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At least 163 records · Page 9

High Altitude Measurements of Radiance at High Spectral and Spatial Resolution for SIMBIOS Sensor Calibration, Validation, and Intercomparisons

The successful combination of data from different ocean color sensors depends on the correct interpretation of signal from each of these sensors. Ideally, the sensor measured signals are calibrated to geophysical units of spectral radiance, and sensor artifacts are removed and corrected. The calibration process resamples the signal into a common radiometric data space so that subsequent ocean color algorithms that are applied to the data are based on physical processes and are inherently sensor independent. The objective of this project is to calibrate and validate the on-orbit radiometric characteristics of Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) with underflights of NASA's calibrated Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). This objective is feasible because AVIRIS measures the same spectral range as SeaWIFS at higher spectral resolution. In addition to satellite sensor underflights, the AVIRIS project has supported comparison and analysis of the radiometric calibration standards used for AVIRIS and SeaWIFS. To date, both the OCTS and SeaWIFS satellite sensors have been underflown by AVIRIS with matching spectral, spatial, geometric, radiometric, and temporal domains. The calibration and validation objective of this project is pursued for the following reasons: (1) Calibration is essential for the quantitative use of SeaWIFS and other SIMBIOS (Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies) sensor data; (2) Calibration in the laboratory of spaceborne sensors is challenging; (3) Satellite sensors are subjected aging on the ground and to trauma during launch; (4) The Earth orbit environment is significantly different than the laboratory calibration environment; (5) Through years of effort AVIRIS has been demonstrated to be well calibrated; and (6) AVIRIS can match the spectral and spatial observation characteristics near the top of the atmosphere at the time of SeaWIFS measurements.

Green, Robert O.↗

Products of the SNPP VIIRS SD Screen Transmittance and the SD BRDFs From Both Yaw Maneuver and Regular On-Orbit Data

To ensure data quality, the Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite regularly performs on-orbit radiometric calibration of its 22 spectral bands. The primary radiance source for the calibration of the VIIRS reflective solar bands (RSBs) is a sunlit onboard solar diffuser (SD).During the calibration process, sunlight goes through a perforated plate (the SD screen) and then strikes the SD. The sunlight, scattered off the SD of near-Lambertian property, is used for the calibration. Consequently, the spectral radiance of the scattered sunlight is proportional to the product of the SD screen transmittance and the SD bidirectional reflectance distribution function (BRDF) value at the observation direction. The BRDF value is decomposed to the product of its initial value at launch and a numerical degradation factor that quantifies the decrease from the initial value. The degradation factor is determined by an onboard SD stability monitor (SDSM). During the BRDF degradation factor determination process, the SDSM receives the SD scattered sunlight and the sunlight that goes through another perforated plate at almost the same time. The ratio of the signal strengths from the two observations is used to determine the BRDF degradation factor. Consequently, the RSB radiometric calibration requires the accurate knowledge of the product of the SD screen transmittance and the initial BRDF value as sensed by the RSB and the SDSM detectors. We use both yaw maneuver and a small portion of regular on-orbit data to determine the products.

Lei, Ning↗

The Radiometric Scaling of the MODIS and VIIRS Imagers to a Common Reference and Stability Analysis for the Next Edition of CERES Products

The NASA CERES project has provided the climate quality observed TOA and computed surface fluxes to the scientific community. CERES uses MODIS and VIIRS imagers to retrieve cloud properties needed to convert Terra, Aqua, NPP, and NOAA-20 CERES footprint radiance observations into fluxes. The imagers are also used to radiometrically scale the geostationary sensors (GEO) radiances to the imager calibration reference to ensure that the GEO derived cloud properties and broadband TOA fluxes are consistent in both space and time. Both the imager and GEO retrieved cloud properties are used to compute the surface fluxes. The CERES imager and GEO calibration team uses ray-matched radiance pairs to radiometrically scale the SNPP and NOAA-20 VIIRS sensors to the Aqua-MODIS calibration reference. The radiometric scaling is further validated using geostationary imagers as transfer radiometers. The team will rely primarily on deep convective clouds to monitor the imager channel calibration stability and to correct for short term calibration drifts. The DSCOVR satellite was launched on February 25, 2015 and orbits around the L1 Lagrange point directly between the Earth and the sun. The EPIC sensor contains no onboard calibration systems. However, multiple inter-calibration studies have shown that the EPIC imager is very stable in time. The excellent radiometric stability of EPIC allows the use of EPIC observations as a stable reference to validate both the short term drift corrections of the imagers, as well as to validate the radiometric scaling factors between them. Examples of the imager relative calibration using EPIC before and after radiometric scaling will be shown along with the results from the use of invariant targets to remove imager calibration drifts.

DSCOVR-EPIC↗

Quantum Efficient Detectors for Use in Absolute Calibration

The trap or quantum efficient detector has a quantum efficiency of greater than 0.98 for the region from 450 to 900 nm. The region of flattest response is from 600 to 900 nm. The QED consists of three windowless Hamamatsu silicon detectors. The QED was mounted below AVIRIS to monitor the Spectralon panel for changes in radiance during radiometric calibration. The next step is to permanently mount the detector to AVIRIS and monitor the overall radiance of scenes along with calibration.

Faust, Jessica↗

Spectral calibration analysis of the airborne oceanographic lidar

Efforts were concentrated on the spectral resolution of the Airborne Oceanographic Lidar (AOL). This year's work was targeted towards the analysis of calibration techniques to enable the AOL to measure absolute radiances of both passive and active modes of operation. Absolute spectral calibration of the AOL is necessary in order to fully understand and monitor the sensitivity and stability of the total system. Calibration is also needed to obtain valid surface truth data, with which to improve the accuracy of satellite-borne oceanic color scanners. In particular, accurate measurements of oceanic chlorophyll concentrations rests upon reliable irradiance calibrations of both laser induced and solar induced chlorophyll fluoresence. An analysis was performed on the spectral calibration methods used by the AOL. The optical path of the instrumentation was examined to study how the radiance from a calibration sphere was influenced. Ray tracing analysis was performed, including the Cassegrain-telescope optics. It was determined that the calibration radiance was significantly effected by optical-defocusing, due to close positioning of the calibration sphere with respect to the telescope. Since the multi-mode usages of the AOL require varying altitudes and trajectories, a computational algorithm was developed to compensate for image distortions of the telescope optics. Secondary mirror blockage, secondary vignetting, and beam divergence was determined, in order to account for the actual amount of calibrated flux received at the spectral sensors.

Rousey, Carlton E.↗

Terra and Aqua MODIS Collection 7 Level 1B Algorithm

MODIS continues to be an important instrument for NASA’s Earth Observing System (EOS). Terra and Aqua MODIS have produced more than 22 and 20 years of global datasets that have significantly helped scientists better understand the Earth’s systems respectively. The MODIS Level-1B (L1B) algorithms use the uncalibrated, geolocated Earth scene observations as input and convert the instrument response into calibrated reflectance and radiance, which are used to generate the downstream science products. The sustained calibration and characterization activities undertaken by the MODIS Characterization Support Team have resulted in several upgrades to the L1B algorithms in order to maintain accurate calibration in the data products. In this paper, we present an overview of the L1B algorithm designated as Collection 7. Various algorithm enhancements both in the reflective bands and thermal bands characterization, are currently under science testing and evaluation. Once applied in data processing (projected in early 2023), they are expected to manifest in improved science products, both in terms of radiometric accuracy and long-term stability.

MODIS↗

Calibration of the AVHRR visible and near IR channels using radiances measured over remote ocean areas

An inflight absolute calibration method has been adapted and applied to channel 1 of the AVHRR. The approach is based on AVHRR observations in channels 1, 2 and 4. A rigorous cloud screening is performed, based on the homogeneity of the data in channel 1 and 2 and on the temperature in channel 4. In a combined approach, the off-nadir view satellite count in channel 2 is used to detect the aerosol optical thickness and loading and the count of channel 1 is used to calibrate this channel, based on the predictable Rayleigh scattering component. Water vapor data are used, and the channels are intercalibrated using the ratio between channels 1 and 2 over the glint region.

Vermote, Eric F.↗

CLARREO Pathfinder Solar Diffuser Calibration Progress

Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission’s Hyperspectral Imager for Climate Science (HySICS) instrument’s transmissive flight diffuser calibration is presented. The absolute Bidirectional Transmittance Distribution Function (BTDF) measurement of the transmissive diffuser is needed to calculate the instrument’s absolute efficiency. Along with a known solar irradiance source such as Total Solar Irradiance Sensor (TSIS), it can provide an absolute irradiance measurement path on orbit, with NIST traceability. This provides an additional path for CPF to cross compare with other on orbit sensors’ measurement such as Visible-Infrared Imaging Radiometer Suite (VIIRS), Clouds and the Earth’s Radiant Energy System (CERES). The flight diffuser was calibrated at NASA’s Goddard Space Flight Center (GSFC) using the Facility’s Optical Scatterometer.

Bidirectional Transmittance Distribution Function↗

GIFTS SM EDU Level 1B Algorithms

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) SensorModule (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the GIFTS SM EDU Level 1B algorithms involved in the calibration. The GIFTS Level 1B calibration procedures can be subdivided into four blocks. In the first block, the measured raw interferograms are first corrected for the detector nonlinearity distortion, followed by the complex filtering and decimation procedure. In the second block, a phase correction algorithm is applied to the filtered and decimated complex interferograms. The resulting imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected spectrum. The phase correction and spectral smoothing operations are performed on a set of interferogram scans for both ambient and hot blackbody references. To continue with the calibration, we compute the spectral responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. We now can estimate the noise equivalent spectral radiance (NESR) from the calibrated ABB and HBB spectra. The correction schemes that compensate for the fore-optics offsets and off-axis effects are also implemented. In the third block, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel performance evaluation. Finally, in the fourth block, the single pixel algorithms are applied to the entire FPA.

Tian, Jialin↗

GIFTS SM EDU Data Processing and Algorithms

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three Focal Plane Arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the processing algorithms involved in the calibration stage. The calibration procedures can be subdivided into three stages. In the pre-calibration stage, a phase correction algorithm is applied to the decimated and filtered complex interferogram. The resulting imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected blackbody reference spectra. In the radiometric calibration stage, we first compute the spectral responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. During the post-processing stage, we estimate the noise equivalent spectral radiance (NESR) from the calibrated ABB and HBB spectra. We then implement a correction scheme that compensates for the effect of fore-optics offsets. Finally, for off-axis pixels, the FPA off-axis effects correction is performed. To estimate the performance of the entire FPA, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel performance evaluation.

Tian, Jialin↗

Results from Source-Based and Detector-Based Calibrations of a CLARREO Calibration Demonstration System

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is formulated to determine long-term climate trends using SI-traceable measurements. The CLARREO mission will include instruments operating in the reflected solar (RS) wavelength region from 320 nm to 2300 nm. The Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO and facilitates testing and evaluation of calibration approaches. The basis of CLARREO and SOLARIS calibration is the Goddard Laser for Absolute Measurement of Response (GLAMR) that provides a radiance-based calibration at reflective solar wavelengths using continuously tunable lasers. SI-traceability is achieved via detector-based standards that, in GLAMRs case, are a set of NIST-calibrated transfer radiometers. A portable version of the SOLARIS, Suitcase SOLARIS is used to evaluate GLAMRs calibration accuracies. The calibration of Suitcase SOLARIS using GLAMR agrees with that obtained from source-based results of the Remote Sensing Group (RSG) at the University of Arizona to better than 5 (k2) in the 720-860 nm spectral range. The differences are within the uncertainties of the NIST-calibrated FEL lamp-based approach of RSG and give confidence that GLAMR is operating at 5 (k2) absolute uncertainties. Limitations of the Suitcase SOLARIS instrument also discussed and the next edition of the SOLARIS instrument (Suitcase SOLARIS- 2) is expected to provide an improved mechanism to further assess GLAMR and CLARREO calibration approaches. (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Angal, Amit↗

Calibration of of Sun Photometers and Sky Radiance Sensors

The main source of error in retrieving aerosol optical thicknesses using sun photometry comes from the determination of the TOA voltages. The degradation of interference filters is the most important source of the long-term changes in the cross-calibrations. Although major improvements have been made in the design of the filters (interference filters fabricated using ion-assisted deposition), the filters remain the principal factor limiting performance of the sun photometers. Degradation of filters necessitates frequent calibration of sun photometers and frequent measurements of the filter transmission or the relative system response. The degradation of the filters mounted on the CIMEL sun photometers have been monitored since 1993 by the Aerosol Robotic Network (AERONET) project. The decay reported by Holben et al. for the first two years of a CIMEL#s operation is between 1 and 5%. Nevertheless, the filters mounted on CIMEL instruments are regularly replaced after two years of use. The cross-calibration technique consists of taking measurements concurrently with the uncalibrated and the reference sun photometers. While analyzing measurements, the quality of the calibration has to be checked, using the following considerations: (1) any cirrus clouds suspected to be masking the sun, during the calibration period, need to be reported and the corresponding data set removed; and (2) the stability of the day needs to be checked. This chapter will describe calibration techniques, facilities, and protocols used for calibrating sun photometers and sky radiometers.

Pietras, Christophe↗

Effects of Out-of-Band and Time-Varying Relative Spectral Response on the Calibration of MODIS Reflective Solar Bands

Calibration of the on-orbit gain changes of the narrow bandwidth reflective solar bands (RSB) of Terra and Aqua MODIS is usually based on the band center wavelength. The relative spectral response (RSR) of each band is assumed to be constant on orbit and the time dependence of an overall gain factor is calculated. Any on-orbit changes to the RSR of the MODIS bands will introduce some error into the calibration and may also have an impact on the Earth scene radiance retrieval. We consider two different ways to track how the RSR of the MODIS RSB may be changing on orbit, and the effects that these changes will have on the calibration. First, we study the broadband degradation of the MODIS scan mirror and how it may be changing the effective out-of-band response of the RSB. Second, we examine in-band RSR measurements from the spectro-radiometric calibration assembly (SRCA) carried on-board both MODIS instruments. We find that RSR changes have a relatively small effect on the radiance calibrated using the on-board solar diffuser, generally less than 0.5% for all RSB at any time in the missions, though the effect may be slightly larger for some scan angles. The impact of RSR changes on the Earth scene radiance retrieval is highly dependent on the spectral properties of the scene and could be significantly larger. The bands showing the largest impacts are Terra bands 1, 4, 8, 9, 17, and 19 and Aqua bands 8 and 9.

MODIS↗

Radiance standards

Two radiometric calibration sources that are utilized by various groups are maintained and operated. One source is a 6-ft diameter sphere and the other a 4-ft diameter hemisphere. Both are internally coated with multiple layers of barium sulfate and house an array of 12 tungsten filament-quartz iodine lamps that provide a uniform diffuse target of radiance traceable to NBS. The lamps are baffled and arranged so that they are not part of the scene during calibrations. Both systems have a 10-inch viewing aperture. The hemisphere is somewhat more versatile in that the aperture can be changed and the system is movable so calibrations can be done at other sites. Together, these systems have supported numerous GSFC projects and missions during this review period. They are listed.

Lester, D. L.↗

TES Level 1 Algorithms: Interferogram Processing, Geolocation, Radiometric, and Spectral Calibration

The Tropospheric Emission Spectrometer (TES) on the Earth Observing System (EOS) Aura satellite measures the infrared radiance emitted by the Earth's surface and atmosphere using Fourier transform spectrometry. The measured interferograms are converted into geolocated, calibrated radiance spectra by the L1 (Level 1) processing, and are the inputs to L2 (Level 2) retrievals of atmospheric parameters, such as vertical profiles of trace gas abundance. We describe the algorithmic components of TES Level 1 processing, giving examples of the intermediate results and diagnostics that are necessary for creating TES L1 products. An assessment of noise-equivalent spectral radiance levels and current systematic errors is provided. As an initial validation of our spectral radiances, TES data are compared to the Atmospheric Infrared Sounder (AIRS) (on EOS Aqua), after accounting for spectral resolution differences by applying the AIRS spectral response function to the TES spectra. For the TES L1 nadir data products currently available, the agreement with AIRS is 1 K or better.

infrared remote sensing↗

Inter-Calibration and Concatenation of Climate Quality Infrared Cloudy Radiances from Multiple Instruments

A change in climate is not likely captured from any single instrument, since no single instrument can span decades of time. Therefore, to detect signals of global climate change, observations from many instruments on different platforms have to be concatenated. This requires careful and detailed consideration of instrumental differences such as footprint size, diurnal cycle of observations, and relative biases in the spectral brightness temperatures. Furthermore, a common basic assumption is that the data quality is independent of the observed scene and therefore can be determined using clear scene data. However, as will be demonstrated, this is not necessarily a valid assumption as the globe is mostly cloudy. In this study we highlight challenges in inter-calibration and concatenation of infrared radiances from multiple instruments by focusing on the analysis of deep convective or anvil clouds. TRMM/VIRS is potentially useful instrument to make correction for observational differences in the local time and foot print sizes, and thus could be applied retroactively to vintage instruments such as AIRS, IASI, IRIS, AVHRR, and HIRS. As the first step, in this study, we investigate and discuss to what extent AIRS and VIRS agree in capturing deep cloudy radiances at the same local time. The analysis also includes comparisons with one year observations from CrIS. It was found that the instruments show calibration differences of about 1K under deep cloudy scenes that can vary as a function of land type and local time of observation. The sensitivity of footprint size, view angle, and spectral band-pass differences cannot fully explain the observed differences. The observed discrepancies can be considered as a measure of the magnitude of issues which will arise in the comparison of legacy data with current data.

cloudy radiance↗

Forty-Year Calibrated Record of Earth-Surface Reflected Radiance from Landsat: A Review

Sensors on Landsat satellites have been collecting images of the Earth's surface for nearly 40 years. These images have been invaluable for characterizing and detecting changes in the land cover and land use of the world. Although initially conceived as primarily picture generating sensors, even the early sensors were radiometrically calibrated and spectrally characterized prior to launch and incorporated some capabilities to monitor their radiometric calibration once on orbit. Recently, as the focus of studies has shifted to monitoring Earth surface parameters over significant periods of time, serious attention has been focused toward bringing the data from all these sensors onto a common radiometric scale over this 40-year period. This effort started with the most recent systems and then was extended back in time. Landsat-7 ETM+, the best-characterized sensor of the series prior to launch and once on orbit, and the most stable system to date, was chosen to serve as the reference. The Landsat-7 project was the first of the series to build an image assessment system into its ground system, allowing systematic characterization of its sensors and data. Second, the Landsat-5 TM (still operating at the time of the Landsat-7 launch and continues to operate) calibration history was reconstructed based on its internal calibrator, vicarious calibrations, pseudo-invariant sites and a tie to Landsat-7 ETM+ at the time of the commissioning of Landsat-7. This process was performed in two iterations: the earlier one relied primarily on the TM internal calibrator. When this was found to have some deficiencies, a revised calibration was based more on pseudo-invariant sites, though the internal calibrator was still used to establish the short-term variations in response due to icing build up on the cold focal plane. As time progressed, a capability to monitor the Landsat-5 TM was added to the image assessment system. The Landsat-4 TM, which operated from 1982-1992, was the third system to which the radiometric scale was extended. The limited and broken use of the Landsat-4 TM made this analysis more difficult. Eight-day separated image pairs from Landsat-5 combined with analysis of pseudo invariant sites established this history. The fourth and most challenging effort was making the Landsat-1 to -5 MSS sensors' data internally radiometrically consistent. This effort was particularly complicated by the age of the MSS data, varying formats and processing levels in the archive, limited datasets, and limited documentation available. Ultimately, pseudo-invariant sites were identified in North America and used for this effort. Note that most of the Landsat-MSS archived data had already been calibrated using the MSS internal calibrators, so this processing was imbedded in the result. The final effort was developing an absolute scale for Landsat MSS similar to what was already established for the "TM" sensors. This was accomplished by using simultaneous data from Landsat-5 MSS and Landsat-5 TM, accounting for spectral differences between the sensors using EO-1 Hyperion data. The recalibrated history of the Landsat data and implications to users are discussed. The key result from this work is a consistently calibrated Landsat data archive that spans nearly 40 years with total uncertainties on the order of 10% or less for most sensors and bands.

Markham, Brian↗