Constantine Lukashin

Achieving Climate Change Absolute Accuracy in Orbit

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREOs inherently high absolute accuracy will be verified and traceable on orbit to Systeme Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earths thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which...

Spectral Reflectance Corrections for Satellite Intercalibrations Using SCIAMACHY Data

High-resolution spectra measured by the ENVISAT SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) are used to develop spectral correction factors for satellite imager solar channels to improve the transfer of calibrations from one imager to another. SCIAMACHY spectra averaged for various scene types demonstrate the dependence of reflectance on imager spectral response functions. Pseudo imager radiances were computed separately over land and water from SCIAMACHY pixel spectra taken over two tropical domains. Spectral correction factors were computed from these pseudo imager radiance pairs. Intercalibrations performed using matched 12th Geostationary Operational Environmental Satellite and Terra MODerate-resolution Imaging Spectroradiometer (MODIS) visible ( ~ 0.65 μm) channel data over the same domains yielded ocean and land calibration gain and offset differences of 4.5% and 41%, respectively. Applying the spectral correction factors reduces the gain and offset differences to 0.1% and 3.8%, respectively, for free linear regression. Forcing the regression to use the known offset count reduces the land-ocean radiance differences to 0.3% or less. Similar difference reductions were found for matched MODIS and Meteosat-8 Spinning Enhanced Visible and Infrared Imager channel 2 ( ~ 0.86 μm ). The results demonstrate that SCIAMACHY-based spectral corrections can be used to significantly improve the transfer of calibration between any pair of imagers measuring reflected solar radiances under similar viewing and illumination conditions.

A Web-Based Tool for Calculating Spectral Band Difference Adjustment Factors Derived From SCIAMACHY Hyperspectral Data

Monitoring and adjusting calibrations of various satellite imagers is often exacerbated by differences in their spectral response functions (SRFs). To help account for spectral disparities among satellite imagers, a web-based spectral band difference correction calculator has been developed to characterize the relationship between a specified pair of satellite imager channels in the hyperspectral wavelength range of 240-1750 nm. These spectral band adjustment factors (SBAFs) are derived by convolving hyperspectral data from the SCIAMACHY instrument with the SRFs of a reference and target sensor. The SBAF tool can be used for all combinations of instrument/channel pairs over predefined Earth spectra, intercalibration domains, or user-defined spatial domains. Options are available to the user whereby SBAFs can be subsetted by time, angle, and/or precipitable water content. To evaluate the relative spectral calibration of SCIAMACHY, comparisons of SBAFs derived from SCIAMACHY, Hyperion, and Global Ozone Monitoring Experiment-2 (GOME-2) were performed. Using observations over the Libya 4 desert pseudoinvariant calibration site, it is shown that SCIAMACHY-based SBAFs are within 0.1%-0.3% of SBAFs derived from Hyperion or GOME-2. This result implies that spectral calibration differences, i.e., the calibration uncertainties of SCIAMACHY relative to other potential spectral sources, have a minor impact on the SBAF compared with the influence of effective parameter-based subsetting. The SCIAMACHY instrument is most suited for calculating the SBAFs, given its high spectral resolution, broad spectral range, and nearly continuous global availability. The calibration community will find this SBAF tool useful for mitigating the SRF differences that can complicate the comparison and intercalibration of visible and near-infrared sensors.

Uncertainty Estimates for Imager Reference Inter-Calibration With CLARREO Reflected Solar Spectrometer

One of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission objectives is to provide a high accuracy calibration standard on orbit to enable inter-calibration of existing sensors. In order to perform an accurate inter-calibration of imaging radiometers, such as VIIRS, one must take into account instrument sensitivity to polarization of incoming light. Even if the sensitivity to polarization of an instrument is established or known on orbit, the knowledge of the polarization state of reflected light is required to make relevant radiometric corrections. In the case when coincident polarimetric measurements are not available, we propose to use a combination of empirical and theoretical models to predict the polarization of solar reflected light at the top-of-atmosphere. We used observations from on-orbit polarimeter PARASOL to derive a global set of empirical Polarization Distribution Models (PDM) as a function of scene type and viewing geometry. The PDM accuracy for the mean values is estimated to match the 3% PARASOL uncertainty in its polarization measurements. The instantaneous single sample uncertainty of the prototype PDMs for the linear degree of polarization is contained within 15%. We also present the formalism and numeric estimates for resulting uncertainty for inter-calibration of an imaging radiometer with the CLARREO reference observations, including uncertainty due to instrument sensitivity to polarization. The uncertainty estimates consider a range of scenarios with varying data sampling, uncertainty of polarization, and imaging radiometer sensitivity to polarization. These results are used to recommend CLARREO mission requirements relevant to reference inter-calibration and polarization effects.

The Intercalibration of Geostationary Visible Imagers Using Operational Hyperspectral SCIAMACHY Radiances

Spectral band differences between sensors can complicate the process of intercalibration of a visible sensor against a reference sensor. This can be best addressed by using a hyperspectral reference sensor whenever possible because they can be used to accurately mitigate the band differences. This paper demonstrates the feasibility of using operational Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) large-footprint hyperspectral radiances to calibrate geostationary Earth-observing (GEO) sensors. Near simultaneous nadir overpass measurements were used to compare the temporal calibration of SCIAMACHY with Aqua Moderate Resolution Imaging Spectroradiometer band radiances, which were found to be consistent to within 0.44% over seven years. An operational SCIAMACHY/GEO ray-matching technique was presented, along with enhancements to improve radiance pair sampling. These enhancements did not bias the underlying intercalibration and provided enough sampling to allow up to monthly monitoring of the GEO sensor degradation. The results of the SCIAMACHY/GEO intercalibration were compared with other operational four-year Meteosat-9 0.65-μm calibration coefficients and were found to be within 1% of the gain, and more importantly, it had one of the lowest temporal standard errors of all the methods. This is more than likely that the GEO spectral response function could be directly applied to the SCIAMACHY radiances, whereas the other operational methods inferred a spectral correction factor. This method allows the validation of the spectral corrections required by other methods.

CLARREO Approach for Reference Intercalibration of Reflected Solar Sensors: On-Orbit Data Matching and Sampling

The implementation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission was recommended by the National Research Council in 2007 to provide an on-orbit intercalibration standard with accuracy of 0.3% (k = 2) for relevant Earth observing sensors. The goal of reference intercalibration, as established in the Decadal Survey, is to enable rigorous high-accuracy observations of critical climate change parameters, including reflected broadband radiation [Clouds and Earths Radiant Energy System (CERES)], cloud properties [Visible Infrared Imaging Radiometer Suite (VIIRS)], and changes in surface albedo, including snow and ice albedo feedback. In this paper, we describe the CLARREO approach for performing intercalibration on orbit in the reflected solar (RS) wavelength domain. It is based on providing highly accurate spectral reflectance and reflected radiance measurements from the CLARREO Reflected Solar Spectrometer (RSS) to establish an on-orbit reference for existing sensors, namely, CERES and VIIRS on Joint Polar Satellite System satellites, Advanced Very High Resolution Radiometer and follow-on imagers on MetOp, Landsat imagers, and imagers on geostationary platforms. One of two fundamental CLARREO mission goals is to provide sufficient sampling of high-accuracy observations that are matched in time, space, and viewing angles with measurements made by existing instruments, to a degree that overcomes the random error sources from imperfect data matching and instrument noise. The data matching is achieved through CLARREO RSS pointing operations on orbit that align its line of sight with the intercalibrated sensor. These operations must be planned in advance; therefore, intercalibration events must be predicted by orbital modeling. If two competing opportunities are identified, one target sensor must be given priority over the other. The intercalibration method is to monitor changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, optics spectral response, and sensitivity to polarization. In this paper, we use existing satellite data and orbital simulation methods to determine mission requirements for CLARREO, its instrument pointing ability, methodology, and needed intercalibration sampling and data matching for accurate intercalibration of RS radiation sensors on orbit. We conclude that with the CLARREO RSS in a polar 90° inclination orbit at a 609-km altitude, estimated intercalibration sampling will limit the uncertainty contribution from data matching noise to 0.3% (k = 2) over the climate autocorrelation time period. The developed orbital modeling and intercalibration event prediction will serve as a framework for future mission operations.

Sensitivity of Intercalibration Uncertainty of the CLARREO Reflected Solar Spectrometer Features

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission was recommended by the National Research Council in 2007 to conduct highly accurate and International System of Unit-traceable decadal change observations and provide an on-orbit intercalibration standard with high accuracy for relevant Earth observing sensors. The goal of reference intercalibration is to enable rigorous observations of critical climate change variables, including reflected broadband radiation, cloud properties, and changes in surface albedo, including snow and ice albedo feedback, to be made consistently among different sensors. This requires the CLARREO Reflected Solar Spectrometer (RSS) to provide highly accurate spectral reflectance measurements to establish an on-orbit reference with a radiometric accuracy requirement better than 0.3% (k = 2) for existing sensors. In this paper, MODTRAN-simulated top-of-atmosphere spectral data and spectral measurements from the SCIAMACHY instrument on Envisat are used to determine sensitivity of intercalibration uncertainty on key design parameters of the CLARREO spectrometer: spectral range, sampling and resolution. Their impact on intercalibration uncertainty for MODIS and VIIRS imagers is estimated for various surface types (ocean, vegetation, desert, snow, deep convective clouds, clouds and all-sky). Results indicate that for the visible to near-infrared spectral region (465-856 nm), the RSS instrument under current design concept produces uncertainties of 0.16% for the spectral range and 0.3% for the sampling and resolution. However, for the water vapor absorption bands in the short wavelength infrared region (1242-1629 nm), the same requirement is not met for sampling and resolution due to their high sensitivity to the influence of atmospheric water vapor.

Using SCIAMACHY to improve corrections for spectral band differences when transferring calibration between visible sensors

The advent of well-calibrated and well-characterized visible sensors, such as the MODerate resolution Imaging Spectroradiometer (MODIS), has allowed the opportunity to cross-calibrate other contemporary, un-calibrated visible sensors. Most of the operational geostationary-Earth-orbit satellite (GEOsat) visible sensors do not have a direct means of on-orbit calibration, and the cross-calibration of MODIS with GEOsats is plagued by the differences in the sensor spectral response functions (SRFs). Spectral band adjustment factors (SBAFs) are needed to correct for the solar flux and inter-band gaseous absorption discrepancies that are caused by SRF differences, which are sometimes significant. In addressing this problem, this manuscript describes a spectral band correction technique that employs Envisat SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) hyper-spectral radiances to derive pseudo-radiance, or equivalent-radiance, values for the MODIS and GEOsat sensors over the calibration targets, which include a desert, deep convective clouds, and a MODIS-with-GEOsat ray-matching ocean domain. The regressions from these equivalent-radiance comparisons constitute the necessary adjustment factor. The regressions of MODIS and GEOsat pseudo-radiance values are well-behaved, with small standard error and offsets, for spectral bands that are similar. When comparing narrowband to broadband, however, the correction difference between deep convective and maritime stratus clouds can be as large as 6%. New scene-selection criteria are investigated to derive spectral band adjustment factors that are dependent on the calibration-target domains, which reduces this uncertainty. Application of these SBAFs, which are validated for accuracy using ray-matched SCIAMACHY and GEOstat radiances, is shown to bring independently derived absolute calibrations to within 1% agreement, or better, with one-another. These spectral band adjustment factors are critical for obtaining accurate and consistent absolute calibration among multiple independent and scene-dependent inter-calibration techniques given that the variation of the SBAFs as a function of scene type can be close to 8% for a narrowband-to-broadband correction.

CLARREO Reflected Solar Spectrometer: Restrictions for Instrument Sensitivity to Polarization

The foundation for future space mission Climate Absolute Radiance and Refractivity Observatory (CLARREO) is the ability to produce climate change benchmark records and provide on-orbit calibration standard through the highly accurate and Système Internationale-traceable observations. The accuracy of CLARREO measurements is set to 0.3% (k=2) for spectrally resolved reflectance. The instrument sensitivity to polarization and polarization of reflected light at the top of atmosphere are the sources for systematic uncertainty. In this paper, we estimate radiometric errors due to polarization effects for CLARREO benchmark and reference intercalibration observations. Data from the Polarization and Anisotropy of Reflectance for Atmospheric Sciences coupled with Observations from Lidar (PARASOL) instrument, a spaceborne polarimeter, have been used in combination with the orbital modeling of Earths sampling. For the CLARREO benchmark data, we used simulated annual nadir sampling for the polar orbit with 90° inclination, and for the intercalibration with cross-track sensors on the JPSS, such as CERES and VIIRS, we simulated on-orbit matched data sampling. Selected PARASOL data over one full solar year provided polarization parameters in visible (VIS) spectral range. For estimating polarization in near infrared (NIR) spectral range, we used a radiative transfer model. Our results show that to limit error contribution due to polarization to half of the allowed total, the sensitivity to polarization of CLARREO reflected solar instrument should not exceed 0.5% (k=2) in spectral range from VIS to NIR.

CLARREO Pathfinder: On-orbit data matching and sensor inter-calibration

One of the objectives of CLARREO Pathfinder mission is to demonstrate on-orbit data matching for sensor inter-calibration The CLARREO Pathfinder approach for reference inter-calibration is based on measuring spectral reflectance with high accuracy and establishing an on-orbit reference for operating Earth viewing sensors: CERES and VIIRS on JPSS. The mission goal is to be able to provide CLARREO reference observations that are matched in temporal and angular domains with measurements from the aforementioned instruments, with sampling sufficient to overcome the random error sources from imperfect data matching. The inter-calibration method is to monitor changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, spectral response function, and sensitivity to polarization. In this paper, we focus on estimating uncertainty for inter-calibration of imaging sensors such as VIIRS.