NOAA-21 VIIRS screen transmittance functions derived from on-orbit calibration dataLei, Ning; Xiong, Xiaoxiong
doi: 10.1117/12.3027458pmid: N/A
The third Earth observing Visible Infrared Imaging Radiometer Suite (VIIRS) is on the recently launched NOAA-21 satellite. Like its predecessors on the SNPP and NOAA-20 satellites, the VIIRS provides daily global geometrically and radiometrically calibrated observations via its 22 spectral bands from 0.41 to 12 mm. VIIRS has 14 reflective solar bands (RSBs), covering wavelengths from 0.41 to 2.25 m. On orbit, the RSBs are radiometrically calibrated through a sunlit solar diffuser (SD). The on-orbit change of the SD’s bidirectional reflectance distribution function (BRDF) is determined by using the onboard solar diffuser stability monitor (SDSM). An SDSM screen and an SD screen, both with holes to let sunlight pass through, are involved in the calibration. The SDSM screen relative transmittance and the products of the SD screen transmittance and the SD BRDF for the SDSM and the telescope SD views were measured prelaunch. But large errors are associated with the prelaunch SDSM screen function. As a result, the SDSM measured SD BRDF onorbit change factor versus time data points have large unrealistic undulations. To improve the screen functions, satellite yaw maneuvers were performed and the calibration data from the yaw maneuver orbits were used to rederive the screen functions. Here, we apply a previously developed methodology with a slight improvement to further refine the screen functions, using the calibration data not only from the yaw maneuver orbits but also from a small portion of the regular orbits. With the updated screen functions, the SDSM determined SD BRDF on-orbit change factors, as well as the retrieved NOAA-21 VIIRS RSB radiometric gains, are much smoother functions of time.
In-flight characterization of the nonlinearity and instrumental noise of the AIRSPagano, Thomas S.; Broberg, Steven E.; Manning, Evan M.; Aumann, Hartmut H.; Licata, Stephen J.; Mathews, William S.; Overoye, Kenneth
doi: 10.1117/12.3028563pmid: N/A
The Atmospheric Infrared Sounder (AIRS) was launched on May 4, 2002 on the NASA Earth Observing System (EOS) Aqua spacecraft. AIRS measures the hyperspectral upwelling spectral radiance of the Earth in the infrared from 3.7- 15.4μm in 2378 channels. Instrument raw digital counts are converted to radiances using a hybrid physical, empirical approach that maintains high measurement accuracy with SI traceability. Before launch, a comprehensive On-board Calibration Plan was developed that configures the AIRS instrument into certain modes that enable characterization and/or validation of various performance parameters. Ten of the eleven on-board tests have been performed on-orbit with varying frequencies. This paper addresses three of the tests that focus on the radiometric performance of the instrument including instrumental gain and noise, non-linearity, non-Gaussian noise and stray light effects on the On-Board Calibrator (OBC) Blackbody and Space View (SV), respectively. The Guard Test, C1, uploads A only and B only detector redundancy gain tables that allow characterization of the noise and gain in normal operational mode. The Space View Noise Test, C8, stops the scan mirror while AIRS views space, providing a long, continuous, measurement of a cold target for characterization of instrumental noise and drift. The OBC Float Test, C5, turns off the OBC blackbody to provide a range of observational temperatures to the instrument for calibration of the nonlinearity. All tests show excellent stability of the instrument response, albeit regular non-automated adjustments to the detector redundancy has been required throughout the mission due to normal instrumental aging and radiation hits. Despite the changes, the AIRS Calibration Team has managed to maintain the number of active channels to the values experienced shortly after launch for the life of the mission.
Entire mission striping and signal dependence assessment for SNPP, NOAA-20, and NOAA-21 VIIRSChang, Tiejun; Xiong, Xiaoxiong
doi: 10.1117/12.3028111pmid: N/A
The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments aboard the Suomi NPP (SNPP), NOAA-20 (N20), and NOAA-21 (N21) spacecraft have successfully provided Earth image products since 2011, 2017, and 2022, respectively. VIIRS has 22 bands with resolutions of 375 m and 750 m for the imaging and moderate resolution bands, respectively, covering a spectral range of 400-12,490 nm. Among them, moderate bands (M-band) 1 to 11 and imaging bands (I-band) 1 to 3 are reflective solar bands (RSBs), and M12 to M16 and I4 and I5 are thermal emissive bands (TEB). Each M-band has 16 detectors, and each I-band has 32 detectors. M-bands (1-5, 7, and 13) have dual-gain stages to enhance the measurement dynamic range. The nonlinear responses of RSB and TEB detectors were characterized during pre-launch testing. An on-board solar diffuser tracks any linear response degradation for RSB detectors. For TEB detectors, an on-board blackbody (BB) tracks linear response change, and a scheduled BB warmup and cooldown event is used to monitor the non-linearity change. Unknown biases or uncertainty in the linear or nonlinear calibration coefficients between different detectors can cause unwanted striping in the image product. In this work, the striping is assessed for all RSB and TEB of the three VIIRS instruments on SNPP, N20, and N21. The assessment is performed using the NASA Level 1B reflectance and radiance products over the entire globe to analyze the aggregate striping and any changes over time. For each band of the three instruments, the striping assessment is performed at different signal levels to analyze their nonlinearity. The striping assessment is also performed separately for both gain stages of the dual-gain bands. The motivation of this work is to have a comprehensive understanding of VIIRS striping and its signal dependency to support calibration improvements and to reduce the striping over a broad radiance range.
Spatiotemporal satellite image fusion using nanosatellite dataKim, Yeji; Kim, Hyun Ok
doi: 10.1117/12.3029007pmid: N/A
As Earth observation satellite data grows, the need for higher temporal and spatial resolutions becomes crucial for accurate monitoring and decision-making. Achieving both of high temporal and spatial resolutions is challenging due to trade-offs in sensor design; for instance, Sentinel-2 and Landsat offer higher temporal but lower spatial resolution, while high-resolution sensors like NEONSAT with small coverages. This study introduces a deep learning-based spatiotemporal image fusion method that integrates multi-sensor data, combining low and high spatial resolution images from different sensors over time. The method estimates adjustment features from temporal and spatial differences, using fusion and convolutional blocks to enhance resolution. Trained on Sentinel-2 and Planet images, the method effectively maintains spectral integrity and enhances spatial details under varying conditions. By leveraging multi-sensor data, this approach addresses sensor quality and stability issues, expanding NEONSAT’s potential applications. Future research will refine the method by incorporating more datasets, including NEONSAT imagery, to advance spatiotemporal fusion techniques.
A deep neural network for achieving spectrally consistent and seamless infrared radiance measurements across geostationary satellite domainsScarino, Benjamin; Doelling, David R.; Smith, William L.; Haney, Conor; Bhatt, Rajendra; Gopalan, Arun; Khakurel, Prathana
doi: 10.1117/12.3032494pmid: N/A
The NASA Clouds and the Earth's Radiant Energy System (CERES) project provides the scientific community with observed top-of-atmosphere (TOA) shortwave and longwave fluxes for climate monitoring and climate model validation. To achieve this goal, CERES relies on TOA broadband fluxes derived from geostationary satellite (GEO) imagery to account for the diurnal flux variations between the CERES observation intervals. Consistent global flux derivation depends on accurate and consistent cloud retrievals. Scene-dependent spectral measurement inconsistency of the instruments that make up the contiguous ring of GEO observations (GEO-Ring), as well as limb darkening effects, can cause discontinuities in derived cloud properties and radiative fluxes at the boundaries of adjacent imager domains. Although the algorithms utilize radiative transfer models to account for instrument-band-dependent atmospheric correction and viewing zenith angle (VZA) dependency, small discontinuities may persist due to uncertainties inherent to the multiple imager-specific algorithms. Furthermore, while hyperspectral-instrument-based spectral band adjustment factors may effectively account for spectrally induced bias, they are less effective at reducing variance owed to the specific composition of the viewed scene, which is challenging to robustly characterize. As such, this article highlights the use of a deep neural network (DNN) to resolve spectral- and VZA-induced biases between GEO-Ring imagers. The DNN uses available infrared (IR) channels from the GEO instruments, along with viewing and solar illumination geometry, to estimate homogenized, VIIRS-like IR radiances for use in the GEO cloud algorithm. This approach is effective at mitigating scene-dependent spectral variance and VZA dependency, resulting in consistent radiance measurements across the GEO-Ring, thereby leading toward a more seamless global cloud assessment.
A NIR spectrometer onboard Uvsq-Sat NG satellite for observing greenhouse gasesClavier, Cannelle; Meftah, Mustapha; Rouanet, Nicolas; Mariscal, Jean-François
doi: 10.1117/12.3028687pmid: N/A
Uvsq-SatNG is a Six-Unit GHG CubeSat dedicated to the simultaneous measurements of the Earth Radiation Budget and greenhouse gases. This space mission aims to evaluate the potential of using a compact spectrometer mounted on a CubeSat for determining atmospheric GHG concentrations (CO2, CH4). This spectrometer operates in the Near-Infrared (NIR) range, typically between 1200 to 2000 nm, which is an ideal wavelength range for detecting and measuring the spectral signatures of the most significant greenhouse gases. The inclusion of such a spectrometer on Uvsq-SatNG represents an important step forward in climate research. It not only provides essential data for environmental science but also demonstrates the growing capability of satellite technology to support crucial observations of our planet’s changing climate. The aim of this article is to present an optical configuration for this instrument. The performance achieved with this design will be presented. We will see if the proposed instrument design is capable of measuring greenhouse gas concentrations with good accuracy (absolute measurements of ±4.0 ppm with an annual stability of ±1.0 ppm for CO2, absolute measurements of ±25.0 ppb with an annual stability of ±10.0 ppb for CH4).
Prelaunch radiometric calibration of the J4 VIIRS reflective solar bandsAngal, Amit; Moyer, David; Ji, Qiang; Link, Daniel; Xiong, Xiaoxiong
doi: 10.1117/12.3027849pmid: N/A
The Joint Polar Satellite System 4 (JPSS-4) Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is the fifth in a series (S-NPP VIIRS, JPSS-1,2,3 VIIRS) of highly advanced polar-orbiting environmental satellites. JPSS-4 VIIRS underwent a comprehensive sensor-level Thermal Vacuum (TVAC) testing at the Raytheon Technologies El Segundo facility in the fall of 2023. While the test program provided characterization for many spatial, spectral, and radiometric aspects of the VIIRS sensor performance, this paper focuses on the radiometric performance of the 14 reflective solar bands (RSB) that cover the wavelength range from 0.41 to 2.3 μm. Key calibration parameters, such as the instrument gain, signal-to-noise ratio (SNR), dynamic range and radiometric uniformity, were derived in a TVAC environment for both the primary and redundant electronics at three instrument temperature plateaus: cold, nominal, and hot. This paper shows that all the JPSS-4 VIIRS RSB detectors have been well characterized, with the key performance metrics being comparable to those of the previous VIIRS instruments. Comparison of radiometric performance to sensor requirements, as well as a summary of key sensor testing and performance issues, will also be presented.
Quantifying uncertainties in Atmospheric Infrared Sounder (AIRS) spatial response functionsYanovsky, Igor; Pagano, Thomas S.; Manning, Evan M.; Broberg, Steven E.; Sutin, Brian M.
doi: 10.1117/12.3029935pmid: N/A
Quantifying uncertainties in Atmospheric Infrared Sounder (AIRS) spatial response functions (SpatialRFs) is critical for enhancing the quality of climate data records. Previously, AIRS in-flight SpatialRF calibrations have utilized an incomplete set of pre-flight data obtained during instrument assembly. In our current work, we combined various pre-flight data sets to interpolate a complete set of pre-flight SpatialRFs. Concurrently, we employed two consecutive days of AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) data to independently retrieve in-flight SpatialRFs for multiple channels and scan angles. Our methodology, based on our previous work, aligns AIRS and MODIS radiances to derive spatially corrected SpatialRFs. This paper compares in-flight SpatialRFs obtained from consecutive days and examines the discrepancies between pre-flight SpatialRFs from a completed set and in-flight SpatialRFs. Employing the total variation distance metric with two days of consecutive data revealed that the average uncertainties in in-flight SpatialRFs are approximately 5%, attributed mainly to noise, which establishes a baseline. In contrast, pre-flight SpatialRFs displayed an average uncertainty of about 16% when compared to the values derived in-flight. Our findings underscore the value of reconstruction techniques to derive in-flight SpatialRFs to validate pre-flight measurements, which is vital for ensuring the long-term reliability and precision of climate data records obtained from AIRS.
PACE OCI on-orbit solar calibrationMcIntire, Jeff; Lee, Shihyan; Eplee, Robert E.; Meister, Gerhard
doi: 10.1117/12.3027461pmid: N/A
The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, recently launched on February 8, 2024, has a payload of two polarimeters and the Ocean Color Instrument (OCI). OCI is the next generation sensor for ocean color science from low Earth orbit, drawing heritage from sensors such as MODIS and SeaWiFs, but with increased spectral coverage and improved accuracy. OCI is a grating spectrometer with hyperspectral coverage from the ultraviolet (about 315 nm) to near-infrared (about 895 nm), with additional filtered channels in the short-wave infrared (940 nm – 2260 nm). In order to maintain the high levels of accuracy demanded by the science community, the sensor calibration is monitored on-orbit through daily observations of the Sun. These solar observations are made via one of two quasi-volume diffusers, whose BRDF was measured prior to launch, during a dedicated spacecraft maneuver. One diffuser is used on a daily basis, while the other is used on a monthly basis to track any changes in the daily diffuser performance. These solar observations are used to monitor variations in the instrument gain over time for all spectral bands, and update the gain in the calibration algorithm. The methodology used to estimate the gain variation and the results of this variation since launch are presented in this work.
PACE OCI lunar calibration: initial resultsLee, Shihyan; Pratt, Frederick; Eplee, Robert E.; McIntire, Jeffrey; Meister, Gerhard
doi: 10.1117/12.3027692pmid: N/A
Launched in February 2024, the Ocean Color Instrument (OCI) onboard NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission has started performing its monthly lunar calibrations at ±7 degrees lunar phase angle in March 2024. In this paper, we will describe the OCI lunar calibration methodology and show the results of lunar calibration events during the initial months of PACE/OCI operation. A key difference of OCI lunar calibration from heritage sensors is that the lunar disk integrated irradiance is computed from lunar pixel radiance and sampling distance instead of the instrument’s IFOV. PACE provided a near constant sweep rate during lunar calibration allowing accurate determination of OCI pixel sampling extent. OCI performs lunar calibration in baseline science mode with 282 hyperspectral bands from 315 – 895 nm and 7 shortwave infrared bands (940 - 2260 nm). For each OCI band, we compute the integrated lunar disk irradiance, and compare the result with a lunar irradiance model (ROLO) prediction. The early results presented here clearly show that OCI’s lunar image acquisition is working as intended and will provide accurate data for OCI’s on-orbit radiometric characterization. The hyperspectral lunar irradiances provided by OCI are expected to become a valuable dataset for the evaluation of lunar irradiance models.