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NASA NTRS2018

Calibration of the DSCOVR EPIC Visible and NIR Channels using MODIS Terra and Aqua Data and EPIC Lunar Observations

The unique position of the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) at the Lagrange 1 point makes an important addition to the data from currently operating low Earth orbit observing instruments. EPIC instrument does not have an onboard calibration facility. One approach to its calibration is to compare EPIC observations to the measurements from polar-orbiting radiometers. Moderate Resolution Imaging Spectroradiometer (MODIS) is a natural choice for such comparison due to its well-established calibration record and wide use in remote sensing. We use MODIS Aqua and Terra L1B 1km reflectances to infer calibration coefficients for four EPIC visible and NIR channels: 443, 551, 680 and 780 nm. MODIS and EPIC measurements made between June 2015 and 2016 are employed for comparison. We first identify favorable MODIS pixels with scattering angle matching temporarily collocated EPIC observations. Each EPIC pixel is then spatially collocated to a subset of the favorable MODIS pixels within 25 km radius. Standard deviation of the selected MODIS pixels as well as of the adjacent EPIC pixels is used to find the most homogeneous scenes. These scenes are then used to determine calibration coefficients using a linear regression between EPIC counts/sec and reflectances in the close MODIS spectral channels. We present thus inferred EPIC calibration coefficients and discuss sources of uncertainties. The lunar EPIC observations are used to calibrate EPIC O2 absorbing channels (688 and 764 nm), assuming that there is a small difference between moon reflectances separated by approx.10 nm in wavelength provided the calibration factors of the red (680 nm) and near-IR (780 nm) are known from comparison between EPIC and MODIS.

Geogdzhayev, Igor V.↗
NASA NTRS2018

Optimal Estimation-Based Algorithm to Retrieve Aerosol Optical Properties for GEMS Measurements Over Asia

The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled to be in orbit in 2019 onboard the GEO-KOMPSAT 2B satellite and will continuously monitor air quality over Asia. The GEMS will make measurements in the UV spectrum (300-500 nm) with 0.6 nm resolution. In this study, an algorithm is developed to retrieve aerosol optical properties from UV-visible measurements for the future satellite instrument and is tested using 3 years of existing OMI L1B data. This algorithm provides aerosol optical depth (AOD), single scattering albedo (SSA) and aerosol layer height (ALH) using an optimized estimation method. The retrieved AOD shows good correlation with Aerosol Robotic Network (AERONET) AOD with correlation coefficients of 0.83, 0.73 and 0.80 for heavy-absorbing fine (HAF) particles, dust and non-absorbing (NA) particles, respectively. However, regression tests indicate underestimation and overestimation of HAF and NA AOD, respectively. In comparison with AOD from the OMI/Aura Near-UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13 km x 24 km V003 (OMAERUV) algorithm, the retrieved AOD has a correlation coefficient of 0.86 and linear regression equation, AOD(sub GEMS) = 1.18AOD(sub OMAERUV) + 0.09. An uncertainty test based on a reference method, which estimates retrieval error by applying the algorithm to simulated radiance data, revealed that assumptions in the spectral dependency of aerosol absorptivity in the UV cause significant errors in aerosol property retrieval, particularly the SSA retrieval. Consequently, retrieved SSAs did not show good correlation with AERONET values. The ALH results were qualitatively compared with the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) products and were found to be well correlated for highly absorbing aerosols. The difference between the attenuated-backscatter-weighted height from CALIOP and retrieved ALH were mostly closed to zero when the retrieved AOD is higher than 0.8 and SSA is lower than 0.93. Although retrieval accuracy was not significantly improved, the simultaneous consistent retrieval of AOD, SSA and ALH alone demonstrates the value of this stand-alone algorithm, given their nature for error using other methods. The use of these properties as input parameters for the air mass factor calculation is expected to improve the retrieval of other trace gases over Asia.

Geostationary Environment Monitoring Spectrometer ↗
NASA NTRS2018

GEONEX: Challenges in Producing MODIS-Like Land Products from a New Generation of Geostationary Sensors

The new generation geostationary (GEO) remote sensors (GOES-R ABI, Himawari AHI, and FY4 AGRI) provide high frequency (5-15 minute) observations spatially/spectrally similar to MODIS/VIIRS for land monitoring. These new features of GEO satellite sensors make producing MODIS like land products for terrestrial monitoring possible. The NASA Earth Exchange (NEX) team developed the GEONEX pipeline that is containerized, deployable on NASA Pleiades supercomputer as well as public cloud platforms (e.g. AWS). The processing pipeline is designed to take Himawari Standard Data (HSD) and GOES-16 L1b to generate surface reflectance (SR) and other high-level land remote sensing products. In order to produce low-Earth-orbiting (LEO) remote sensing compatible land products, inter-comparison between Himawari AHI and MODIS Terra/Aqua has been conducted in this research work. Comparisons of TOA reflectance and surface reflectance between AHI and Terra/Aqua are presented. Ray-Matching method was used to locate the co-located pixels, where GEO and LEO sensors look at the land target with similar Viewing Zenith Angle (VZA) and Viewing Azimuth Angle (VAA) simultaneously. Here, we address challenges associated with the selection of qualified pixels of similar solar illumination condition and atmosphere path. We used strict criterion to constrain the pixel selection: the time difference between GEO and LEO observations is less than +-2.5 mins, the cosine of VZA difference is less than 1%, and the VAA difference is less than 10 deg. We also discuss the strong radiometric consistency that the new generation GEO sensors along with the popular LEO sensors would benefit the environmental remote sensing community.

Li, Shuang↗
NASA NTRS2018

Land Surface Reflectances from Geostationary Sensors

GEONEX is a processing pipeline that produces a suite of satellite land surface products using data streams from the latest geostationary (GEO) sensors including the GOES016/ABI and the Himawari-8/AHI. The suite, created collaboratively by scientists from NASA and NOAA, includes top-of-atmosphere (TOA) reflectances, land surface reflectances (LSRs), vegetation indices, LAI/fPAR, and other downstream products. As a key component of the GEONEX product processing, we have adapted the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce LSRs from the TOA data. Because the algorithm depends on building "stacks" of images, we first run internal geo-registration checks to ensure geo-spatial accuracy and consistency of the input (L1B) data before transferring them from the geostationary projection into a tile system in geographic grids. Scan-time is inferred from metadata and applied to calculate the sun-sensor angles for each grid cell. The MAIAC algorithm is run to detect clouds/shadows, estimate aerosol optical thickness (AOT), perform atmospheric corrections, and generate LSRs. We have processed 18-months (from 2016/04 onward) of AHI data over East Asia and Oceania at a 10-minute time step and 10-months (from 2018/01 onward) of ABI data over North and South Americas at a 15-minute time step. As a verification measure, we compare the GEONEX (AHI/ABI) surface reflectances with the standard MODIS products (MOD09GA) and the MODIS MAIAC products over pixels that have similar sun-view geometries. The results indicate general linear relationships between GEONEX and corresponding MODIS LSRs. In particular, the RMSEs between GEONEX and MOD09 data are comparable to those between MOD09 and MODIS MAIAC products, suggesting that the uncertainties of GEONEX LSRs fall into an acceptable range. However, direct comparisons of LSRs over pixels with different sun-view angles are not as straightforward and require more modeling efforts to correct the directional effects. Evaluation of such angular influences on the downstream products (e.g., vegetation indices) is also under investigation.

Geostationary satellite; Remote Sensing; Atmospher↗
NASA NTRS2018

Air Quality Satellite Monitoring by TROPOMI on Sentinel-5P

The recently launched Sentinel satellite mission, the Sentinel-5 Precursor (Sentinel-5P), is one of the European Space Agency's (ESA) new mission family – Sentinels. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), a nadir-viewing 108⁰ field-of-view push-broom grating hyperspectral spectrometer, covering the wavelengths of ultraviolet-visible (270 nm - 495 nm), near infrared (675 nm - 775 nm), and shortwave infrared (2305 nm - 2385 nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels, and is providing measurements of atmospheric chemistry, aerosols, and clouds at high spatial, temporal, and spectral resolution. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) supports over a thousand data collections in the focus areas of Atmospheric Composition, Water & Energy Cycles, and Climate Variability. Sentinel-5P TROPOMI Level-1B (L1B) and Level-2 (L2) products are curated at the GES DISC. Sentinel-5P data are provided by the European Union and the European Space Agency (ESA) through an agreement between ESA and NASA. Through its convenient and enhanced tools/services, such as OPeNDAP and L2 Subsetting, GES DISC offers the air quality remote sensing user community facile solutions for using complex Earth science data and applications. This presentation will demonstrate up-to-date TROPOMI products including EarthView (EV) radiance, solar irradiance, Aerosol Index, Carbon Monoxide, Total column Ozone, Nitrogen Dioxide, and cloud, as well as easy ways to access, visualize and subset TROPOMI data.

TROPOMI↗
NASA NTRS2018

Sentinel-5P/TROPOMI and S-NPP/OMPS Data Support at GES DISC

The TROPspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (Sentinel-5P) is the first of the Atmospheric Composition Sentinels by the European Space Agency (ESA) that provides measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions. The early afternoon orbit of Sentinel-5P mission provides a strong synergy with the U.S. Suomi National Polar-orbiting Partnership (S-NPP) satellite, especially in that the S-NPP Ozone Monitoring and Profiling Suite (OMPS) facilitates high vertically resolved stratospheric and lower mesospheric ozone profiles. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) supports over a thousand data collections in the Focus Areas of Atmospheric Composition, Water & Energy Cycles, and Climate Variability and it is the Distributed Active Archive Center (DAAC) that is curating both offline Sentinel-5P TROPOMI and S-NPP OMPS Level-1B (L1B) and Level-2 (L2) products. Through its convenient and enhanced tools/services such as OPeNDAP and L2 Subsetting, GES DISC offers air quality remote sensing user communities facile solutions for complex Earth science data and applications. This presentation will demonstrate TROPOMI and OMPS products including earthview radiance, solar irradiance, and currently available L2 datasets, as well as easy ways to access, visualize and subset data. The implementation of the End User License Agreement (EULA) between NASA GES DISC and all data users accessing data at GES DISC will be emphasized as well.

TROPOMI↗
NASA NTRS2018

Evaluating the Calibration of Aqua MODIS Bands 33, 35, and 36 During Blackbody Warm-Up Cool-Down Events

Aqua MODIS is the second MODIS instrument of NASA's Earth Observation System and has operated for over sixteen years since its launch in 2002. MODIS has sixteen thermal emissive bands (TEBs) located on two separate cold focal plane assemblies (CFPA). The TEBs are calibrated every scan using observations of an onboard blackbody (BB) and a space view port. Low saturation temperatures (Tsat) of Aqua MODIS bands 33, 35, and 36 cause these bands to saturate when the BB temperature is higher than their Tsat values during a BB warm-up cool-down (WUCD) cycle, therefore impacting the ability to perform nominal calibration. In addition, starting from around 2006, the CFPA temperature showed gradual variation from its nominally-controlled operating temperature due to a loss of its radiative cooler margin and the magnitude of its fluctuation reaching a maximum in 2013. The MODIS Characterization Support Team currently uses a correction that is dependent on the CFPA temperature to provide a gain estimate for the saturated scans during the BB WUCD. This gain estimation has been implemented in the Aqua MODIS Collection 6 (C6) and C6.1 L1B products. This paper evaluates the quality of the calibrated radiance of Aqua MODIS bands 33, 35, and 36 using simultaneous nadir observations from the Atmospheric Infrared Sounder (AIRS), which is also onboard the Aqua satellite. Our analysis results show that the differences between AIRS and Aqua MODIS can be controlled well within the fluctuation range compared to the periods when the BB signals for these bands are not saturated.

Li, Yonghong↗
NASA NTRS2019

MODIS Reflective Solar Bands On-Orbit Calibration and Performance

The design of the MODIS instrument was driven by the scientific community's desire to have near-daily global coverage at moderate resolution (1 km) with a comprehensive spectral coverage from visible to long-wave infrared wavelengths. Since their launches in 1999 and 2002, respectively, the Terra and Aqua MODIS instruments have made continuous global observations and generated numerous data products to help users worldwide with their studies of the Earth's system and its short- and long-term changes. The 20 reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 m collect data at three nadir spatial resolutions: 250 m, 500 m, and 1 km. The solar diffuser (SD) coupled with the solar diffuser stability monitor (SDSM) provide a reflectance-based calibration on-orbit. In addition, lunar observations and response trends from pseudo-invariant desert sites are used to characterize the response versus scan- angle changes on-orbit. This paper provides a brief overview of MODIS RSB calibration algorithms, as implemented in the latest Level 1B version 6.1, operational activities, on-orbit performance, remaining challenges and potential improvements. Results from the SD and SDSM measurements show a wavelength and mirror side dependent degradation in RSB responses, with the largest degradation at the shortest wavelengths, particularly for Terra MODIS. Aqua MODIS has experienced far less degradation of its optics and on-board calibrators compared to Terra MODIS, resulting in an overall better performance. With the exception of Aqua band 6, there have been no new noisy or inoperable detectors in the RSB of either instrument during post-launch operations. As the instruments age and continue to endure the space environment, the detectors and optical systems degrade. The challenges associated with incorporating these on-orbit changes to ensure a production of high-quality calibrated L1B data products are also discussed in this paper.

solar diffuser stability monitor↗
NASA NTRS2017

Hyperspectral Sounder Performance for Cold Scenes

We investigate the use of 200K scenes as a valuable “stress test” for the evaluation of the calibration of AIRS and CrIS. Under these conditions both instruments show artifacts much larger than the nominal stated radiometric accuracy of about 0.1-0.2 K. Except for the AIRS shortwave trend, both instruments clearly perform well at the 1 K level even for these extremely low scene temperatures. Unfortunately, changes in extremes, in this case cold extremes, are of great interest to the evaluation of climate change effects, such as changes in the height of the tropopause or the frequency of severe storms. The evaluation of the AIRS performance at extremely low scene temperatures has been key to identifying the need for updating the polarization coefficients in the L1B software Version 7. These changes are expected to eliminate a large fraction of the observed AIRS artifacts. The CrIS instrument teams is also working on refining the calibration.

Manning, Evan M.↗
NASA NTRS2018

Terra and Aqua MODIS Intercomparison Using LEO-GEO Double Difference Method

The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites havesuccessfully operated since their launch in 1999 and in 2002, providing more than 18 and 16 years ofcontinuous global observations, respectively. The inter-comparison between the two MODIS instruments can bevery supportive for the instrument calibration and uncertainty assessment. Aqua and Terra MODIS have almostidentical relative spectral response, spatial resolution, and dynamic range for each band. Therefore, a sitedependent correction for a sensor spectral band pair is not necessary for their comparison. However, Terra is inthe morning orbit with an equator crossing time of 10:30 am, and Aqua is in the afternoon orbit with equatorcrossing time of 1:30 pm. Consequently, there is a dearth of simultaneous nadir overpasses (SNOs)between the two satellites. Major challenges in cross-sensor comparison of instruments on different satellitesinclude differences in observation time, solar angle, and view angle over selected pseudo-invariant sites.In this work, the inter-comparisons of thermal emissive bands are performed over a pseudo-invariant target,using the observations from a sensor onboard a geostationary satellite as a bridge. Himawari8 was launched onOctober 7, 2014. The Advanced Himawari Imager (AHI) onboard Himawari8 can be used as a reference tobridge the comparison between Terra and Aqua MODIS. AHI has 16 channels; with spatial resolutions from 0.5km to 2 km at nadir and produces a full disk observations every 10 minutes. The band spectral coveragematchup, comparable spatial resolution and near-simultaneous observation between MODIS and AHI providefeasibility to implement a double difference method. This comparison method minimizes the impact of thedifference in observation time and solar angle. The comparison results will be used as an assessment for MODISinstrument calibration and will be helpful for future enhancement of the L1B product.

Himawari8↗
NASA NTRS2019

Water Storage Trends in High Mountain Asia

Changes in terrestrial water storage (TWS) in High Mountain Asia (HMA) could have major societal impacts, as the region’s large reservoirs of glaciers, snow, and groundwater provide a freshwater source to more than one billion people. We seek to quantify and close the budget of secular changes in TWS over the span of the GRACE satellite mission (2003–2016). To assess the TWS trend budget we consider a new high-resolution mass trend product determined directly from GRACE L1B data, glacier mass balance derived from Digital Elevation Models (DEMs), groundwater variability determined from confined and unconfined well observations, and terrestrial water budget estimates from a suite of land surface model simulations with the NASA Land Information System (LIS). This effort is successful at closing the aggregated TWS trend budget over the entire HMA region, the glaciated portion of HMA, and the Indus and Ganges basins, where the full-region trends are primarily due to the glacier mass balance and groundwater signals. Additionally, we investigate the closure of TWS trends at individual 1-arc-degree mascons (area ≈12,000 km2); a significant improvement in spatial resolution over previous analyses of GRACE-derived trends. This mascon-level analysis reveals locations where the TWS trends are well-explained by the independent datasets, as well as regions where they are not; identifying specific geographic areas where additional data and model improvements are needed. The accurate characterization of total TWS trends and its components presented here is critical to understanding the complex dynamics of the region, and is a necessary step toward projecting future water mass changes in HMA.

Bryant D Loomis↗
NASA NTRS2019

Generating Accurate and Consistent Top-Of-Atmosphere Reflectance Products from the New Generation Geostationary Satellite Sensors

GeoNEX is a collaborative project by scientists from NASA, NOAA, JAXA, and other organizations around the world with the purpose of generating a suite of Earth-monitoring products using data streams from the latest geostationary (GEO) sensors including the GOES-16/17 ABI and the Himawari-8/9 AHI. An accurate and consistent top-of-atmosphere (TOA) reflectance product, in particular the bidirectional reflectance factor (BRF), is the starting point in the scientific processing chain. We describe the main considerations and corresponding algorithms in generating the GeoNEX TOA BRF product. First, a special advantage of geostationary data streams is their high temporal resolution (~10 minutes per full-disk scan), providing a key source of information for many downstream products. To fully utilize this high temporal frequency demands a high georegistration accuracy for every acquired image. Our analysis shows that there can be substantial georegistration uncertainties in both GOES and Himawari L1b data which we addressed by implementing a phase-based correction algorithm to remove residual errors. Second, geostationary sensors have distinct illumination-view geometry features in that the solar angle changes for every pixel. Therefore, to accurately derive a BRF requires a solar position algorithm and the estimation of the pixel-wise acquisition time within an uncertainty of 10 seconds. Third, we discuss the measures we adopted to check and correct residual radiometric calibration issues of individual sensors to enable time-series analysis as well as the cross calibration between different satellite sensors (including those from low-Earth orbit). Finally, we also explain the rationale for the choice of the global grid/tile system of the GeoNEX TOA BRF product.

Wang, Weile↗
NASA NTRSDate not supplied

Monitoring the Calibration of the DSCOVR EPIC Instrument’s Visible Cchannels Using MODIS and VIIRS as a Reference

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. Due to EPIC not having any on-board calibration systems, the ten spectral channels of EPIC must be inter-calibrated using vicarious on-orbit methods, such as ray-matching with well-calibrated low Earth orbiting satellites like the Aqua-MODIS and SNPP-VIIRS radiometers. The recently released EPIC version 3 L1B data has greatly enhanced the residual navigation errors found in prior versions, thereby decreasing the calibration uncertainty in the aforementioned ray-matching calibration techniques. The automated navigation correction used by these ray-matching methods for further improving the EPIC geolocation will be compared with a new navigation correction method utilizing optical flow between the EPIC and MODIS/VIIRS images. The DSCOVR satellite went into safe mode on June 27, 2019 due to an anomaly with the satellite’s attitude control system, but operations recommenced on March 2, 2020. The calibration of the EPIC instrument before it went into safe mode and after it resumed will be analyzed in order to investigate any potential calibration shifts or discontinuities caused by the spacecraft anomaly.

Conor Haney↗
NASA NTRSDate not supplied

Radiometric Assessment of the First Three Years of the NOAA-20 VIIRS Reflective Solar Bands Calibration

NASA’s Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg Ed4.1 product utilizes geostationary (GEO) satellite measured radiances and retrieved cloud properties to account for the regional diurnal fluctuations in the Earth’s radiant broadband fluxes for times between the CERES measurements gathered from the Aqua (1:30 PM) and Terra (10:30 AM) sun-synchronous satellites. In CERES Edition 4 products, a global uniformity in the cloud properties and computed surface fluxes across the GEO satellite domains is maintained by scaling the radiance observations from more than twenty GEO visible imagers in the CERES record to a common radiometric reference scale, i.e., Aqua-MODIS. With the new-generation GEO (Himawari-8/9 and GOES-16/17) imagers having multiple reflective solar bands (RSB) that are spectrally similar to those of VIIRS, the CERES Imager and Geostationary Calibration Group (IGCG) is preparing to use NOAA-20 VIIRS as the reference imager for maintaining the radiometric uniformity across the GEO imager constellation. Given the recent Aqua satellite anomaly, this transition may happen sooner than the projected date of Aqua’s de-orbit. This paper presents an independent performance evaluation of the first three years of the NOAA-20 VIIRS RSB calibration in the NASA VIIRS Land Science Investigator-led Processing System (Land SIPS) L1b Collection 2 dataset. The temporal radiometric stability is assessed using multiple invariant Earth targets, including tropical deep convective clouds and the Saharan desert. The invariant target anisotropic reflectance at the top of atmosphere was modeled using five years of stable satellite observations acquired from the previous VIIRS instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The anisotropic corrections are essential for detecting temporal trends with a high statistical confidence. In addition, the radiometric consistency between the RSB of the two VIIRS instruments will be evaluated.

Rajendra Bhatt↗
NASA NTRSDate not supplied

Radiometric Assessment of the First Three Years of the NOAA-20 VIIRS Reflective Solar Bands Calibration

NASA’s Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg Ed4.1 product utilizes geostationary (GEO) satellite measured radiances and retrieved cloud properties to account for the regional diurnal fluctuations in the Earth’s radiant broadband fluxes for times between the CERES measurements gathered from the Aqua (1:30 PM) and Terra (10:30 AM) sun-synchronous satellites. In CERES Edition 4 products, a global uniformity in the cloud properties and computed surface fluxes across the GEO satellite domains is maintained by scaling the radiance observations from more than twenty GEO visible imagers in the CERES record to a common radiometric reference scale, i.e., Aqua-MODIS. With the new-generation GEO (Himawari-8/9 and GOES-16/17) imagers having multiple reflective solar bands (RSB) that are spectrally similar to those of VIIRS, the CERES Imager and Geostationary Calibration Group (IGCG) is preparing to use NOAA-20 VIIRS as the reference imager for maintaining the radiometric uniformity across the GEO imager constellation. Given the recent Aqua satellite anomaly, this transition may happen sooner than the projected date of Aqua’s de-orbit. This paper presents an independent performance evaluation of the first three years of the NOAA-20 VIIRS RSB calibration in the NASA VIIRS Land Science Investigator-led Processing System (Land SIPS) L1b Collection 2 dataset. The temporal radiometric stability is assessed using multiple invariant Earth targets, including tropical deep convective clouds and the Saharan desert. The invariant target anisotropic reflectance at the top of the atmosphere was modeled using five years of stable satellite observations acquired from the previous VIIRS instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The anisotropic corrections are essential for detecting temporal trends with high statistical confidence. In addition, the radiometric consistency between the RSB of the two VIIRS instruments will be evaluated.

Rajendra Bhatt↗
NASA NTRS2020

Derivation of Shortwave Radiometric Adjustments for SNPP and NOAA-20 VIIRS for the NASA MODIS-VIIRS Continuity Cloud Products

Climate studies, including trend detection and other time series analyses, necessarily require stable, well-characterized and long-term data records. For satellite-based geophysical retrieval datasets, such data records often involve merging the observational records of multiple similar, though not identical, instruments. The National Aeronautics and Space Administration (NASA)cloud mask(CLDMSK) and cloud-top and optical properties(CLDPROP) products are designed to bridge the observational records of the Moderate-resolution Imaging Spectroradiometer (MODIS) onboard NASA’s Aqua satellite and the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the joint NASA/National Oceanic and Atmospheric Administration(NOAA)Suomi National Polar-orbiting Partnership (SNPP)satellite and NOAA’s new generation of operational polar-orbiting weather platforms(NOAA-20+).Early implementations of the CLDPROP algorithms on Aqua MODIS and SNPP VIIRS suffered from large intersensor biases in cloud optical properties that were traced back to relative radiometric inconsistency in analogous shortwave channels on both imagers, with VIIRS generally observing brighter top-of-atmosphere spectral reflectance than MODIS (e.g., up to 5%brighter in the 0.67μm channel). Radiometric adjustment factors for the SNPP and NOAA-20 VIIRS shortwave channels used in the cloud optical property retrievals are derived from an extensive analysis of the overlapping observational records with Aqua MODIS, specifically for homogenous maritime liquid water cloud scenes for which the viewing/solar geometry of MODIS and VIIRS match. Application of these adjustment factors to the VIIRS L1B prior to ingestion into the CLDMSK and CLDPROP algorithms yields improved intersensor agreement, particularly for cloud optical properties

relative radiometry↗
NASA NTRS2019

Evaluation of NOAA-20 VIIRS reflective solar bands calibration performance using vicarious approaches

The newly launched polar-orbiting NOAA-20 satellite is the follow-on mission to the SNPP (Suomi National Polar-orbiting Partnership) satellite. Both satellites are in an afternoon orbit with a close equatorial cross time. The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key sensor onboard NOAA-20 and SNPP. The two VIIRS sensors are within the same engineering design with nearly identical spectral ranges. Its on-board calibration components include a solar diffuser and a solar diffuser stability monitor for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view as background reference. This study evaluates calibration performance of the NOAA-20 VIIRS RSB using the first internally released L1B data product by NASA Land SIPS, which has consistent calibration coefficient look up tables (LUT) throughout the entire mission. Several independent vicarious approaches are used to examine the stability and consistence of reflectance. The first approach is based on a double difference method by comparison with SNPP VIIRS using observations from simultaneous nadir overpasses (SNO) with Aqua MODIS. The second is based on the reflectance trends from 16-day repeatable orbits obtained over the widely used Liby-4 desert site so each data point has the nearly same viewing angles relative to the site. The third approach is to use the frequent overpasses over the Dome C snow site. Results of this study provide NOAA-20 VIIRS post-launch calibration stability performance and radiometric agreement with SNPP for the first 18 months of mission.

VIIRS↗
NASA NTRS2019

Terra MODIS: 20 years of on-orbit calibration and performance

For nearly 20 years, Terra MODIS observations have generated a broad range of data products, enabling the remote sensing community and users worldwide for their studies of many key geophysical parameters of the Earth’s system. MODIS collects data in 36 spectral bands, covering wavelengths from 0.41 to 14.4 μm, that are calibrated by a set of on-board calibrators (OBC). Also contributed to sensor on-orbit calibration and characterization are near monthly-scheduled lunar observations and long-term trends of sensor responses over select ground targets. The quality of MODIS data products relies strongly on the dedicated efforts to the operate instrument, derive and update calibration parameters, and improve calibration strategies and algorithms in order to address on-orbit changes of sensor characteristics and its OBC functions. This paper provides an overview of Terra MODIS on-orbit operation and calibration activities over the last 20 years, including changes made to extend and preserve instrument and OBC functions and their implementation strategies. It illustrates sensor on-orbit performance using data from its OBC, lunar observations, and select ground targets and discusses major changes in sensor characteristics and corrections applied to the L1B algorithms or updates of calibration look-up tables (LUTs). Also described in this paper are lessons learned from Terra MODIS and future efforts to further extend its long-term data records.

Terra↗