This PDF file contains the front matter associated with SPIE Proceedings Volume 12685, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

GLIMR is a NASA Earth Venture Instrument (EVI) project led by Principal Investigator Dr. Joseph Salisbury of the University of New Hampshire (UNH). The GLIMR investigation uses a Raytheon-built hyperspectral imaging radiometer in geostationary orbit to enable a new class of ocean color science data collection. As NASA stated in the EVI project selection announcement: “GLIMR fills significant gaps in the current suite of ocean color sensors. Current NASA ocean color missions do not provide the temporal or spatial resolution necessary to describe processes in the dynamic coastal zone.” GLIMR data enable quantification of biological and biogeochemical processes including primary production; tracking of carbon inventories in time and space; and the examination of impacts of tides, surface currents, and river discharge on distribution and fluxes of ocean materials. GLIMR provides federal, state, and local agencies with vital information on coastal hazards (e.g., oil spills, harmful algal blooms, post-storm assessment, water quality) for improved response, containment, and public advisories both at sea and along the coast. This paper reports on key design features and capabilities of the GLIMR instrument.

In partnership with Raytheon Intelligence and Space, Labsphere Inc. has been developing a technology demonstration system for a new type of on-board absolute radiometric calibration source. The Improved Radiometric Calibration of Imaging Systems (IRIS) addresses the need for reduced risk, cost, size, and mass for next generation Earth Observation (EO) satellites through paired onboard and vicarious calibration methods. In particular, the IRIS High-performance Integrated Flat Illuminator (HIFI) is a compact, combined VISNIR and SWIR (0.4 – 2.3μm), and MWIR-LWIR (3-14μm) Jones radiance source. Funded by the NASA Earth Science Technology Office (Grant to Raytheon #80NSSC20K1676), the IRIS Technology Demonstration Unit currently under test successfully meets significant program specifications for radiance, stability, adjustability, uniformity, and polarization. Development is ongoing to further improve system performance and achieve space flight qualification. This type of new technology additionally may provide a path to on-board calibration for small satellite architectures.

In 2016, construction was completed for two custom ultra-portable visible and near-infrared (VNIR) transfer radiometers developed by the Remote Sensing Group (RSG) at the University of Arizona. Dubbed CaTSSITTR (Calibration Test Site SI-Traceable Transfer Radiometer), these instruments have since been used for transfer radiometry in support of various field and laboratory calibrations around the world, much in support of the Radiometric Calibration Network, or RadCalNet, an initiative of the Working Group on Calibration and Validation of the Committee on Earth Observation Satellites (CEOS). As technology advancements in short-wave infrared (SWIR) detectors have matured and become more commercially available, RSG has been testing these SWIR detectors and system components towards the end goal of producing SWIR transfer radiometers based on similar design goals as the CaTSSITTRs. These goals include one operator portability and data collection, and standalone (battery) power for field collection times. To this end we strive to prove we can achieve high accuracy transfer radiometry in the SWIR without liquid nitrogen cooling or optical chopping. This work details the prototype testing results and system design details of these new SWIR ultra-portable transfer radiometers.

Front-end stray light baffles for optical imaging systems are used to limit the amount of out-of-field light that reaches the entrance pupil of the optical system. From star tracker baffles to the outer barrel of the Hubble Space Telescope, it is vital to design the locations and apertures of baffle vanes so that the inner walls of the baffle are not simultaneously visible to both stray light sources and the optical entrance pupil. Various designs have been presented for arbitrary cylindrical baffle tubes and explicitly specified conical tubes, but no working generalized algorithm has been presented where the baffle tube can take an arbitrary conical form. Haghshenas and Johari presented what should be a working recursive algorithm, but the published equations have two errors that result in incorrect output. Corrections to their equations are presented here. Additionally, tolerancing in the field of baffle design has typically been accomplished by slightly increasing the field-of-view of the baffle system to avoid clipping the optical field due to mechanical tolerance errors. A new way of incorporating fabrication, alignment, and environmental tolerancing is presented that is more consistent with typical mechanical engineering practice and margin against those fabrication errors is included in the recursive equations with demonstration of their benefit.

The Fly’s Eye GLM Simulator (FEGS) is a multi-band radiometer system designed to measure lightning optical emission through thunderstorm cloud-tops. It is carried as a payload on the NASA ER-2 high-altitude aircraft with a primary objective to provide ground validation measurements for the Geostationary Lightning Mapper onboard NOAA GOES-R series satellites. During 2022/23 a series of upgrades were applied to the FEGS optical and electronics systems to improve radiometric precision and optimize the sensor dynamic range. In July 2023 FEGS will collect a new set of observations as part of the Airborne Lightning Observatory for FEGS and Terrestrial Gamma-Ray Flashes (ALOFT) flight campaign. This presentation will describe recent upgrades to the FEGS instrument, provide a preliminary analysis of observations from the ALOFT campaign, and discuss implications for future space-based lightning optical detectors.

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) consists of an Earthviewing reflected solar (RS) spectrometer that will measure the Earth-reflected solar radiation from International Space Station with an SI-traceable radiometric uncertainty of 0.3% (1-sigma). The high-accuracy CPF measurements will provide an in-orbit reference for intercalibrating other spaceflight RS instruments. The CPF intercalibration team has been tasked to develop a state-of-the-art approach to calibrate the shortwave channel (300-5000 nm) of the Clouds and the Earth’s Radiant Energy System (CERES) instrument and the reflective solar bands (RSB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, both onboard the NOAA-20 satellite, against the CPF benchmark measurements. The aimed intercalibration methodology uncertainty for both the target instruments is also 0.3%. To meet this stringent intercalibration accuracy, the CPF team has developed methods for mitigating the impacts of spatial, spectral, and angular differences between the intercalibration footprints from the CPF and target instruments. To further alleviate uncertainty, the CPF team will employ Polarization Distribution Models (PDMs) to characterize the polarization state of the Earth-reflected radiance as a function of the intercalibration footprint scene type, solar and viewing geometry, and wavelength. The PDMs will assist in identifying low-polarized scene radiances for meticulously intercalibrating the polarization sensitive VIIRS instrument against the significantly-less polarization-sensitive CPF instrument. This paper will highlight the CPF mission overview, the details of the CPF intercalibration approach, and additional outcomes of the CPF intercalibration studies that may benefit the broader remote sensing community.

Spectralon® is a high reflectance excellent diffuser used to reflect sunlight for use as a calibrator for on-orbit and ground instruments. Radiometric calibration of the reflective bands in the 0.4 to 2.5μm wavelength range is performed by measuring the sunlight reflected from Spectralon®. Reflected sunlight is directly proportional to the Bidirectional Reflectance Distribution Function (BRDF) of the Spectralon®. On-orbit exposure to sunlight results in solarization due to solar UV and the presence of residual contamination. Spectralon® quality is checked at start of build by measuring the change in reflectance on exposing a witness sample to 100 hours Solar UV as an indication of on orbit performance. For JPSS J2, the witness samples accompanied the sensor till 30 days before launch. Measuring the reflectance change on exposure to Solar UV of the witness samples accompanying the sensor through build and test is a better indication of on orbit performance as this includes any additional contamination during the build and test phase.

The NASA Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission Ocean Color Instrument Team has completed the prelaunch radiometric characterization of the thermal response of the Ocean Color Instrument (OCI). The radiometric performance of the ultraviolet to visible (UVVIS) and visible to near-infrared (VISNIR) grating spectrographs and the shortwave-infrared (SWIR) filter spectrograph of OCI were characterized during the thermal vacuum testing of the instrument conducted in September and October of 2022. The thermal characterization test program will be outlined, along with the derived radiometric dependencies on temperature. For the UVVIS and VISNIR spectrographs, the change in radiometric response with temperature is consistent with theoretical models of the measured detector performance and is on the order of 0.15% per °C. For the SWIR spectrograph, the change in radiometric response with temperature in on the order of 0.04% per °C. For the UVVIS spectrograph, uncertainties in the radiometric measurements as the detector temperatures varied by ∼10° C were less than 0.15% for wavelengths of 350 − 593 nm. For the VISNIR spectrograph, uncertainties were less than 0.11% for wavelengths of 625 − 867 nm. For the SWIR spectrograph, the typical uncertainties were less than 0.15% for all bands. Since the expected temperature range for the instrument on orbit is 0.5° C, OCI meets the design goals for upper limits on radiometric uncertainties due to thermal effects.

The Goddard Laser for Absolute Measurement of Radiance (GLAMR) is a mobile spectral and radiometric sensor characterization facility based at NASA/Goddard Space Flight Center. Based on NIST’s traveling Spectral Irradiance and Radiance Calibration using Uniform Sources (SIRCUS), GLAMR consists of a system of tunable lasers to generate quasi-monochromatic energy between 310 and 2500nm, a large integrating sphere to provide a full aperture uniform source, a control system to automate operations and a data system to record and serve telemetry. GLAMR was used to characterize the Ocean Color Instrument (OCI) to be launched aboard the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. The test of the OCI flight instrument took place in October 2022. GLAMR will be used to characterize the CLARREO Pathfinder (CPF) instrument in September 2023. Both programs had stringent calibration requirements on GLAMR, necessitating additional characterization of GLAMR radiometric uncertainty and improvements in the NIST traceability. This paper will discuss the improvement in the GLAMR uncertainty budget and the performance of GLAMR for the OCI instrument as well as the upcoming test for CPF.

The NASA GSFC Code 618 Calibration Laboratory maintains instruments and National Institute of Standards and Technology (NIST) traceable calibrated sources and detectors to calibrate, characterize, and monitor remote sensing instrumentation throughout NASA and the larger scientific community. Under the Calibration Laboratory umbrella, we operate the Radiometric Calibration Lab (RCL) focused on calibrating instrument radiometers, the Diffuser Calibration Lab (DCL) specializing in NIST traceable calibration of reflective and transmissive space diffusers. The RCL uses broadband sources as well as an array of options for monochromatic spectral calibration to provide regular NIST traceable calibration services to ground, flight, and remote sensing missions at NASA GSFC. The DCL uses scatterometers to measure the Bidirectional Reflectance and Transmittance Distribution Functions (BRDF & BTDF) of flight diffusers and witness samples. As we look to the future, the Calibration Laboratory will be automating routine processes throughout the facility and updating our online data collection and distribution capabilities. We are adding monitoring radiometers to our Grande calibration sphere to improve NIST traceability. Hardware updates to our scatterometers will keep us aligned with the diffuser calibration capabilities being developed at NIST.

The Ocean Color Instrument (OCI) is a sensor on the upcoming Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in early 2024. OCI is a grating spectrometer with hyperspectral coverage from the ultraviolet (about 310 nm) to near-infrared (about 900 nm), with additional filtered channels in the short-wave infrared (940 nm – 2260 nm). This instrument will provide ocean color science data to continue the data sets collected by heritage sensors MODIS, SeaWiFs, and VIIRS, but with increased spectral coverage and improved accuracy. In order to achieve the high levels of accuracy demanded by the science community, a rigorous ground test program was conducted to calibrate the instrument and ensure that the calibration can be transferred to on-orbit operations. Some calibration parameters can only be measured during pre-launch testing; one such parameter is the polarization sensitivity. Polarization testing measured the Mueller matrix components needed to determine the polarization sensitivity for all spectral bands for a series of telescope scan angles covering the expected on-orbit scan range. Results indicate that the sensitivity is below 0.6 % except at the shortest wavelengths (less than 340 nm) and was characterized to better than 0.1 % above 340 nm. This indicates that any polarized scenes measured on orbit can be corrected for with a high degree of confidence.

Cloud thermodynamic phase is an important parameter in climate models and cloud remote sensing because it controls whether a cloud tends to have a net heating or cooling effect and it must be known to retrieve other cloud parameters. Passive remote sensing of cloud thermodynamic phase using shortwave infrared radiance ratios is a well-known technique, and adding polarization sensitivity to the radiance ratio method can increase accuracy. Ground-based passive polarimetric remote sensing of cloud phase has also been performed in visible and near infrared wavelengths. Prior work has relied on highly sensitive, expensive polarimeters to detect the small change in polarization state between ice and liquid clouds. We explored the use of a low-cost, commercial division-of-focal-plane polarization imager for cloud thermodynamic phase retrievals. We calibrated and deployed a monochrome polarization imager, with both a moderate field-of-view lens and a fisheye lens. The imagers were deployed alongside a verified dual-polarization lidar that provided a truth measurement at the zenith. In this paper, we discuss the relationship between the Stokes S₁ parameter measured by the low-cost polarization imager with both lenses and the cloud thermodynamic phase retrieved by a dual-polarization lidar.

The 18th Geostationary Operational Environmental Satellite (GOES-18) was launched on 1 March 2022 and became operational on 4 January 2023, replacing GOES-17 as GOES-West. For GOES-18 ABI, the solar channel calibration has a large seasonal variation, even after the correction of an alignment parameter. This paper reports a method to correct these errors, which is similar to the method proposed for GOES-16/17 ABI. We will report the results for GOES-18 and an update for GOES-16/17. The method and the corrected calibration coefficients can be used in a reprocessing of the ABI L0 data.

Lunar surface reflectance is considered extremely stable. This property has been used to validate the stability of satellite instrument calibration for reflective solar bands (RSB), such as Channels 1-6 of the Advanced Baseline Imager (ABI) onboard the Geostationary Operational Environmental Satellite (GOES). A common method is to compare the measured and modeled lunar irradiance over time. An early lunar irradiance model, the Robotic Lunar Observatory (ROLO) model, was released by the Global Space-based Inter-Calibration System (GSICS) as GSICS Implementation of the ROLO (GIRO) model. Another lunar irradiance model, the Spectral Lunar Irradiance Model Effective wavelength methodology (SLIM), was published recently. In this study, we evaluate these two models using regularly collected ABI lunar observations, with special attention to their dependence on lunar phase angle in the visible bands for B01-B02 (0.47 – 6.4 μm) and near-infrared bands for B03-B06 (0.86 – 2.3 μm). It was found that GIRO model performs well for 0.47 – 0.9 μm range but is biased for images of small lunar phase angle, and the bias increases with wavelength. SLIM model substantially corrected these biases, and the residual bias may be further reduced empirically. The SLIM model consistently predicts higher, and closer to ABI, irradiance values than the GIRO model across all ABI visible and nearinfrared (VNIR) channels.

Stray light rejection around local midnight during eclipse season is a unique challenge for satellite instrument on geostationary orbit, especially for a 3-axis stabilized platform such as the Advanced Baseline Imager (ABI) on the U. S. Geostationary Operational Environmental Satellite (GOES-16/17/18), the Advanced Himawari Imager (AHI) on Japan’s Himawari-8/9 satellites, and the Advanced Meteorological Imager (AMI) on Korea’s GEO-KOMPSAT-2A satellite. In this study, we use the data collected in fall 2022 to compare the straylight rejection performance for the infrared (IR) channels of these instruments, all built by the same manufacture. Since straylight contamination is most pronounced in the 3.7 µm channel, the straylight magnitude in this channel is estimated for the six instruments and compared with each other. The results show that the three ABIs met the requirements, with GOES-17 slightly worse than GOES-16 and GOES-18 noticeably better than GOES-16/17. Both Himawari-8/9 AHIs are subject to serious stray light contamination, including the bands of straylight far away from the Sun that is due to the “sneak path”. Launched in October 2014, Himawari-8 is the first satellite with ABI-type instrument. Thanks to Japan Meteorological Agency (JMA) who shared early AHI-8 results with NOAA, the manufacture was able to improve the straylight rejection for the following flight modules, which proves to be successful. The AMI data is currently being processed; the results will be reported to the conference.

The Advanced Baseline Imager (ABI) sensor, which is on board the new generation of NOAA’s Geostationary Observational Environmental Satellites (GOES) R-series or GOES-R platforms, is of critical importance in weather forecasting and other environmental monitoring. The NOAA GOES-R Calibration Working Group (CWG) has developed an Image Navigation and Registration (INR) monitoring system CENRAIS (CWG Extended Navigation and Registration Analysis and Improvement System). The GOES-R ABI Trending and Data Analysis Toolkit (GRATDAT) is a software tool suite for supporting the GOES-R Advanced Baseline Imager (ABI) radiometric and geometric operations. It has the capacity to process the GOES-R ABI L0 data up to the L1B data through full sets of radiometric and geometric processing the same as the GOES-R ground operational processing of the data. Therefore, GRATDAT has the potential to be used as a toolkit in calibration and validation group work investigating the cause of the geometric calibration or correction anomaly. This paper focuses on the comparison of GOES-R Geometric or INR monitoring using both the GRATDAT generated and GOES-R ground processing generated L1b data and runs both pairs of the same time images through CENRAIS to evaluate and assess the accuracy of the GRATDAT Geometric or INR processing by comparing with the CENRAIS results of the two. The goal of this work is to make sure GRATDAT is accurate enough to be used as a toolkit to assistant in tracing the cause of any anomaly. In GRATDAT processing of GOES-R data from Level 0 to Level 1B, we can adjust any look up table (LUT) values to check the impacts of the parameters or thresholds used in the L0 to L1B processing, which gives us more power to detect both the geometric and radiometric anomaly and assess the impacts of any parameter and threshold value changes in the processing. Preliminary results of 2-hour FD and CONUS image comparison show the CENRAIS results from both Full Disk (FD) and CONUS image pairs are comparable and matching well from the pairs of CENRAIS runs. The Image Navigation Residuals (NAV), Frame-to-Frame Registration (FFR), Channel-to-Channel Registration (CCR) results from the comparison of two sets of images will be presented. One full day of the two sets of images will be processed through CENRAIS for a robust and convincing comparison.

The Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) is a primary tool for assessing INR performance of GOES-R series ABI images. IPATS assesses five INR metrics: navigation, channel-to-channel registration (CCR), frame-to-frame registration, within-frame registration, and swath-to-swath registration. It was discovered that CCR assessment results between Visible-Near-Infrared (VNIR) channels and Infrared (IR) channels exhibits an annual oscillation in the north-south (NS) direction and a diurnal oscillation in the east-west (EW) direction, with an amplitude of approximately 5 μrad and 2.5 μrad, respectively. However, differences of navigation assessment results between VNIR and IR channels do not exhibit the annual or diurnal oscillations observed in CCR results. This indicates that the observed oscillations are due to measurement errors. The characteristics of the oscillations imply that cloud shadows are a possible cause of these measurement errors. In this study, several methods are explored to minimize the impact of cloud shadows on VNIR to IR CCR assessments: a) assessment at landmark locations only; b) using navigation assessment results to filter CCR assessments; c) using the ABI clear-sky-ratio product as a cloud mask; and d) smaller CCR assessment windows. In this paper, each method and a combination of several methods are evaluated based on assessment accuracy and the number of successful assessments. The selected approach is then used to reprocess GOES-16 ABI CCR data to show reductions in the annual and diurnal measurement error oscillations.

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua spacecraft measures the upwelling radiance of the atmosphere from 3.7 to 15.4 μμm. The AIRS radiometric calibration coefficients convert the counts measured from the instrument’s A/D converters (Level 1A) to SI traceable radiance units (Level 1B). The calibration equations are based on how the instrument operates and follow a simple second order relationship between counts and radiance. Terms are included to account for nonlinearity of the detectors, emissivity and temperature knowledge of the on-board calibrator (OBC) blackbody and radiometric offset due to coupling of the polarization of the scan mirror with the spectrometer. Radiometric coefficients have not been updated since launch and are used in the operational Version 5 available at the GES/DISC. A new set of coefficients, Version 7 (V7), were produced in 2018 but never released. This paper presents the coefficients for Version 8 (V8) with only a few changes from V7 relating to the additional time used in the training of the trend of the polarization coefficients. We then compare new coefficients, V8, with the latest operational version of the AIRS radiometric calibration coefficients Version 5 (V5) and the prior V7. The Version 8 coefficients utilize more of the pre-flight test data and show lower residuals to the tests than V5. V8 also removes a trend in the polarization seen in Module 5 and is expected to have more accurate nonlinearity than prior versions.

The exit of EOS Aqua from the A-train in early 2023 marks the end of 20 years of Atmospheric Infrared Sounder (AIRS) data from the 1:30 PM ascending node orbit. The AIRS 20-year data record shows impressive accuracy and stability. Trends in the radiometry relative to accepted stable geophysical references are at the -3 to +6 mK/yr level, likely caused by unaccounted for changes in the lower troposphere and increasing sensor aging effects. Previously unknown trends are seen in the distribution of clouds. The planned continuation of the AIRS data record with potentially 20 years of multiple Cross-track Infrared Sounder (CrIS) instruments may be used to confirm these trends. The overlap of three years of AIRS, SNPP-CrIS and JPSS1-CrIS shows radiometric agreement under cloud free ocean conditions at the 50 mK level. However, there are large day/night, land/ocean and cloud dependent differences between AIRS and CrIS data, which, even if explained by known footprint size differences, will complicate the climate change interpretation of trends from potentially 40 years of concatenated data.

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002 and is currently fully operational. AIRS, in addition to the infrared system comprised of 2378 channels with wavelengths ranging from 3.7-15.4 um, has 4 Visible/Near-Infrared channels and an on-board calibration source utilizing 3 independent lamps to characterize the change in the visible response over time. We describe our experience from 20 years of AIRS data using internal calibration lamps and Deep Convective Clouds (DCCs) for the calibration and stabilization of the AIRS visible light data. We compare and contrast the response the response of the 4 AIRS Visible channels to the three onboard calibration lamps and DCCs. The upcoming release of the AIRS Version 8 Visible L1B product will be using a DCC based calibration.

AIRS has provided highly stable and accurate radiances since 2002, which has exceeded the expected instrument noise level. Despite the highly accurate data our analysis has shown warming as high as 5 Kelvin in the shorter wavelength portions of the AIRS spectrum for extremely cold scenes (less then 230 Kelvin), such as when AIRS views deep convective clouds. The warming only exists when AIRS is viewing a cold scene with neighboring warmer scenes. This work will demonstrate the spatial characteristics of these trends in relation to where the warm area is to the scene AIRS is viewing. Lastly, we will show that a linear regression correction approach that will account for the trend in the shorter wave portions of the AIRS spectrum.

After more than 20 years in orbit, NASA’s Terra and Aqua satellites have both started drifting away from their historically maintained orbits. The MODIS instruments on Terra and Aqua continue to collect valuable Earth observation data, but the changing orbits present a challenge for maintaining accurate calibration. The MODIS reflective solar bands (RSB), spanning the wavelength range from 412 nm to 2130 nm, are calibrated on orbit using a combination of regular data collections from an on-board solar diffuser, the Moon, and pseudo-invariant Earth scenes. Starting in the Collection 6 Level 1B (L1B) data products, the RSB calibration began using data from desert targets for a few of the visible bands to better track changes in the response versus scan angle that could not be captured by the on-board calibration. The use of Earth scene data has been extended recently for Terra MODIS calibration in Collection 6.1 (C6.1) and the upcoming Collection 7 (C7) L1B to also include data from ocean scenes and deep convective clouds (DCC). Drifts in both the orbit inclination and ground track of Terra and Aqua lead to changes in the solar illumination angles and satellite view angles of the Earth scenes. We discuss how these orbital changes impact the desert and DCC targets used for MODIS RSB calibration and present the accompanying changes made to our C6.1 and C7 calibration algorithms. We also discuss remaining future challenges, such as better characterization of bi-directional reflectance distribution functions, and possible alternative calibration strategies.

The MODIS instrument onboard the Terra and Aqua satellites provides key measurements of various environmental parameters such as the land, ocean, and atmosphere. After over two decades of successful operations, both sensors experienced anomalies in the year 2022. In March, the Aqua spacecraft and, subsequently, the MODIS instrument entered a safe mode, and Terra MODIS experienced a Command Processor and Format Processor (CP/FP) reset. Separately, the Terra constellation exit maneuver (CEM) was performed in October, which included the transition of the MODIS instrument into a safe configuration as well. While MODIS has 16 infrared channels referred to as the thermal emissive bands (TEB), only the longwave infrared bands (27-30) were significantly impacted due to an increase in electronic crosstalk contamination after the Aqua MODIS sensor entered into safe mode. Crosstalk corrections have been applied to these bands to maintain the Level 1B product quality. Although to a lesser extent, the same MODIS bands were affected due to a slight increase in electronic crosstalk contamination after the Terra CEM was completed. Lastly, the Terra MODIS CP/FP reset had an effect on the digital output that transferred onto its photovoltaic bands due to their calibration algorithm. This paper presents the impacts of these events on the instruments’ TEB performance, and the subsequent changes made to their respective calibration algorithms.

In February 2023 the Landsat 8 mission with its two payloads passed the milestone for a decade of on-orbit operation. This manuscript would summaries major events that occurred through this period to the observatory which includes the spacecraft the two science payloads and their on-board calibration components. It provides a review and decadal summary for the radiometric and geometric performance and stability of the OLI and the TIRS science payloads. Highlights of the current state of the Radiometric and Geometric characteristics performance will be shown. This manuscript illustrates, that despite various safehold events and other technical challenges the Landsat 8 mission continue to perform extremely well, successfully expending the Landsat earth-data archive from 40 years to beyond the 50 years mark.

Landsat 8 collects the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) data and stores them at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The Landsat Product Generation System (LPGS) was designed to process both OLI and TIRS acquisitions and combine them into the 11-band Level 1 Terrain (L1T) standard products. Processing parameters and various scene statistics are stored and used for radiometric and geometric assessments of generated products. In this paper, we discuss application of several processing changes and instrument calibration updates to product generation that have been performed over the first 10 years of the mission life to address variations in instrument responsivity and effects of spacecraft and sensor anomalies. In addition, we provide examples of radiometric and geometric performance assessments to demonstrate product calibration stability over time. After 10 years on orbit, both Landsat 8 sensors continue to perform very well and provide high quality products to the user community.

Satellite nocturnal images of the Earth are a useful way to identify urbanization. Nighttime lights have been used in a range of scientific contributions, including studies on building human development indices and on the identification of megalopolises and impacted landscapes. However, the study of the area and the internal structure of urban systems by nighttime light imagery has had a fundamental limitation to date: the low spatial resolution of satellite sensors. DMSP Operational Linescan System (OLS), with a 2.7 km/pixel footprint, has been gathering global low-light imaging data for over 40 years. The 2011 launch by NASA and the NOAA of the Suomi National Polar Partnership (SNPP) satellite, with the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on board, has led to a significant improvement. This instrument has a better spatial resolution (742 m/pixel), onboard calibration, a greater radiometric range, and fewer saturation and blooming problems than DMSP-OLS data. The launch of Luojia 1-01 in June 2018 has increased expectations. Its high-resolution nocturnal images (130 meters/pixel) allow a better in-depth study of the landscape impacted by urbanization. The objective of this work is to analyze the ability of different nighttime light sensors to delineate urbanized and built-up areas, as well as their effectiveness in typifying and classifying different types of urban developments. The case studies are the three major Chinese megacities: the Guangdong Bay Area (GBA), the Shanghai agglomeration and the Beijing- Tianjin-Hebei (BTH) metropolitan region. For the delimitation of the urbanized and built-up areas that make up the three mentioned megalopolises, the usefulness of Zipf's Law is evaluated. The research question proposed in this paper is whether urban development occurs spontaneously following Zipf's Law, or more generally Pareto's distribution. Initial results confirm the usefulness of applying Zipf's law to DMPS-OLS sensor images to identify the urbanized areas of major Chinese megacities. However, sensors with a higher spatial and radiometric resolution, such as NPP-VIIRS or Luojia 1-01, show greater complexity. The application of Zipf's Law to the images obtained by these sensors allows the identification of the densest and most compact built-up areas. However, they do not show a clear opportunity to identify and delimit the urbanized areas that compose the metropolis.

In recent decades, rapidly increasing forest fires have become a significant threat to the forest environment and rural communities. The average annual land affected by wildfires from 1997 to 2018 reached 10350 ha in Türkiye. In order to mobilize forestry protection and post-wildfire recovery plans, earth observation satellites have become the key component due to their wide range of data and vision capacity. In this study, a classification-based burn severity assessment was planned created on single post-wildfire satellite images from the Southern Mediterranean Region of Türkiye which has a quite complicated topography. The classification algorithm was trained to classify images into four classes: unburned forest area, low severe burned forest area, moderate severe burned forest area and high severe burned forest area. The classification results compared with differenced Normalized Burn Ratio (dNBR). Various remote sensing products were taken into consideration during generating the methodology. For minimizing fieldwork and understanding the study area characteristics, aerial photos of 0.25 m spatial resolution were analyzed and used for train/test points collection; 11519 train and 400 test points have been selected. Sentinel-2 were used as input data. Classification algorithm selected as Random Forest. Overall accuracy, kappa coefficient, precision, recall and F-score parameters have been calculated for accuracy assessment. As a result, F-scores of 0.9, 0.77, 0.71 and 0.85 were obtained from Sentinel-2 for unburned forest area, low severe burned forest area, moderate severe burned forest area and high severe burned forest area, respectively. Corresponding F-scores of 0.85, 0.47, 0.63 and 0.76 were calculated from the dNBR.

In recent years, airports, serving as vital transportation hubs, have faced the challenge of limited available land in megacities. As a result, airport construction on reclaimed areas has become a common solution. However, over time, these areas are exposed to soil behaviors like settlement and uplift, leading to surface movements. Detecting and monitoring these movements consistently is crucial to prevent potential disasters. Interferometric Synthetic Aperture Radar (InSAR) has emerged as a powerful tool for monitoring surface movements with high temporal and spatial resolution based on satellite properties, unlike traditional point-based methods. In particular, time series InSAR methods, such as Persistent Scatterer Interferometry (PSI), have been developed to monitor surface movements over a period of time. However, in addition to observing past surface movements, forecasting future movements is also of great importance. In this context, various forecasting methods have been explored, among which Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) have gained significant popularity due to their successful performance. In a recent study, these two methods were applied to forecast surface movements at Istanbul Airport, utilizing time series data obtained from the freely available Sentinel-1 SAR images. The performance of the ARIMA and LSTM models was evaluated using well-established metrics including root mean square error (RMSE) and mean absolute error (MAE). Both ARIMA and LSTM are suitable for forecasting surface movements, but LSTM exhibited a marginally better fit to the data compared to the ARIMA model.

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument on the recently launched NOAA-21 (previously JPSS-2) satellite. The VIIRS, like its predecessors on the SNPP and NOAA-20 satellites, provides daily global coverage in 22 spectral bands from 0.41 to 12.0 micrometers. The geometrically and radiometrically calibrated observations are the basis for numerous operational applications and scientific research studies. Fourteen of the 22 bands are reflective solar bands (RSBs), covering wavelengths from 0.41 to 2.25 micrometers. The RSBs were radiometrically calibrated prelaunch and are regularly calibrated on orbit through the onboard solar diffuser (SD) and scheduled lunar observations. The on-orbit SD’s reflectance change is determined by the onboard solar diffuser stability monitor (SDSM). Here, we report our findings on the early mission NOAA-21 VIIRS RSB radiometric performance, and the performance of the SD and the SDSM.

On November 10, 2022, the NOAA-21 (also known as Joint Polar Satellite System (JPSS)-2) Visible Infrared Imaging Radiometer Suite (VIIRS) was successfully launched and operated on-orbit. The NOAA-21 VIIRS is the third VIIRS instrument in the series, following S-NPP and NOAA-20, providing 22 spectral bands that cover a spectral range from 0. 402 μm to 12.5 μm. From the intensive Post Launch Tests (PLTs), the NOAA-21 VIIRS Sensor Data Record (SDR) achieved beta maturity status on Feb. 23, 2023 and is expected to achieve provisional and validated maturity in the next few months, ensuring the performance requirements are met and data are of high quality with on-orbit calibration. The accuracy of the current NOAA-21 VIIRS Reflective Solar Band (RSB) calibration was limited by in the Solar Diffuser (SD) degradation estimates, which proportionally affect the accuracy of the on-orbit RSB calibration. To achieve the beta maturity status, the SD degradation was omitted from the initial radiometric response analyses, and calculated solar calibration scaling coefficients (F-factors) were extrapolated to the start of the on-orbit operations that marked the onset of the SD degradation. To mitigate the unexpected SD reflectance variability, a series of yaw maneuvers will be performed as a part of the PLTs during the Intensive Calibration and Validation (ICV) phase. In addition to the yaw points, on-orbit Solar Diffuser Stability Monitor data sets will fill the intermediate angles between the yaw angles. The updated estimates of the SD degradation (H-factors) will be applied in the SD F-factor calculations. Finally, the improved SD F-factors will be compared and validated with vicarious calibration results, such as lunar F-factors. This paper will evaluate the impacts of SD-based calibration updates for NOAA-21 RSBs through assessing the radiometric biases of NOAA-21 VIIRS RSBs relative to NOAA-20 ensuring the radiometric accuracy of the NOAA-21 SDR products.

The NOAA-21 VIIRS yaw maneuver operation was carried out in March 2023 over 15 scheduled orbits to characterize the three required input functions for the standard on-orbit RSB calibration pipeline. The characterization functions of the product of the bidirectional reflectance factors (BRFs) of the solar diffuser (SD) with the vignetting function (VF) of the SD screen (SDS) are derived for the two required outgoing directions from the SD to the RSBs and from the SD to the SDSM. The VFs for the attenuation screen placed in front of the Sun-view port are also derived with the yaw measurements.

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the NOAA-21 satellite was successfully launched on November 10, 2022, as a follow-on to the VIIRS onboard the Sumi-NPP (S-NPP) and NOAA-20 satellites. NOAA-21 VIIRS has been under the intensive cal/val phase since its cold Focal Plane Array (CFPA) temperature reached nominal operating temperatures (on late February 10, 2023). This study focuses on NOAA-21 VIIRS Thermal Emissive Bands (TEB, I4-I5 and M12-M14) early on-orbit performance. NOAA-21 VIIRS TEBs have been performing well in general. Blackbody (OBCBB) and other instrument temperatures are stable during nominal operations, with a mean value of 27 mK. A mid-mission outgassing (MMOG) was performed on February 23, 2023 to remove potential ice contamination. CFPA temperatures were switch 82 K to 80 K on March 3, 2023 to further enhance the performance. After these two events, NOAA-21 VIIRS long-wave infrared (LWIR, I5 and M14-M16) detector responsivities have remained generally stable. Mid-wave infrared (MWIR, I4 and M12-M13) bands have been degrading again since mid-March 2023, with degradations more than 4% for some M12 and I4 detectors by mid-July 2023. NOAA-21 TEB Noise Equivalent Differential Temperatures (NEdT) are well within specifications. Prelaunch calibration offset, nonlinearity, and response versus scan were verified using on-orbit OBCBB warm-up/cool-down (WUCD) and spacecraft pitch maneuver data. TEB SDR calibration biases and improvements in the NOAA operational Sensor Data Records (SDR) were evaluated by inter-comparison of VIIRS with co-located CrIS observations. The impacts of MWIR degradations on NEdTs and TEB SDRs are negligible so far.

The second NOAA/NASA Join Polar Satellite System (JPSS-2) satellite was successfully launched on November 10, 2022, becoming NOAA-21. Instruments on-board the NOAA-21 satellite include the Visible Infrared Imaging Radiometer Suite (VIIRS). This instrument is the third build of VIIRS, with the first and second flight instruments onboard NASA/NOAA Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20 satellites operating since October 2011 and November 2017, respectively. The purpose of these VIIRS instruments is to continue the long-term measurements of biogeophysical variables for multiple applications including weather forecasting, rapid response, and climate research. The geometric performance of VIIRS is essential to retrieving accurate biogeophysical variables. This paper describes the early on-orbit geometric performance of the JPSS-2/NOAA-21 VIIRS. It first discusses the on-orbit position and attitude performance, a key input needed for accurate geolocation. It then discusses the on-orbit geometric characterization and calibration of VIIRS and an initial assessment of the geometric accuracy. It follows with a discussion of correcting the scan angle dependent geolocation biases across the scan. Finally, this paper discusses onorbit measurements of the band-to-band co-registration, focal length and the impact of this on the scan-to-scan underlap/overlap.

NOAA-21 satellite was successfully launched on November 10, 2023 and joins the SNPP and NOAA-20 missions under NOAA Joint Polar Satellite System (JPSS) to provide continuation of Earth system observations. The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard the SNPP, NOAA-20 and NOAA-21 satellites provide sustained long-term Earth observation data accumulating to over a decade. The unique VIIRS Day/Night Band (DNB) observations particularly have a wide range of applications such as geophysical and socio-economic studies and natural disaster assessment. As learned from SNPP and NOAA-20 DNB, there was stray light over high latitude regions (with spacecraft solar zenith angle less than 118.4 degree) in DNB images over both northern and southern hemispheres. Efforts in prelaunch preparation have been devoted to reducing NOAA-21 DNB stray light. The post-launch assessment indicates that there are traces of stray light in the NOAA-21 DNB image, but with a significant reduction in stray light magnitude in comparison with both SNPP and NOAA-20 DNB. This paper presents the development and application of stray light correction for NOAA-21 DNB. Furthermore, the spatial distribution and magnitude of DNB stray light of NOAA-21 are assessed and compared with SNPP and NOAA-20. DNB images with no major artificial or auroral lights over the northern and southern hemispheres on new moon days are selected for comparison. It is found that NOAA-21 DNB stray light over both hemispheres is reduced by ~40 to 60% (depending on the along scan zone) in comparison with NOAA-20 DNB, which confirms the effectiveness of the prelaunch efforts in reducing the NOAA-21 DNB stray light.

A field deployable transfer radiometer has been developed as part of an effort to ensure the quality of upwelling radiance at automated test sites used for vicarious calibration in the solar reflective. Ground-based radiometer measurements of the surface combined with knowledge of the atmospheric state can be used to predict top-of-atmosphere reflectance and radiance. This work discusses two pathways with independent traceability of deriving the surface reflectance, namely a radiance-based and reflectance-based approach. The radiance-based retrieval converts the upwelling radiance reported by the radiometer to reflectance using radiative transfer calculations and atmospheric characterization data. The reflectance-based approach converts measurements by the radiometer of the surface to reflectance through ratios to data collected while viewing a diffuser reference of known reflectance. The results from both traceability paths are obtained using the same radiometer data sets, thus allowing analysis of any resulting differences. Field radiometer data collected at a desert site in the western US coincident with overpass of the Landsat 8 OLI sensor are analyzed to understand the impact of the two approaches on predictions of both the top-of-atmosphere reflectance and radiance. The comparison between the two traceability paths shows clear differences, but these differences are within the combined uncertainties of the two approaches.

This paper presents an intercomparison study between the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) using data from the Radiometric Calibration Network (RadCalNet). The study evaluates the radiometric performance and agreement between ASTER and Landsat 8 OLI, focusing on their spectral bands relevant for vegetation analysis and land cover classification. The analysis includes the assessment of data quality, uncertainties, and factors influencing the measurements. The results demonstrate the usability of RadCalNet in evaluating the accuracy and reliability of remote sensing data. The findings contribute to our understanding of the strengths and limitations of ASTER and Landsat 8 OLI, supporting informed decision-making in environmental monitoring and resource management. Overall, the intercomparison study provides valuable insights into the capabilities and limitations of ASTER and Landsat 8 OLI, highlighting the importance of RadCalNet in assessing the radiometric performance of remote sensing sensors. The results from the Railroad Valley RadCalNet show that the site is suitable for sensors with spatial resolutions as small as 15 m. The comparison between ASTER and OLI demonstrates that the recent update to the ASTER radiometric calibration provides results that are in agreement with Landsat 8 OLI to well within the absolute radiometric uncertainties of both sensors.

The Clouds and Earth’s Radiant Energy System (CERES) project operates six instruments that provide a continuous record of the Earth’s radiation budget (ERB) at the top of atmosphere (TOA). The instruments are flying on the Terra, Aqua, SNPP and NOAA-20 spacecraft. The CERES instruments on Terra and Aqua have completed twenty years of continuous operations. Each instrument is calibrated and characterized on the ground before launch. Post launch, the calibration is conducted using on-board calibration sources and the performance of the instrument is validated using vicarious approaches using both Earth and celestial targets. In this paper, we describe the calibration and validation approach and demonstrate the performance of the CERES instruments on the Terra and Aqua spacecraft over the twenty-year period since launch.

The NASA Clouds and the Earth's Radiant Energy System project provides the scientific community with observed top-of-atmosphere shortwave and longwave fluxes for climate monitoring and climate model validation. To provide consistent VIIRS cloud retrievals, the CERES Imager and Geostationary Calibration Group (IGCG) must understand and quantify the stability of the VIIRS instruments. To achieve this, the IGCG utilizes tropical deep convective clouds (DCCs) as invariant targets. Proper seasonal characterization of the DCC bidirectional reflectance distribution function (BRDF) is key to the success of DCC-based calibration methods, particularly for shortwave infrared (SWIR) bands. This article proposes the use of a deep neural network (DNN) to characterize VIIRS solar reflective band BRDF reflectance, with which individual channel trends are isolated by manipulating the DNN time input. Initial results show that the DNN method can extract statistically significant SNPP-VIIRS band trends, using only SNPP-VIIRS inputs, that are correlative to and match the magnitude of significant trends determined using methods that rely on an external angular distribution model. The goal is to use this approach to actively monitor the stability of new instruments without the need for predetermined seasonal BRDF corrections.

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 Aqua- MODIS 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 DCC-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.

The NASA Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) product provides the scientific community observed TOA SW and LW fluxes for climate monitoring and climate model validation. To provide continuity for cloud retrievals between MODIS and VIIRS, the CERES project inter-calibrates MODIS and VIIRS utilizing coincident ray-matched radiance pairs over all-sky tropical ocean. The Aqua and Terra satellites have started drifting, thereby preventing any coincident tropical MODIS and VIIRS inter-calibration events. Similarly, no simultaneous nadir overpasses (SNOs) will exist between SNPP and NOAA satellites, which will fly in the same 1:30 PM orbit but positioned a half an orbit apart. The CERES project will utilize the Libya-4 and Dome-C invariant targets to radiometrically scale between MODIS and VIIRS reflective solar bands. This study has advanced the Libya-4 and Dome-C characterization by considering all angular conditions, improving clear-sky identification and atmospheric corrections. The BRDF for each VZA and RAA stratified angular bin is approximated using a 2^nd order regression with respect to cos(SZA). The clear-sky filtering utilized spatial homogeneity thresholds applied to channels not impacted by atmospheric parameters and additional angular bin specific dynamic filtering. Multiple sources of PW, ozone and aerosol optical depth are considered. The improved atmospheric characterization is evaluated by comparing the trendSE consistency across channels. For Libya-4 the 2.2μm and 0.91μm strong water vapor absorption bands, the trendSE was reduced by ~60% and ~80% by including the PW term. The Libya- 4 trendSE with atmospheric correction was reduced from within 2% to 1% for all channels except MODIS B17. The Dome-C 0.55mm and 0.65μm band trendSE was reduced by between 40% to 60% after accounting for ozone absorption. The Dome-C imager channel trendSE was reduced from within 2% to 1% by including atmospheric corrections. The Dome-C post-solstice ozone and PW daily variations are much smaller than prior to solstice. The Dome-C resulting post-solstice imager channel trendSE was reduced from 1% to 0.85% by including atmospheric corrections and closer to the 0.48μm band trendSE of 0.6%, which was not impacted by the atmosphere. Smaller trend_SE can be realized by limiting the large VZA observations over Libya-4 as well as utilizing only post-solstice observations over Dome-C.

Aerosol optical thickness (AOT) and water vapor (WV) was retrieved using Geo-KOMSAT2A satellite (GK-2A, Geostationary Satellite) launched in 2018, and operated by the Meteorological Satellite Center in Korea. GK-2A is equipped with 16 bands, including 4 visible bands, and is taking pictures of the East Asia region every 2 minutes. We utilized visible, near infrared, and shortwave infrared bands on AOT and WV retrieval. These bands are simultaneously affected by atmospheric scattering and surface reflection, so the contribution of each element can be simulated using the atmospheric radiation transfer model (RTM model). The first is to generate Look-up Table using RTM model of SBDART (Santa Barbara DISORT Atmospheric Radiative Transfer), the second is the atmospheric correction reflectivity calculation process. The third, WV and AOT was retrieved, and the results were compared and verified with ground measurement data. Finally, atmospheric correction was experimentally performed for polar orbit satellite (KOMSAT 3, 3A) images using WV and AOT as input variables.

The University of Arizona Remote Sensing Group (RSG) began outfitting the radiometric calibration test site (RadCaTS) at Railroad Valley Nevada in 2004 for automated vicarious calibration of Earth-observing sensors. RadCaTS was upgraded to use RSG custom 8-band ground viewing radiometers (GVRs) beginning in 2011, several of which are currently deployed providing an average reflectance for the test site. GVRs are also beginning to be deployed at other field sites for both vicarious calibration and reflectance product validation. The measurement of ground reflectance is the most critical component toward both of these goals. In order to ensure the quality of these measurements, RSG has been exploring more efficient and accurate methods of on-site calibration evaluation. We will present experimental methods and results testing commercial tablet screens as portable calibration sources. Recent work in medical fields have shown encouraging results for stability of tablet display luminance both short and long term. We assess them in spectral radiance using NIST-traceable methods and transfer radiometers, particularly the Calibration Test Site SI-Traceable Transfer Radiometer (CaTSSITTR). CaTSSITTR will also continue to play an integral role in the on-site deployment of this or any source, providing radiance calibration at time of use. Current on-site calibration methods (sun-illuminated sources) rely on stable, preferably clear sky conditions and require personnel involvement at each radiometer. While spectrally limited, a tablet source method may be able to help monitor some spectral bands more often and in any dry weather conditions.

The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments aboard the Suomi NPP and NOAA-20 spacecraft have successfully provided Earth image products since 2011 and 2017, respectively. Maintaining accurate radiometric calibration and calibration consistency between the two sensors is a necessity for the continued quality of long-term data records. In this work, the use of frequent VIIRS measurements of brightness temperature over the area surrounding Dome Concordia (Dome C), Antarctica (75.1 °S, 123.4°E) to track the long-term stability of its thermal emissive bands (TEB) is presented. The extremely dry, cold, and rarefied atmosphere of the site makes it ideal to track and detect longterm changes in the TEB responses via analysis of near-nadir and off-nadir VIIRS overpasses in reference to the surface temperature measurements provided by an automated weather station (AWS). Multi-year Dome C measurements have been used to assess the stability of the VIIRS response-versus-scan-angle (RVS) of the half-angle-mirror (HAM), derived from prelaunch characterization, and detector differences at multiple scan angles. Also, included in this work is the RVS stability assessments using the Dome C overpasses. The methodology developed via this work will also be applied to the recently launched VIIRS instrument onboard the NOAA-21 satellite (previously JPSS-2) in the future.

The MODIS instruments on the Terra and Aqua spacecraft employ a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) system to calibrate their reflective solar bands (RSBs), covering a spectral range from 0.4 to 2.1 μm. The UV exposure of the SD, from its sun-view port as well as the scattered light (sunlight reflected from top-of-atmosphere), has led to a wavelength dependent degradation of the SD, with larger degradation observed at shorter wavelengths. The scatter off the diffuser onto the scan mirror is in the forward direction, whereas the scatter off the diffuser onto the SDSM fold mirror is in the backward direction. Since the outgoing angles (viewed by MODIS detectors) are the same as the scheduled SD calibration, the gain derived from scattering light facilitates monitoring the dependence of the SD’s degradation on incident angles. In this paper, we present a method that uses multiple orbits over each mission to obtain a SD response to the nadir port illumination. The SD degradation estimated from the nadir port illumination is compared with the degradation derived from the sun-illuminated SD. As both Terra and Aqua spacecraft continue to drift from their nominal orbits, the SD calibration mechanism has been adapted to these drifts, especially in terms of characterizing the transmission screen function. This paper also presents the utility of this scattering light data to support the RSB calibration in the post-nominal orbit drift era of operations.

The MODIS instruments onboard the Terra and Aqua satellites have provided continuous global observations for science research and applications. The calibration accuracy and product quality have been maintained via routine monitoring and characterization of the instrument behavior. Electronic crosstalk in the thermal emissive bands (TEB) is a known issue, and its impact on the calibrated imagery has been mitigated via corrections derived from scheduled lunar observations. Mission-long crosstalk corrections for the Terra MODIS photovoltaic (PV) longwave infrared (LWIR) bands have been applied in Collection 6.1 (C6.1). In recent years, the electronic crosstalk between the Aqua PV LWIR bands has exhibited an increasing downward trend in the crosstalk coefficients. Just like Terra MODIS, this affects the Level-1B (L1B) product’s measurement accuracy and image quality. These artifacts were further amplified after the safe mode event in March 2022. Starting in April 2022, crosstalk corrections have been applied to the Aqua MODIS PV LWIR bands in the Level-1B product. However, due to the uncertainty associated with these crosstalk coefficients, an over- or under-correction was observed in the EV imagery in the form of residual striping. With the development of an Earth image assessment tool, the image striping has been quantified, and a subsequent correction was developed. The crosstalk coefficients for each receiving detector are additionally corrected to maintain the product’s image quality. Lastly, a crosstalk correction for select detectors in the MWIR bands is also applied to both MODIS missions in Collection 7.

The JPSS-3 VIIRS sensor has completed its pre-launch test program including measurements for characterizing the VIIRS relative spectral response (RSR) in support of the Sensor and Environmental Data Records (SDR and EDR, resp.) that will be generated from VIIRS on-orbit observations. Government team subject matter experts of the VIIRS DAWG have analyzed the VIIRS spectral measurements and produced the VIIRS spectral characterization, in the form of band-average and supporting detector level RSR for each VIIRS band. The characterization is based upon the analysis of independent SpMA dual monochromator (all bands) and GSFC GLAMR laser system (reflectance bands only) spectral measurements. The SpMA and GLAMR measurements for reflectance bands (DNB LGS and MGS, I1-I3, M1-M11) were combined to produce a “fused” RSR. For emissive bands (I4, I5, M12-M16), the SpMA measurements provide the characterization. The effort has led to the VIIRS Version 2 RSR release, the official at-launch RSR characterization for the JPSS-3 VIIRS mission. The JPSS-3 RSR are a close match to those of JPSS-2. An assessment on compliance with spectral performance metrics finds that VIIRS band-average RSR are compliant on nearly all metrics, with only a single minor exception. The Version 2 RSR release is available under EAR99 restrictions to the science community on the restricted access NASA Sharepoint.