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NASA NTRS2016

Global Space-Based Inter-Calibration System Reflective Solar Calibration Reference: From Aqua MODIS to S-NPP VIIRS

The MODIS has successfully operated on-board the NASA's EOS Terra and Aqua spacecraft for more than 16 and 14 years, respectively. MODIS instrument was designed with stringent calibration requirements and comprehensive on-board calibration capability. In the reflective solar spectral region, Aqua MODIS has performed better than Terra MODIS and, therefore, has been chosen by the Global Space-based Inter-Calibration System (GSICS) operational community as the calibration reference sensor in cross-sensor calibration and calibration inter-comparisons. For the same reason, it has also been used by a number of earth observing sensors as their calibration reference. Considering that Aqua MODIS has already operated for nearly 14 years, it is essential to transfer its calibration to a follow-on reference sensor with a similar calibration capability and stable performance. The VIIRS is a follow-on instrument to MODIS and has many similar design features as MODIS, including their on-board calibrators (OBC). As a result, VIIRS is an ideal candidate to replace MODIS to serve as the future GSICS reference sensor. Since launch, the S-NPP VIIRS has already operated for more than 4 years and its overall performance has been extensively characterized and demonstrated to meet its overall design requirements. This paper provides an overview of Aqua MODIS and S-NPP VIIRS reflective solar bands (RSB) calibration methodologies and strategies, traceability, and their on-orbit performance. It describes and illustrates different methods and approaches that can be used to facilitate the calibration reference transfer, including the use of desert and Antarctic sites, deep convective clouds (DCC), and the lunar observations.

Xiong, Xiaoxiong↗
NASA NTRS2017

A Consistent EPIC Visible Channel Calibration using VIIRS and MODIS as a Reference

The Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) satellite constantly images the sunlit disk of Earth from the Lagrange-1 (L1) point in 10 spectral channels spanning the UV, VIS, and NIR spectrums. Recently, the DSCOVR EPIC team has publicly released version 2 dataset, which has implemented improved navigation, stray-light correction, and flat-fielding of the CCD array. The EPIC 2-year data record must be well-calibrated for consistent cloud, aerosol, trace gas, land use and other retrievals. Because EPIC lacks onboard calibrators, the observations made by EPIC channels must be calibrated vicariously using the coincident measurements from radiometrically stable instruments that have onboard calibration systems. MODIS and VIIRS are best-suited instruments for this task as they contain similar spectral bands that are well-calibrated onboard using solar diffusers and lunar tracking. We have previously calibrated the EPIC version 1 dataset by using EPIC and VIIRS angularly matched radiance pairs over both all-sky ocean and deep convective clouds (DCC). We noted that the EPIC image required navigations adjustments, and that the EPIC stray-light correction provided an offset term closer to zero based on the linear regression of the EPIC and VIIRS ray-matched radiance pairs. We will evaluate the EPIC version 2 navigation and stray-light improvements using the same techniques. In addition, we will monitor the EPIC channel calibration over the two years for any temporal degradation or anomalous behavior. These two calibration methods will be further validated using desert and DCC invariant Earth targets. The radiometric characterization of the selected invariant targets is performed using multiple years of MODIS and VIIRS measurements. Results of these studies will be shown at the conference.

Haney, C. O.↗
NASA NTRS2018

Assessment of Terra MODIS Thermal Emissive Band Calibration Using Cold Targets and Measurements in Lunar Roll Events

Terra MODIS has provided continuous global observations for science research and applications for more than 18 years. The MODIS Thermal emissive bands (TEB) radiometric calibration uses a quadratic function for instrument response. The calibration coefficients are updated using the response of an on-board blackbody (BB) in quarterly warm-up and cool-down (WUCD) events. As instrument degradation and electronic crosstalk of long-wave infrared (LWIR) bands 27 to 30 developed substantial issues, accurate calibration is crucial for a high-quality L1B product. The on-board BB WUCD temperature ranges from 270 K to 315 K and the derived nonlinear response has a relatively large uncertainty for the offset, especially for these LWIR bands, which affects the measurements of low brightness temperature (BT) scenes. In this study, the TEB radiometric calibration impact on the L1B product is assessed using selected cold targets and the measurements during regular lunar rolls. The cold targets include Antarctic Dome Concordia (Dome-C) and deep convective clouds (DCC) for the calibration assessment, focusing on bands 27 to 30. Dome-C area is covered with uniformly-distributed permanent snow, and the atmospheric effect is small and relatively constant. Usually the DCC is treated as an invariant earth target to evaluate the reflective solar band calibration. The DCC can also be treated as a stable target to assess the performance of TEB calibration. During a scheduled lunar observation event with a spacecraft roll maneuver to view the moon through the space view port, the instrument cavity provides a stable reference for calibration assessment. The long-term trending of BT measurements and the relative difference between scan mirror sides and detectors are used for the assessment of the calibration consistency and stability. The comparison of L1B products over the selected targets before and after the calibration coefficients update can be used to assess the impact of a calibration look-up table (LUT) update. This assessment is beneficial for future calibration algorithm and LUT update procedure improvements for enhancing the L1B product quality.

Chang, Tiejun↗
NASA NTRS2018

Geostationary Visible Imager Calibration for the CERES SYN1deg Edition 4 Product

The Clouds and the Earth’s Radiant Energy System (CERES) project relies on geostationary (GEO) imager derived TOA broadband fluxes and cloud properties to account for the regional diurnal fluctuations between the Terra and Aqua CERES and MODIS measurements. Anchoring the GEO visible calibration to the MODIS reference calibration and stability is critical for consistent fluxes and cloud retrievals across the 16 GEO imagers utilized in the CERES record. The CERES Edition 4A used GEO and MODIS ray-matched radiance pairs over all-sky tropical ocean (ATO-RM) to transfer the MODIS calibration to the GEO imagers. The primary GEO ATO-RM calibration was compared with the deep convective cloud (DCC) ray-matching and invariant desert/DCC target calibration methodologies, which are all tied to the same Aqua-MODIS calibration reference. Results indicate that most GEO record mean calibration method biases are within 1% with respect to ATO-RM. Most calibration method temporal trends were within 0.5% relative to ATO-RM. The monthly gain trend standard errors were mostly within 1% for all methods and GEOs. The close agreement amongst the independent calibration techniques validates all methodologies, and verifies that the coefficients are not artifacts of the methodology but rather adequately represent the true GEO visible imager degradation.

Doelling, David↗
NASA NTRS2018

Results from the Deep Convective Clouds-Based Response Versus Scan-Angle Characterization for the MODIS Reflective Solar Bands

The Terra and Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) scan mirror reflectance is a function of the angle of incidence (AOI) and was characterized prior to launch by the instrument vendor. The relative change of the prelaunch response versus scan angle (RVS) is tracked and linearly scaled on-orbit using observations at two AOIs of 11.2° and 50.2° corresponding to the moon view and solar diffuser, respectively. As the missions continue to operate well beyond their design life of six years, the assumption of linear scaling between the two AOIs is known to be inadequate in accurately characterizing the RVS, particularly at short wavelengths. Consequently, an enhanced approach of supplementing the on-board measurements with response trends from desert pseudoinvariant calibration sites (PICS) was formulated in MODIS Collection 6 (C6). An underlying assumption for the continued effectiveness of this approach is the long-term (multiyear) and short-term (month to month) stability of the PICS. Previous work has shown that the deep convective clouds (DCC) can also be used to monitor the onorbit RVS performance with less trend uncertainties compared with desert sites. In this paper, the raw sensor response to the DCC is used to characterize the on-orbit RVS on a band and mirror-side basis. These DCC-based RVS results are compared with those of C6 PICS-based RVS, showing an agreement within 2% observed in most cases. The pros and cons of using a DCC-based RVS approach are also discussed in this paper. Although this reaffirms the efficacy of the C6 PICS-based RVS, the DCC-based RVS approach presents itself as an effective alternative for future considerations. Potential applications of this approach to other instruments, such as Suomi National Polarorbiting Partnership, Joint Polar Satellite Systems, and Visible Infrared Imaging Radiometer Suite, are also discussed.

Angal, Amit↗
NASA NTRS2019

The Inter-Calibration of the DSCOVR EPIC Imager 2 with Aqua-MODIS and NPP-VIIRS

The Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) continuously observes the illuminated disk from the Lagrange-1 point. The EPIC sensor was designed to monitor the diurnal variation of ozone, clouds, aerosols, and vegetation, especially those features that benefit from observation near-backscatter conditions. The EPIC sensor does not contain any onboard calibration systems. This study describes the inter-calibration of EPIC channels 5 (0.44 μm), 6 (0.55 μm), 7 (0.68 μm), and 10 (0.78 μm) with respect to Aqua-MODIS and NPP-VIIRS. The calibration is transferred using coincident ray-matched reflectance pairs over all-sky tropical ocean (ATO) and deep convective cloud (DCC) targets. A robust and automated image-alignment technique based on feature matching was formulated to improve the navigation quality of the EPIC images. The EPIC V02 dataset exhibits improved navigation over V01. Because the visible channels display similar spatial features, a single visible channel can be used to co-register the remaining visible bands. The VIIRS-referenced EPIC ATO and DCC ray-matched calibration coefficients are within 0.3%. The EPIC four-year calibration trends based on VIIRS are within 0.15%/year. The MODIS-based EPIC calibration coefficients were compared against the Geogdzhayev and Marshak 2018 published calibration coefficients and are found to be within 1.6%.

DSCOVR↗
NASA NTRSDate not supplied

TPSAS-NF1676L-32020-DND

The Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) satellite has a constant unique view of the sunlit disk of the Earth from the Lagrange-1 (L1) point nearly a million miles away from the Earth. The DSCOVR EPIC team released the version 2 dataset last year which included many enhancements, such as improved navigation, stray-light correction, and flat-fielding. Since there is no on-board calibration for EPIC, its 10 spectral channels must be calibrated using other methods, such as inter-calibrating with sensors with on-board calibration hardware. VIIRS is a well-calibrated instrument with similar spectral channels as EPIC. Spectral band induced radiance differences between VIIRS and EPIC are mitigated using Spectral Band Adjustment Factor (SBAF). We will extend the previous calibrations from prior studies to include more recent data by ray-matching EPIC with VIIRS over all-sky tropical ocean (ATO) and deep convective cloud (DCC) conditions. In addition to ATO and DCC ray-matching, we will validate these results by utilizing DCC as invariant targets to monitor sensor degradation. DCC behave as solar diffusers in the tropics and when collectively analyzed can be used to monitor the degradation of the EPIC sensor. Improvement to our dynamic navigation adjustment algorithm, as well as exploring the view angle response of the EPIC CCD array, will be examined for their effectiveness and presented at the conference.

C O Haney↗
NASA NTRS2019

TPSAS-NF1676L-32323-DND

The GSICS VIS/NIR subgroup has several items to discuss and to provide a brief summary of the GSICS VIS/NIR activities. The first item is currently using Aqua-MODIS as the visible calibration reference. The plan is to migrate to NPP-VIIRS as the visible calibration reference. Then official source is the NOAA NPP VIIRS dataset, which is only archived with V0. However, NOAA has updated the calibration known as V2. The specifics will be discussed of how to scale the V0 visible radiances to the V2 standard. Second item is to outline a deep convective cloud (DCC) paper visible calibration paper with input from the various agencies using the GSICS DCC calibration approach. Also, to finalize the solar spectra selection. Lastly, to start the conversation with Rayleigh scattering calibration. Several slides will be compile using conclusions from GSICS web meetings, which are compiled from input across multiple agencies. Topics include improvements in spectral band adjustment factors, desert calibration, and homogenization of data records.

David Doelling↗
NASA NTRSDate not supplied

TPSAS-NF1676L-11363-DND

The key to the vicarious calibration of historical satellites relies on invariant targets, such as the moon, Dome C, and deserts. Deep convective clouds (DCC) also show promise of being a stable invariant or predictable target viewable by all satellites, since they behave as solar diffusers. However DCC have not been well characterized for calibration. Ten years of well-calibrated MODIS is now available. DCC can easily be identified using IR thresholds, where the IR calibration can be traced to the onboard blackbodies. The natural variability of DCC albedo will be analyzed geographically and seasonally, especially difference of convection initiated over land or ocean.

D R Doelling↗
NASA NTRS2020

Application of quasi-deep convective clouds method for MODIS and VIIRS TEB calibration assessments

A technique to use deep convective clouds (DCC) and quasi-DCC (qDCC) for the calibration assessment of the thermal emissive bands (TEB) on remote sensing instruments has proven feasible. The Terra and Aqua MODIS and S-NPP and NOAA-20 VIIRS TEB calibration uses a nonlinear algorithm whose nonlinear coefficients rely on on-orbit black body (BB) warm-up and cool-down (WUCD) activities for updates. However, the limited BB temperature range affects the calibration’s uncertainty. The DCC core, one of the coldest Earth scenes, is suitable for MODIS calibration assessments; more specifically, for the evaluation of the offset effect in its TEB quadratic calibration function. Moreover, nighttime qDCC measurements provide the advantage of removing solar reflectance effects, thus enhancing the assessment’s accuracy for the midwave infrared TEB. In this paper, the qDCC method is applied to the Terra MODIS and VIIRS TEB. Their stabilities are assessed using long-term DCC and qDCC trending measurements over the instruments’ entire missions. The measurements from bands with an approximately 11-μm wavelength are used to identify the DCC pixels. MODIS band31 (~ 11m) has demonstrated stable performance and accurate calibration for both instruments throughout their respective missions. MODIS band31 can therefore be used as a reference for the other TEB. Furthermore, it also allows for a Terra and Aqua MODIS TEB cross-comparison. The assessment results, along with the calibration uncertainty and Level 1B product impact modeling, can be quite helpful for calibration improvements.

MODIS↗
NASA NTRSDate not supplied

Overview of GSICS visible calibration methods.

Global Space-based Inter-Calibration System (GSICS) is an international collaborative effort initiated in 2005 by the World Meteorological Organization (WMO) and the Coordination Group for Meteorological Satellites (CGMS) to 1-monitor, 2-improve and 3-harmonize the quality of observations from operational weather and environmental satellites of the Global Observing System (GOS). GSICS aims at ensuring consistent accuracy among space-based observations worldwide for climate monitoring, weather forecasting, and environmental applications by 1-monitoring instrument performance, 2-operational inter-calibration of satellite instruments, 3-radiometrically scaling observations to absolute reference standards, 4-recalibration of archived datasets. Although many of the GSIC visible inter-calibration methods are based on medium pixel-level imagers such as MODIS, VIIRS, AVHRR, and geostationary sensors, the methods are applicable to high spatial resolution imagery such as Landsat. For sensor inter-calibration efforts, coincident ray-matched reflectance pairs are used to transfer the calibration from the reference to the target instrument. Spectral band adjustment factors (SBAF) are applied to account for any spectral band differences. For sensor stability monitoring, PICS, deep convective cloud (DCC) and polar ice Earth viewed targets are utilized. GSICS uses the moon for stability monitoring by using the GSICS Implementation of the USGS Robotic Lunar Observatory (ROLO) model (GIRO). GSICS is looking forward to the launch of CLARREO on the international space station (ISS) in 2023. The CLARREO hyperspectral reflective solar band (RSB) sensor will establish an absolute calibration reference in space, which will characterize invariant targets and will inter-calibrate concurrent sensors. Examples of these calibration methods will be presented at the workshop.

Visible calibration methods↗
NASA NTRS2021

Application of Quasi-Deep Convective Clouds Method for VIIRS and MODIS TEB Calibration Assessments

A technique that utilizes quasi-deep convective clouds (qDCC) for the calibration assessment of the thermal emissive bands (TEB) on remote sensing instruments has been proven viable. The Terra and Aqua MODIS and S-NPP and NOAA-20 VIIRS TEB calibration uses a nonlinear algorithm whose nonlinear coefficients rely on on-orbit blackbody (BB) warm-up and cooldown operations for updates. However, a limited BB temperature range affects the calibration’s accuracy particularly for cold scenes. The deep convective clouds (DCC) core, one of the coldest Earth scenes, is suitable for MODIS calibration assessments; more specifically, for the evaluation of the offset term’s effect in its TEB quadratic calibration function. Moreover, nighttime qDCC measurements provide with the advantage of removing solar reflectance effects during daytime, thus enhancing the assessment’s accuracy for the midwave infrared TEB. In this paper, this qDCC method is applied to the Terra MODIS and VIIRS TEB; and their stabilities are assessed using long-term qDCC trending measurements over the instruments’ missions. The measurements from bands with an 11-μm wavelength are used to identify the DCC pixels. The 11-μm bands, MODIS band 31 and VIIRS bands M15 and I5, are stable throughout the MODIS and VIIRS missions and have shown excellent calibration accuracy and noise performance. Hence, using these bands as references, a normalization method is employed to enhance the accuracy of the stability and consistency assessments. The S-NPP VIIRS TEB show stable trends over the instrument’s mission. The S-NPP-to-N20 VIIRS comparison shows their TEB measurements are consistent over qDCC. The Terra MODIS TEB also show stable performance – except for bands 27, 29, and 30. Terra MODIS band 30 shows a large downward trend throughout the mission, while bands 27 and 29 show slight, upward drifts. Lastly, a calibration correction using qDCC assessments is discussed and intended to be used in a future calibration algorithm collection.

MODIS↗
NASA NTRS2021

Normalization Method and Application for MODIS TEB Assessments using Earth Scene Measurements

Selected Earth targets are commonly used for satellite sensor calibration assessments (e.g. sensor stability and inter-comparisons). Moreover, typical scenes used for the calibration assessment of the thermal emissive bands (TEBs) includeDome Concordia (Dome-C), ocean, desert, and deep convective clouds (DCC). Reference data used for these calibration assessments can come from another band, another instrument, or ground measurements. The Dome-C site, covered with uniformly-distributed permanent snow, is normally used for the assessment of the TEBsat cold temperatures. Furthermore, ocean and desert measurements prove useful for scenes with higher temperatures. The DCC, one of the most consistent and coldest targets, can be used for the TEBs calibration and product stability assessments. MODIS band 31 (~ 11 m) can be used as a reference for these scenes. However, measurements over these scenes have seasonal variations, and the DCC brightness temperatures (BTs) have asymmetrical distributions. These features can introduce additional uncertainty to the stability assessments. A normalization method is applied by using an empirical model to derive reference-dependent BTs. Using the developed empirical model, measurements can be normalized to a reference BT in order to enhance the calibration assessment’s accuracy. This method is evaluated using all four scene types (i.e. ocean, desert, snow (Dome-C), and DCC) and applied to all the Terra and Aqua MODIS TEBs. Stability assessments over the instruments’ entire data records are presented and discussed. The technique can be applied in future efforts to support MODIS TEBs calibration assessments.

MODIS TEB↗
NASA NTRS2020

Assessment of MODIS and VIIRS Calibration Consistency for Reflective Solar Bands Using Vicarious Approaches

The Moderate-Resolution Imaging Spectroradiometer (MODIS) is the key instrument of the NASA’s Earth Observing System (EOS) Terra and Aqua missions, launched in December 1999 and May 2002, respectively. The Visible Infrared Imaging Radiometer Suite (VIIRS) expands the MODIS legacy, launched onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite in October 2011 and NOAA20 satellite in November 2017, respectively. The MODIS and VIIRS sensors have a similar design with spectrally matched reflective solar spectral bands (RSB). Their on-board calibration components include a solar diffuser and a solar diffuser stability monitor for RSB, a V-grooved blackbody for the thermal emissive bands (TEB), and a space view as a background reference. This study evaluates the calibration consistency of the Terra and Aqua MODIS RSB based on the current Collection 6.1 L1B data products generated by the NASA MODAPS, which have used consistent calibration coefficient look up tables (LUT) for the entire data-record. In the case of SNPP and NOAA20 VIIRS, the latest L1B data produced by NASA Land SIPS are used. Several independent vicarious approaches are used to examine the stability and consistency of the at-sensor reflectance among MODIS and VIIRS instruments. Vicarious approaches include observations from simultaneous nadir overpasses (SNO), the Libya-4 desert and Dome C snow sites, as well as deep convective clouds (DCC). Impact of existing band spectral difference on the reflectance is corrected using hyperspectral observations provided by Europe Space Agency’s SCIAMACHY sensor. Results of this study provide comprehensive assessments of calibration performance, radiometric agreement and associated uncertainties.

MODIS↗
NASA NTRS2020

Long Term Stability Monitoring of Aqua MODIS Thermal Emissive Bands through Radiative Transfer Modeling

Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua has been in operation providing continuous global observations for science research and applications since 2002. The long-term stability of thermal emissive bands (TEBs) of Aqua MODIS was monitored through inter-comparisons with measurements by hyperspectral infrared sensors, such as AIRS on Aqua and IASI on MetOp satellite, or through long term vicarious monitoring over cold targets, such as Dome- C and deep convective clouds (DCC). In this paper, a radiative transfer modeling-based simulation model using Community Radiative Transfer Model (CRTM) is developed to perform the long-term monitoring of the stability of TEBs of Aqua MODIS. CRTM is a fast-radiative transfer model for calculations of radiances for satellite infrared radiometers and is able to output infrared radiance and brightness temperature at spectral bands of MODIS. Long term European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis data, such as temperature and humidity profiles, are used as inputs to the CRTM simulation. By confining the area of interest to be over low to middle latitude ocean, the long-term stabilities of selected Aqua MODIS TEBs are monitored through Observation–Background (O-B) brightness temperature (BT) bias between MODIS measurements and BT retrieval from CRTM simulation. The consistency and relative stability between Aqua MODIS and ECMWF reanalysis data for surface channels of MODIS are evaluated. In addition, the radiative transfer modeling with CRTM enables us to evaluate the impacts of long term variation of global CO2 distribution on the O-B BT biases for CO2 channels of Aqua MODIS through comparison of simulations with constant or long term variable CO2 as inputs. The O-B analysis with RTM show that Aqua MODIS surface channels are all radiometrically stable with yearly BT bias drift less than 0.004K/year for B20, B22, B23 and ~0.01K/year for B31 and B32. The CO2 absorption channels of Aqua MODIS, e.g. B33-B36, are stable with BT bias drift < 0.005K/year.

MODIS↗
NASA NTRSDate not supplied

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

The 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 and Aqua CERES instrument observed radiances, rely on coincident measurements from the onboard MODIS imagers to determine cloud properties that are used in the angular distribution model scene selection required to convert the CERES observed radiances into flux values. Once the Terra and Aqua orbits start drifting outside of their 15-minute window, the CERES project will rely solely on the NOAA-20 CERES observations. A seamless transition of fluxes and clouds can only occur if the analogous MODIS and VIIRS channels are properly inter-calibrated. The visible band (0.65 µm) in MODIS (band 1) and VIIRS (M5 or I1) is critical for retrieving the cloud mask and optical depth. The spectral response functions (SRF) of these bands differ noticeably and will require scene dependent spectral band adjustment factors (SBAF) for proper radiometric scaling between them. Fortunately, the VIIRS I1 and M5 bands are calibrated using the same solar diffuser as a reference, which implies that band reflectance differences must be due to the spectral disparity. The coincident I1 and M5 TOA reflectance measurements provide the optimal opportunity to validate SBAFs over many surface and cloud conditions. The CERES project maintains SCIAMACHY, GOME-2, Hyperion, and radiative transfer model-based scene-stratified hyper-spectral reflectance measurements that can be convolved with sensor pair SRFs to compute the corresponding SBAF. This study will evaluate the SCIAMACHY, GOME-2, Hyperion, and RTM based SBAFs over tropical ocean targets used in SNO inter-calibration of MODIS and VIIRS, including clear-sky ocean, deep convective clouds (DCC), and liquid cloud targets in terms of their applicability to absolute intercomparison of visible imagers. The large SCIAMACHY and GOME-2 footprints and the lack of Hyperion cloudy scenes will impact the resulting SBAFs and necessitates the need for future CLARREO hyper-spectral reflectances to decrease SBAF uncertainties Preliminary results indicate that the SCIAMACHY and GOME-2 based SBAFs for the VIIRS I1 and M5 band pairs may differ by 1.5% for some ATO scene types. Because most of the modern GEOs visible band SRFs encompass the VIIRS I1 band SRF, these evaluations are critical to ensure that the MODIS, VIIRS, and GEO clouds and fluxes are consistent. SBAFs for Libya-4, Dome-C and other Earth invariant target will also be evaluated.

D. R. Doelling↗
NASA NTRSDate not supplied

The Impact of Pixel Size on the Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, to estimate the broadband fluxes between CERES observations. This requires stable imager visible channel calibration, which the CERES project verifies by utilizing deep convective clouds (DCC) as an invariant Earth target. GSICS, which is an international collaboration, is also evaluating the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the Aqua-MODIS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical DCC-identified pixel-level reflectances, which are histogrammed to find the mode reflectance of the probability density function (PDF). The imager stability is monitored by tracking the monthly DCC PDF mode reflectance over time. Radiometric scaling is accomplished by ratioing the GEO and VIIRS DCC mode reflectance values. The PDF shape and mode dependency on sensor pixel resolution, which varies among sensors, is unknown. This study will characterize the impact of pixel resolution on the DCC PDFs by aggregating Landsat 30-m pixel reflectances into various coarser pixel resolutions ranging from 100-m to 4-km, and comparing the corresponding PDF statistics. This analysis will assist in improving the uncertainty in a DCC-based intercalibration between instruments with different pixel resolutions.

Conor Haney↗
NASA NTRSDate not supplied

The Impact of Pixel Size on the Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, are used to estimate the broadband fluxes between CERES observations. This requires stable and consistent cross-platform imager visible channel calibration. The CERES project utilizes deep convective clouds (DCC) as an invariant Earth target to both monitor the stability of sensors and for radiometric scaling. GSICS, an international collaboration, is also evaluating and implementing the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the AquaMODIS or the NOAA-20 VIIRS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical D CC-identified pixel-level reflectances, which are aggregated as probability density functions (PDF). By assuming the monthly PDF shape is otherwise consistent in time excepting shifts in reflectance caused by changes in the sensor calibration, the imager stability is monitored. Radiometric scaling is accomplished by ratioing the sensor pair DCC PDF reflectance values. The success of the DCC methodology relies on consistent PDF distributions. The goal of this study is to determine the impact of pixel resolution on the DCC reflectance distribution. Single SNPP-VIIRS 750-m and Landsat 8 OLI 30-m granules are aggregated to degrade the pixel resolution from the native level. The DCC pixels are identified using a BT threshold. Most of the brightest DCC pixels are also the coldest, although there are exceptions. It was found that increasing the BT threshold exponentially increased the number of darker pixels. The pixel resolution did not seem to impact the DCC reflectance PDF distribution for pixel resolutions less than 3 km, which suggests that imagers of varying pixel resolutions may be radiometrically scaled to each other using DCC targets.

DCC↗