of the signal received at the sensor may result in a target-reflectance error of more than 50 percent. Since prelaunch calibration accuracies of 5 percent are typical of space-sensor requirements, recalibration of the sensor using ground-base methods is required for low-signal target. Known target reflectance or water-leaving radiance spectra and atmospheric correction parameters are required. In this article we describe an atmospheric-correction method that uses cloud shadowed pixels in combination with pixels in a neighborhood region of similar optical properties to remove atmospheric effects from ocean scenes. These neighboring pixels can then be used as known reflectance targets for validation of the sensor calibration and atmospheric correction. The method uses the difference between water-leaving radiance values for these two regions. This allows nearly identical optical contributions to the two signals (e.g., path radiance and Fresnel-reflected skylight) to be removed, leaving mostly solar photons backscattered from beneath the sea to dominate the residual signal. Normalization by incident solar irradiance reaching the sea surface provides the remote-sensing reflectance of the ocean at the location of the neighbor region.

Carder, K. L.↗
NASA NTRSDate not supplied

Evaluation of Spectral Band Adjustment Factors for Cross-Calibration of Visible Imagers

The NASA CERES EBAF dataset provides TOA SW and LW fluxes for long-term monitoring of the Earth’s energy balance and to validate climate models. The EBAF products, based on the Terra, Aqua, and NOAA20 CERES instrument observed radiances, rely on coincident measurements from the onboard MODIS or VIIRS imagers to determine cloud properties used for angular distribution model scene selection, which is required to convert the CERES observed radiances into flux values. Furthermore, CERES utilizes geostationary imager (GEO) hourly fluxes and clouds to infer the regional averaged daily flux in the SYN1deg product. A seamless transition of fluxes and clouds can only occur if the analogous MODIS, VIIRS, and GEO channels are properly inter-calibrated. The analogous band SRFs differ noticeably and require scene dependent spectral band adjustment factors (SBAF) for proper radiometric scaling between them. Given their disparate but overlapping SRFs, the coincident VIIRS I1 and M5 band TOA reflectance measurements provide the optimal opportunity to validate SBAFs over many surface and cloud conditions. The CERES project maintains SCIAMACHY, GOME-2, and Hyperion scene-stratified hyper-spectral reflectance measurements that can be convolved with sensor pair SRFs to compute the corresponding SBAF. This study highlights the SCIAMACHY, GOME-2, and Hyperion based SBAFs for different MODIS, VIIRS, and GEO inter-calibration targets, including all-sky tropical ocean (ATO), Libya-4, Dome-C, and deep convective clouds. To mitigate the observed sensor radiance fluctuations due to atmospheric absorption and aerosol variations, the Earth target observed radiances are correlated with multiple atmospheric parameters, such as precipitable water and ozone. The remaining M5 and I1 mean spectral band radiance difference should be resolved by the SBAF correction. The formulation of hyper-spectral sensor based SBAFs and validation methods can be verified in future utilizing high-accuracy, SI-traceable hyper-spectral measurements from CLARREO Pathfinder.

David R Doelling↗
NASA NTRS2021

On-Orbit Calibration and Performance of NOAA-20 VIIRS Reflective Solar Bands

The NOAA-20 (N20) satellite was launched on November 18, 2017 carrying the second Visible Infrared Imaging Radiometer Suite (VIIRS) instrument. Immediately following the launch, the VIIRS passed a series of intensive calibration and validation tests, after which regular calibration and operation activities have continued successfully for more than three years. The production of NASA Collection 2 Level 1B (C2 L1B) for N20 VIIRS began in summer 2019. In this article, we evaluate the early mission performance of the N20 VIIRS reflective solar bands (RSB) covering the first three full years of operation. The calibrated RSB gains are calculated primarily from the onboard solar diffuser (SD) and used in generating the C2 L1B reflectance and radiance products. We also show the on-orbit performance of the instrument noise, signal-to-noise ratio (SNR), and a reflectance uncertainty assessment. Comparisons are made to the first three years of operation of the first VIIRS instrument, aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. We evaluate the long-term stability of the calibrated N20 RSB reflectance product by looking at the long-term trends of lunar observations and data from the pseudo-invariant Libya 4 desert site. The N20 RSB have had excellent early mission performance, with changes in the gain of less than 0.5% in the first three years across all detectors, stable L1B reflectance, and very stable values of detector SNR and reflectance uncertainty.

calibration↗
NASA NTRS2003

GOME Total Ozone and Calibration Error Derived Usign Version 8 TOMS Algorithm

The Global Ozone Monitoring Experiment (GOME) is a hyper-spectral satellite instrument measuring the ultraviolet backscatter at relatively high spectral resolution. GOME radiances have been slit averaged to emulate measurements of the Total Ozone Mapping Spectrometer (TOMS) made at discrete wavelengths and processed using the new TOMS Version 8 Ozone Algorithm. Compared to Differential Optical Absorption Spectroscopy (DOAS) techniques based on local structure in the Huggins Bands, the TOMS uses differential absorption between a pair of wavelengths including the local stiucture as well as the background continuum. This makes the TOMS Algorithm more sensitive to ozone, but it also makes the algorithm more sensitive to instrument calibration errors. While calibration adjustments are not needed for the fitting techniques like the DOAS employed in GOME algorithms, some adjustment is necessary when applying the TOMS Algorithm to GOME. Using spectral discrimination at near ultraviolet wavelength channels unabsorbed by ozone, the GOME wavelength dependent calibration drift is estimated and then checked using pair justification. In addition, the day one calibration offset is estimated based on the residuals of the Version 8 TOMS Algorithm. The estimated drift in the 2b detector of GOME is small through the first four years and then increases rapidly to +5% in normalized radiance at 331 nm relative to 385 nm by mid 2000. The lb detector appears to be quite well behaved throughout this time period.

Gleason, J.↗
NASA NTRS2010

Future Flight Opportunities and Calibration Protocols for CERES: Continuation of Observations in Support of the Long-Term Earth Radiation Budget Climate Data Record

The goal of the Clouds and the Earth s Radiant Energy System (CERES) project is to provide a long-term record of radiation budget at the top-of-atmosphere (TOA), within the atmosphere, and at the surface with consistent cloud and aerosol properties at climate accuracy. CERES consists of an integrated instrument-algorithm validation science team that provides development of higher-level products (Levels 1-3) and investigations. It involves a high level of data fusion, merging inputs from 25 unique input data sources to produce 18 CERES data products. Over 90% of the CERES data product volume involves two or more instruments. Continuation of the Earth Radiation Budget (ERB) Climate Data Record (CDR) has been identified as critical in the 2007 NRC Decadal Survey, the Global Climate Observing System WCRP report, and in an assessment titled Impacts of NPOESS Nunn-McCurdy Certification on Joint NASA-NOAA Climate Goals . Five CERES instruments have flown on three different spacecraft: TRMM, EOS-Terra and EOS-Aqua. In response, NASA, NOAA and NPOESS have agreed to fly the existing CERES Flight Model (FM-5) on the NPP spacecraft in 2011 and to procure an additional CERES Sensor with modest upgrades for flight on the JPSS C1 spacecraft in 2014, followed by a CERES follow-on sensor for flight in 2018. CERES is a scanning broadband radiometer that measures filtered radiance in the SW (0.3-5 m), total (TOT) (0.3-200 m) and WN (8-12 m) regions. Pre-launch calibration is performed on each Flight Model to meet accuracy requirements of 1% for SW and 0.5% for outgoing LW observations. Ground to flight or in-flight changes are monitored using protocols employing onboard and vicarious calibration sources. Studies of flight data show that SW response can change dramatically due to optical contamination. with greatest impact in blue-to UV radiance, where tungsten lamps are largely devoid of output. While science goals remain unchanged for ERB Climate Data Record, it is now understood that achieving these goals is more difficult for two reasons. The first is an increased understanding of the dynamics of the Earth/atmosphere system which demonstrates that separation of natural variability from anthropogenic change on decadal time scales requires observations with higher accuracy and stabilit

Priestley, Kory J.↗
NASA NTRS2013

The Version 8.6 SBUV Ozone Data Record: An Overview

Under a NASA program to produce long-term data records from instruments on multiple satellites, data from a series of nine Solar Backscatter Ultraviolet (SBUV and SBUV2) instruments have been re-processed to create a coherent ozone time series. Data from the BUV instrument on Nimbus 4, SBUV on Nimbus 7, and SBUV2 instruments on NOAA 9, 11, 14, 16, 17, 18, and 19 covering the period 1970-1972 and 1979-2011 were used to create a long-term data set. The goal is an ozone Earth Science Data Record - a consistent, calibrated ozone time series that can be used for trend analyses and other studies. In order to create this ozone data set, the radiances were adjusted and used to re-process the entire data records for each of the nine instruments. Inter-instrument comparisons during periods of overlap as well as comparisons with data from other satellite and ground-based instruments were used to evaluate the consistency of the record and make calibration adjustments as needed. Additional improvements in this version 8.6 processing included the use of the Brion, Daumont, and Malicet ozone cross sections, and a cloud-height climatology derived from Aura OMI measurements. Validation of the re-processed ozone shows that total column ozone is consistent with the Brewer Dobson network to within about 1 for the new time series. Comparisons with MLS, SAGE, sondes, and lidar show that ozone at individual levels in the stratosphere is generally consistent to within 5 percent.

ozone↗
DOE OSTI2022

Multispectral and Thermal Imager Onboard Aerial Platforms Instrument Handbook

The MicaSense Altum imager is an off-the-shelf, synchronized multispectral and thermal camera, combined with a Global Positioning System (GPS) unit and downwelling light sensor (DLS). The Altum takes images of the land surface within its field of view (FOV) across five visible bands and one longwave infrared thermal band. The sensor records the radiance and converts it to digital numbers. Imagery is radiometrically corrected, taking into account the sensor calibration, lens distortions, vignette effects, sun angle, and atmospheric effects (scattering and absorption). The photogrammetry software Agisoft PhotoScan v 1.4 is used to align and stitch the images into a larger composite image using the technique of structure from motion image capture to construct a dense cloud and 3D model of the surface, which is used to produce a digital elevation model of the terrain surveyed and orthomosaic imagery. Land surface leaf area index, albedo, and surface skin temperature are provided for the user. The user can perform raster calculations on the imagery to produce various other vegetative indices, which are used to indicate plant health and land surface characteristics, including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Normalized Difference Water Index (NDWI), surface temperature, and Enhanced_vegetation_index (EVI). This code is provided with the readme file for each data set. The images have a resolution of 20-60 cm/pixel, which are subsampled to 100 cm/pixel.

47 OTHER INSTRUMENTATION↗
NASA NTRS1991

Requirements of a solar diffuser and measurements of some candidate materials

If the solar spectral irradiance and the orientation and directional reflectance of a solar diffuser are known, then the spectral radiance of the diffuser is readily calculated and it can be used for the accurate absolute calibration of a satellite sensor. However, the solar diffuser is exposed during in-flight satellite sensor calibration to high-energy ultraviolet irradiance, particle impacts and atomic oxygen effects. This paper describes desirable solar diffuser characteristics and the results of proton and UV irradiation on the directional-hemispheric spectral reflectance, the bidirectional spectral reflectance factor and the polarization properties of candidate diffuser materials.

Guzman, Carmen T.↗
NASA NTRS1993

Calibration of the AVHRR visible and near-IR bands by atmospheric scattering, ocean glint and desert reflection

A method for calibrating satellite sensors (such as the AVHRR visible and NIR bands) is proposed by which the sensors are calibrated using well-known physical characteristics of the atmosphere, ocean, and deserts, as well as the digital satellite imagery. The approach, independent of ground support, used the following three phenomena: molecular scattering over the ocean for absolute visible band calibration; ocean glint, to transfer the calibration from the visible band to the NIR band; and desert reflectance to monitor, independently, the stability of the visible and NIR bands. The method was applied to NOAA-7, -9, and -11 sensors. The results of the ocean and the desert calibration methods were found to differ in the brightness range and the spectral response of the radiance source (molecular scattering over the ocean versus the desert reflectance).

Kaufman, Y. J.↗