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NASA NTRSDate not supplied

CLARREO Pathfinder as a SI-traceable Reference for Satellite Intercalibration

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.community.

Hyperspectral↗

NASA NTRSDate not supplied

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

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

DCC↗

NASA NTRS2022

A Compilation of Global Bio-Optical in Situ Data for Ocean Colour Satellite Applications – Version Three

A global in situ data set for validation of ocean colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI) is presented. This version of the compilation, starting in 1997, now extends to 2021, which is important for the validation of the most recent satellite optical sensors such as Sentinel 3B OLCI and NOAA-20 VIIRS. The data set comprises in situ observations of the following variables: spectral remote-sensing reflectance, concentration of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficient, and total suspended matter. Data were obtained from multi-project archives acquired via open internet services or from individual projects acquired directly from data providers. Methodologies were implemented for homogenization, quality control, and merging of all data. Minimal changes were made on the original data, other than conversion to a standard format, elimination of some points, after quality control and averaging of observations that were close in time and space. The result is a merged table available in text format. Overall, the size of the data set grew with 148 432 rows, with each row representing a unique station in space and time (cf. 136 250 rows in previous version; Valente et al., 2019). Observations of remote-sensing reflectance increased to 68 641 (cf. 59 781 in previous version; Valente et al., 2019). There was also a near tenfold increase in chlorophyll data since 2016. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) are included in the final table. By making the metadata available, provenance is better documented and it is also possible to analyse each set of data separately.

ocean color↗

NASA NTRS2023

Evaluation of Systematic Errors on Polarization Parameters from POLDER Instrument Data for Use In CLARREO Pathfinder-VIIRS Intercalibration

One of the CLARREO Pathfinder (CPF) mission’s science objectives is to intercalibrate the reflective solar bands of the NOAA-20 VIIRS instrument against high-accuracy CPF measurements utilizing coincident, co-angled, and co-located footprints acquired over diverse Earth targets. To alleviate the effect of high polarization sensitivity of select VIIRS channels on intercalibration analysis, the CPF team will limit the intercalibration footprints over low-polarized scene types, which will be identified based on an empirical estimation of their degree and angle of polarization (DOP and AOP) using POLDER data. This paper describes the methodology for evaluating systematic errors in the estimation of DOP and AOP for Earth-reflected radiances using POLDER’s polarized bands and investigates their potential impact on CPF-VIIRS intercalibration uncertainty. The systematic errors were found to be less than 0.01 for DOP and less than 2.2 deg. for AOP, which will have a negligible impact on CPF-VIIRS intercalibration uncertainty.

polarization↗

NASA NTRSDate not supplied

Deriving a Suite of Climate Data Records from 21-years of Sounder Observations

Two retrieval algorithms, a Single Field-of-view Sounder Atmospheric Product (SiFSAP) Level 2 algorithm and a Climate Fingerprinting Sounder Product (ClimFiSP) Level 3 algorithm, have been developed at NASA Langley Research Center. In this presentation, we will demonstrate the radiance closure build into these two algorithms. This is possible due to the use of a principal-component-based radiative transfer model (PCRTM). The PCRTM enables the inclusion of all available spectral information from hyperspectral IR sounders. It also has fast and accurate capability of modeling observed cloudy radiance spectra directly. The SiFSAP, which fits sounder radiance spectra using PCRTM as forward model and an optimal estimation as inverse model, has 3-times higher spatial resolution and 9-times denser data products comparing to current NASA and NOAA operational IR sounder products. With great support from NASA sounder SIPS, the SiFSAP algorithm has been delivered to NASA GES DISC for L2 and L3 data generation and releasing. The ClimFiSP uses a spectral fingerprinting method to directly generate L3 data products from spatiotemporally averaged L1 data. The goal of ClimFiSP is to generate high-quality climate data records (CDRs) from multiple IR sounders (e.g. Aqua AIRS, SNPP CrIS, NOAA-20 and NOAA-21 CrIS) using a consistent retrieval methodology. Using CHIRP L1 data, we have generated 20-years of CDRs for atmospheric temperature, water vapor, and trace gas profiles, as well as cloud and surface properties. The algorithm will be transitioned to Sounder SIPS soon and eventually to NASA GES DISC.

Xu Liu↗

NASA NTRSDate not supplied

Seasonal Surface Spectral Emissivity Derived From MODIS Data

Surface emissivity is essential for many remote-sensing applications including the retrieval of surface skin temperature from satellite-based infrared measurements, the determination of cloud detection thresholds, and the estimation of the surface longwave radiation emission, an important component of the energy budget of the surface-atmosphere interface. The CERES (Clouds and the Earth’s Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties from the MODIS on Terra and Aqua and from the VIIRS on NOAA-19 and NOAA-20 orbiters to produce combined global radiation and cloud property data sets. Zhou et al. (IEEE Trans. Geosci. Remote Sens., 49, 2011) used Infrared Atmospheric Sounding Interferometer (IASI) data to create a high spectral resolution surface emissivity atlas for remote sensing and modeling applications. The IASI measures spectral radiances between 3.62 and 15.5 μm. The VIIRS I4 channel width is from 3.55 to 3.93 μm, while MODIS Band 20 is from 3.66 to 3.84 m. Comparisons of top-of-atmosphere (TOA) radiance calculations with MODIS and VIIRS observations for these bands relative to bands in the mid-infrared suggest that the IASI emissivity atlas near 3.7 µm may not be suitable for CERES cloud retrievals. In this paper, the IASI emissivities for the VIIRS and MODIS bands centered near 11m are used to derive surface skin temperature from nighttime MODIS/VIIRS data. The Goddard Earth Observing System for Instrument Teams (GEOS-IT) numerical weather analyses provide temperature and water vapor profiles fused to correct the observed radiances for atmospheric absorption and emission. Global seasonal emissivity maps are then derived for the VIIRS and MODIS 3.7-m bands that are consistent with the derived skin temperatures and the observed TOA radiances. These seasonal climatology maps are validated and will be used in CERES Edition 5 and other CERES-related cloud retrieval algorithms to provide improved clear-sky radiances and derived cloud properties.

Surface Emissivity↗

NASA NTRSDate not supplied

Using DSCOVR EPIC as an Additional Calibration Reference to Radiometrically Scale the Geo Imagers for the NASA CERES Project

The NASA CERES project provides climate-quality observed TOA and calculated surface fluxes to the climate community. The CERES instruments are mounted on the Aqua, Terra, NPP, and NOAA-20 low earth orbiting (LEO) satellites, where they are used alongside the VIIRS and MODIS based cloud properties necessary for converting CERES radiance observations into fluxes. The CERES SYN1deg product provides the regional hourly fluxes in between the Terra and Aqua/NOAA-20-CERES observations based on geostationary imager (GEO) radiances. The GEO radiances are radiometrically scaled to the MODIS or VIIRS calibration references. The GEO and MODIS inter-calibration events are limited by the Aqua-MODIS or VIIRS local equator crossing time of 1:30 PM. The DSCOVR satellite orbits the Lagrange-1 (L1) point about 1.5 million kilometers from Earth, and the Earth Polychromatic Imaging Camera (EPIC) instrument onboard DSCOVR has a constant view of the sunlit side of the Earth while taking images ranging from the UV to the NIR throughout the day. While the EPIC sensor has no onboard calibration systems, multiple inter-calibration studies have indicated that EPIC is radiometrically stable, which allows it to potentially be used as a transfer radiometer between imagers. This study will assess the viability of using EPIC as a consistent and stable calibration source for GEO imagers. EPIC will be inter-calibrated with Himawari-8 that has been radiometrically scaled with Aqua. The Himawari-8 based EPIC calibration gains will be verified by the EPIC calibration gains determined directly from Aqua-MODIS matches. The EPIC calibration gains based on Himawari-8 will be stratified by local time to determine any diurnal dependence of the GEO/EPIC calibration strategy.

C O Haney↗

NASA NTRSDate not supplied

Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder Intercalibration Data Analysis Strategy

One of the prime science objectives of NASA’s Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission is to acquire unprecedentedly accurate Système Internationale (SI)-traceable Earth-view measurements that can be used as reference for intercalibrating the Clouds and the Earth’s Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard NOAA-20 satellite. The hyperspectral nature of CPF measurements will significantly reduce spectrally induced biases when intercalibrating multiband or broadband satellite instruments with CPF. This advancement eliminates the requirement for spectral band adjustment factors, representing a substantial improvement in sensor intercalibration studies. The CPF intercalibration team is aiming to achieve a maximum intercalibration methodology uncertainty of 0.3 % (k=1). Our studies have revealed that the most significant contribution to the targeted uncertainty budget originates from the combined effects of spatial and temporal matching errors. Spatial matching error arises from discrepancies in CPF and target instrument pixel resolution and geolocation uncertainty, while temporal matching error is caused by changes in scene radiances over time, occurring between when the target and reference instruments observe the same scenes. To estimate the maximum expected uncertainty contribution from these sources, spatial and temporal matching noise analyses were conducted using algorithmically filtered Landsat 9 Operational Land Imager (OLI) and Geostationary Operational Environmental Satellite (GOES)-16 ABI CONUS scan data as proxies for CPF and target instruments. In the upcoming conference presentation, we will elaborate on the methodology employed in these experiments, provide details of the data filtering algorithms, and present results of the spatial and temporal matching uncertainty analyses.

Intercalibration↗

NASA NTRSDate not supplied

Progress Towards a Common CERES Cloud Mask Algorithm for MODIS and VIIRS: Evaluation using CALIOP Data

For over two decades The Clouds and the Earth’s Radiant Energy System (CERES) project has endeavored to produce a long-term global climate data record for detecting changes in the Earth’s radiation budget and to improve understanding of how clouds contribute to those changes. CERES incorporates cloud information derived from passive narrowband satellite imaging radiometers, and over the course of the project different instruments have contributed to this effort, namely the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS).Cloud properties have been derived from MODIS on the Aqua satellite for CERES since 2002,and VIIRS on the NOAA-20 satellite launched in 2017 will continue the cloud record once Aqua-MODIS reaches the end of its operational lifetime. However, MODIS and VIIRS have different spectral capabilities and characteristics which complicates our ability to seamlessly transition the record from MODIS to VIIRS. This study evaluates some of the recent algorithm modifications incorporated by the CERES Cloud Working Group towards developing a unified cloud mask algorithm for MODIS and VIIRS that utilizes a set of spectral bands common to both instruments. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products are used to evaluate MODIS and VIIRS regional cloud fraction estimates and identify areas where improvements can be made. The cloud mask algorithm relies on computed estimates of cloud-free top-of-atmosphere radiances to differentiate cloudy and cloud-free imager pixels. The unified cloud mask algorithm currently under development uses a reduced number of spectral bands common to both MODIS and VIIRS and so relies on the accuracy of these simulated cloud-free radiances more heavily than predecessor algorithms, i.e., the CERES Edition 4 cloud mask, which use as much spectral information as available on each imager with less consideration for cross-platform consistency. Our validation strategy using CALIOP data is also described. The CALIOP observations are critical for assessing cloud detection accuracies and for independently confirming cloud-free conditions which enables a more robust evaluation of the simulated cloud-free radiances for biases due to factors such as view angle and the spectral dependence of water vapor absorption. These effects are known to differ for the two satellite instruments. Comparisons of MODIS and VIIRS cloud fractions are presented in context with estimates from CALIOP and from the CERES Edition 4 cloud mask algorithm to gauge current progress in developing accurate and consistent MODIS and VIIRS cloud properties for CERES.

CERES↗

NASA NTRS2023

Calibration of the SNPP and NOAA 20 VIIRS Sensors for Continuity of the MODIS Climate Data Records

Accurate long-term sensor calibration and periodic re-processing to ensure consistency and continuity of atmospheric, land and ocean geophysical retrievals from space within the mission period and across different missions is a major requirement of climate data records. In this work, we applied the Multi-Angle Implementation of Atmospheric Correction (MAIAC)-based vicarious calibration technique over Libya-4 desert site to perform calibration analysis of Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20 satellites. For both VIIRS sensors we characterized residual linear calibration trends and cross-calibrated both sensors to MODerate resolution Imaging Spectroradiometer (MODIS) Aqua regarded as a calibration standard. The relative spectral response (RSR) differences were accounted for using the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS) hyperspectral surface reflectance data. Our results agree with independent vicarious calibration results of both the MODIS/VIIRS Characterization Support Team as well as the CERES Imager and Geostationary Calibration Group within estimated uncertainty of 1–2%. Analysis of MAIAC geophysical products with the new calibration shows a high level of agreement of MAIAC aerosol, surface reflectance and NDVI records between MODIS and VIIRS. Excluding high aerosol optical depth (AOD), all three sensors agree in AOD with mean difference (MD) less than 0.01 and residual mean squared difference rmsd ∼ 0.04. Spectral geometrically normalized surface reflectance agrees within rmsd of 0.003–0.005 in the visible and 0.01–0.012 at longer wavelengths. The residual surface reflectance differences are fully explained by differences in spectral filter functions. Finally, difference in NDVI is characterized by rmsd ∼ 0.02 and MD less than 0.003 for NDVI based on VIIRS imagery bands I1/I2 and less than 0.01 for NDVI based on VIIRS radiometric bands M5/M7. In practical sense, these numbers indicate consistency and continuity in MAIAC records ensuring the smooth transition from MODIS to VIIRS.

MAIAC↗

NASA NTRS2023

Early Mission Radiometric Performance of NOAA-21 VIIRS Reflective Solar Bands

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.

N21 VIIRS↗

NASA NTRS2023

Using Dome Concordia to Characterize the Long-Term Stability of VIIRS Thermal Emissive Bands

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 long-term 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.

Amit Angal↗

NASA NTRSDate not supplied

Open Source Principles Utilized by the CERES Edition 5 Level-3 Framework

The Clouds and the Earth’s Radiant Energy System (CERES) Science Team integrates and fuses observations from six CERES instruments aboard the Terra, Aqua, S-NPP, and NOAA-20 missions with data from twenty-five geostationary imagers, in creating a nearly 25-year, ongoing record of the Earth’s radiation budget. In preparation for the next version of CERES data products, the team has been exploring software development methods leveraging open-source principles and software to streamline data product configuration and algorithm implementation. This effort will provide robust software for production while maintaining greater flexibility for the algorithm developers to explore new science.

T. Nelson Hillyer↗

NASA NTRSDate not supplied

Open Source Principles Utilized by the CERES Edition 5 Level-3 Framework

Thomas N Hillyer↗

NASA NTRSDate not supplied

Data Simulation Using VLIDORT and PCRTM and its Use for Radiometric Calibration of Hyperspectral UV-NIR-SWIR Sensors

Using the vector linearized discrete ordinate radiative transfer model (VLIDORT), a multiple-scattering multi-layer discrete ordinate scattering codes, coupled with a fast principal component (PC) radiative transfer model (PCRTM), we can simulate the radiation fields for hyperspectral UV-NIR-SWIR sensors from 250nm to 2500nm with a very high speed. Since the accurate gas absorptions, molecules and aerosol/cloud particle scatterings, and the surface reflectance have been considered in these simulations, these model data can be used for satellite or airborne sensor design, characterization, or end-to-end system level uncertainty assessment. Comparison of the modelled data with measured results has been a general practice for operational satellite sensor calibrations, such as the Ozone Mapping and Profiler Suite (OMPS) onboard on SNPP and NOAA-20. This presentation will give more details of this simulation system and models. Some examples of the generation of simulations data for CLARREO PathFinder (CPF) and the Surface Biology and Geology (SBG), as well as some examples to use these data for CPF and OMPS radiometric calibration will be presented.

Xiaozhen Xiong↗

NASA NTRSDate not supplied

On-Orbit Calibration Assessment of NOAA-21 VIIRS Thermal Emissive Bands and Implications for JPSS-4 VIIRS

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard the NOAA-21 (N21) satellite has been successfully operating for over three years collecting valuable scientific measurements. A large suite of weather forecasting models and scientific research applications are supported with the VIIRS measurements from N21 combined with those acquired from the VIIRS instrument onboard the S-NPP and NOAA-20 spacecraft. Among the 22 VIIRS spectral bands, there are seven thermal emissive bands (TEB) covering the 3.7 to 12.2 µm spectral range at two different spatial resolutions. The VIIRS TEB detectors are calibrated onboard using a blackbody at a controlled temperature and a space view for background signal measurement. In this paper, we discuss the on-orbit performance of the N21 VIIRS TEB using various parameters such as the detector gain, noise, and offset. This on-orbit assessment provides critical insights into instrument behavior and calibration performance that will inform pre-launch testing and post-launch validation strategies for the upcoming JPSS-4 VIIRS mission scheduled for launch in 2027. The methodologies and lessons learned from characterizing the N21 TEB performance will enable more efficient and comprehensive radiometric assessment of the next VIIRS instrument. Specific focus is placed on identifying performance trends and anomaly signatures observed during the N21 commissioning phase that can enhance the JPSS4 instrument checkout procedures and accelerate the transition to routine on-orbit operations. The established performance baselines and uncertainty estimates will serve as an acceptance criterion for the JPSS-4 commissioning activities, ensuring mission readiness and data continuity for operational users.

Amit Angal↗

NASA NTRSDate not supplied

PRELIMINARY JPSS-3 VIIRS POLARIZATION SENSITIVITY AND COMPARISON WITH S-NPP, JPSS-1 AND -2

The Visible-Infrared Imaging Radiometer Suite (VIIRS) was first launched on-board the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft in October of 2011. There have been three subsequent builds of the VIIRS sensor for the Joint Polar Satellite System (JPSS) program with JPSS-1, -2 and -3 having launch dates of November 2017, March 2022 and 2026 respectively. There is also a JPSS-4 VIIRS, that is in hardware integration during 2020, with a launch date of 2031. VIIRS has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). Ocean Color/Chlorophyll (OCC) products use calibrated Science Data Records (SDRs) for bands M1-M7(0.412-0.865μm) to compute their ocean chemistry products. These bands require accurate polarization sensitivity characterization to compensate for polarized upwelling Rayleigh scatter and produce accurate OCC Environment Data Products (EDRs). VIIRS polarization sensitivity requirement failures have driven hardware modifications to the bandpass filters and dichroic beam splitter over the program. This paper will discuss the preliminary JPSS-3 polarization results and how these hardware modifications, as the JPSS program progresses, have affected the sensor performance. Comparisons of the polarization sensitivities between sensor builds will be discussed along with the hardware modifications that contributed to their differences.

VIIRS↗

NASA NTRSDate not supplied

Preliminary JPSS-3 VIIRS Polarization Sensitivity and Comparison with S-NPP, JPSS-1 and -2

The Visible-Infrared Imaging Radiometer Suite (VIIRS) was first launched on-board the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft in October of 2011. There have been three subsequent builds of the VIIRS sensor for the Joint Polar Satellite System (JPSS) program with JPSS-1, -2 and -3 having launch dates of November 2017, March 2022 and 2026 respectively. There is also a JPSS-4 VIIRS, that is in hardware integration during 2020, with a launch date of 2031. VIIRS has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). Ocean Color/Chlorophyll (OCC) products use calibrated Science Data Records (SDRs) for bands M1-M7 (0.412-0.865μm) to compute their ocean chemistry products. These bands require accurate polarization sensitivity characterization to compensate for polarized upwelling Rayleigh scatter and produce accurate OCC Environment Data Products (EDRs). VIIRS polarization sensitivity requirement failures have driven hardware modifications to the bandpass filters and dichroic beam splitter over the program. This paper will discuss the preliminary JPSS-3 polarization results and how these hardware modifications, as the JPSS program progresses, have affected the sensor performance. Comparisons of the polarization sensitivities between sensor builds will be discussed along with the hardware modifications that contributed to their differences.

VIIRS↗