Launched in November 2017, the National Oceanic and Atmospheric Administration-20 (NOAA-20) Visible Infrared Imaging Radiometer Suite (VIIRS) has successfully operated over five years and produced high-quality sensor data records (SDRs), which have significantly contributed to the Earth’s environmental and climate change studies. The VIIRS instrument collects data in the reflective solar bands (RSBs) from bands M1 to M11 and I1 to I3 with two spatial resolutions of 375 m for imaging ($I$) bands and 750 m for moderate resolution ($M$) bands covering a wavelength range from 401 to 2284 nm. For the RSBs on-orbit radiometric calibration, VIIRS primarily uses solar diffuser (SD) observations along with alternative long-term lunar calibrations and deep convective cloud (DCC) trends. The NOAA VIIRS SDR team observed upward long-term trends after three years in the lunar calibration coefficients (called lunar F-factors) compared to the initial on-orbit SD F-factors. These long-term lunar trend changes were validated with the DCC observation results and the operational radiometric calibration coefficient (called F-PREDICTED) lookup table (LUT) was updated in November of 2021, which was proportional to observed radiance. After five years of on-orbit operations, the performance of the current operational F-PREDICTED LUT was evaluated in comparison with the long-term DCC trends. After application of the LUT, the results showed excellent on-orbit radiometric calibration stability providing confidence for the user communities of NOAA-20 VIIRS SDR products.

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the National Oceanic and Atmospheric Administration-21 (NOAA-21) satellite was launch on November 10, 2022, following the successful operations of the VIIRS onboard the Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 satellites. This article presents NOAA-21 VIIRS thermal emissive bands (TEBs) early on-orbit calibration performance, including instrument temperature telemetry trending, TEB gains, noise, and calibration stability as well as biases in the NOAA operational sensor data records (SDR). Different from S-NPP and NOAA-20, NOAA-21 VIIRS TEBs have experienced distinct on-orbit gain changes during its early mission, caused by detector responsivity degradations, mid-mission outgassing (MMOG), and the cold focal plane assembly setpoint temperature switch. The calibration stability and biases of NOAA-21 VIIRS TEB SDRs were analyzed by intercomparing with co-located Cross-Track Infrared Sounder (CrIS) observed and gap-filled spectra. NOAA-21 TEB SDRs have been stable, except for small changes caused by known VIIRS or CrIS instrument setting or calibration updates. VIIRS longwave infrared (LWIR) bands agree with CrIS within 0.1 K; M13 agrees with CrIS ~0.13 K. Calibration parameters derived from the spacecraft pitch maneuver data were applied for the first time in the operational processing, and LWIR scan angle and scene temperature-dependent biases were effectively reduced after that update. Similar to S-NPP and NOAA-20 VIIRS, NOAA-21 VIIRS TEBs also exhibit calibration anomalies during the blackbody warm-up/cool-down (WUCD) tests. NOAA-21 WUCD bias correction coefficients were developed and deployed to the operations for supporting sea surface temperature (SST) applications.

The Visible Infrared Imaging Radiometer Suite (VIIRS) is onboard the Suomi National Polar-orbiting Partnership (S-NPP) and the National Oceanic and Atmospheric Administration - 20 (NOAA-20) satellites. This study presents a method for estimating VIIRS Thermal Emissive Bands (TEB) Response Versus Scan (RVS) and calibration offsets simultaneously using on-orbit pitch maneuver data (METHOD2021). Raw Earth View (EV) RVS is estimated using an existing method (METHOD2019), with prelaunch RVS and calibration offsets as first guesses. Errors in the calibration offset are derived based on a prelaunch data-based assumption. Moreover, RVS and calibration offsets are optimized iteratively using the updated calibration coefficients until results converge. Compared to the METHOD2019, the METHOD2021 derived RVS is not affected by errors in the calibration offsets. Evaluation results using independent co-located Cross-track Infrared Sounder (CrIS) observations indicate that the METHOD2021 could effectively mitigate NOAA-20 scan angle and scene temperature dependent biases in M15-M16 and I5, as well as the cold bias in S-NPP M15. S-NPP TEB striping at cold scene temperatures can also be significantly reduced. Furthermore, NOAA-20 I5 and M15 measurements become more in family with S-NPP VIIRS and other radiometers at extremely low temperatures. Our analysis indicates that the impacts of the METHOD2021 and METHOD2019 on TEB SDRs are generally comparable. The METHOD2019 is simpler, while the METHOD2021 better explains the root causes of the VIIRS TEB scan angle and scene temperature dependent biases. Both can be used for improving VIIRS TEB on-orbit calibration, especially at cold scenes.

This article presents an improved radiance limit verification and saturation rollover flagging method for the Visible Infrared Imaging Radiometer Suite (VIIRS) reflective solar band (RSB) and thermal emissive band (TEB) sensor data records (SDRs). Platform (satellite)-dependent radiance limits are introduced to account for the different radiometric characteristics of the VIIRS onboard the Suomi National Polar-Orbiting Partnership (S-NPP) and the National Oceanic and Atmospheric Administration-20 (NOAA-20) satellites. Two reference band-based tests are added for better saturation rollover flagging. Evaluation results using NOAA-20 and S-NPP reprocessed and on-orbit SDRs indicate that saturation rollover flagging can be significantly improved. To date, the improved scheme of saturation rollover flagging is applied only to NOAA-20 and S-NPP M6. The application of this scheme to other RSB and TEB bands can be achieved by updating the Quality Assurance lookup table. Moreover, the issue of radiance and brightness temperature mismatch for NOAA-20 TEBs is also resolved. A VIIRS SDR algorithm code change for the improved method has been implemented in the NOAA operational processing for NOAA-20 and S-NPP since March 25, 2019. It can also be applied to the VIIRS onboard the future Joint Polar Satellite System satellites (J2–J4).

In the NOAA operational processing, the Thermal Emissive Band (TEB) data from the VIIRS onboard the NOAA-20 and S- NPP satellites are not calibrated if all scans in a granule are flagged as lunar intrusion into space view (SV). As a result, more than 100 NOAA-20 and S-NPP VIIRS single-gain TEB granules are un-calibrated each year. For M13 (dual-gain fire detection band), the number of un -calibrated granules due to lunar intrusion is doubled because of an additional bug in the operational processing software. This study presents a Lowest N Algorithm for calibrating VIIRS TEB during lunar intrusions. It takes advantage of the fact that the extent of the full moon image is smaller than the field of view of VIIRS SV. Moreover, the bug that affects M13 calibration was also fixed. A VIIRS SDR algorithm code change package has been implemented in the NOAA operational processing since March 30,2021.

In this paper, we present recent progress in the development of interactive integrated Cal/Val system enhanced by 3D globe visualization. Examples of two of such enhanced systems: Small satellite (Smallsat) integrated Cal/Val system (ICVS) in support of the Smallsat program and VIIRS Global Validation System (VGVS) are presented. For the Smallsat ICVS, the global contextual visualization of Global Navigation Satellite System (GNSS) Radio Occultation data enables orbital phasing analysis and temperature profile quality monitoring from the six COSMIC2 satellites. The 3D visualization of TEMPEST-D microwave SmallSat multi-channel observations facilitates geolocation accuracy and data inventory monitoring, both are critical to the inter-sensor Cal/Val. The VGVS consists of ~20 vicarious validation sites. Mission-long time series for instrument performance trending and degradation monitoring are supported. The interactive WebGL based 3D interface provides integrated monitoring of VIIRS multi-channel radiometric performance in the context of types, locations, radiometric uncertainties and stability of validation sites.

This paper presents NOAA-20 and S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Reflective Solar Bands (RSB) and Thermal Emissive Bands (TEB) Sensor Data Records (SDR) performance and recent improvements to support user communities. Results for NOAA-20 VIIRS and in 2019 are emphasized. NOAA-20 VIIRS geolocation errors are within ±100 m, comparable to S-NPP; RSBs have been stable after achieved validated maturity status, except that small upward trends were observed; TEBs agree with co-located Cross-track Infrared Sounder (CrIS) observations within ~0.1 K at nadir, more stable (relative to CrIS) compared to S-NPP TEBs in 2019. NOAA-20 RSBs continue bias ~2-4.5% lower than S-NPP. Three major improvements to VIIRS SDRs, including the new operational M6 saturation rollover flagging method, the operational TEB warm-up/cool-down bias correction, and the latest results for correcting NOAA-20 TEB scan angle/scene temperature dependent biases, are also presented to address users' concerns.

The NOAA-20 (N-20) VIIRS has successfully operated for more than two years since its launch in November 2017. Shortly after completing its initial instrument check-outs and post-launch testing (PLT) activities, the N-20 VIIRS sensor data records (SDR) achieved the beta, provisional, and validated maturity status in January, February, and April 2018, respectively. In this paper, we briefly describe the instrument on-orbit operation and calibration activities, provide an overall assessment of its on-orbit performance, and discuss the methodologies developed to maintain and improve sensor calibration and data quality. As illustrated in this paper, the N-20 VIIRS continues to perform with excellent stability, allowing high-quality environmental data records (EDR) to be generated from its well-calibrated SDR.

The National Oceanic and Atmospheric Administration (NOAA)-20 Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on November 18, 2017, and it has been operational for more than two years and follows the first Joint Polar Satellite System (JPSS) series of the Suomi National Polar-orbiting Partnership (S-NPP) mission. VIIRS has 14 reflective solar bands (RSBs) covering a spectral range of 0.41-2.3 μm. The primary source of RSB calibration is the solar diffuser (SD), and the time-dependent SD degradation is monitored by the SD stability monitor (SDSM). The initial instability of the SD degradation (H-factor) was resolved by updating SDSM sun screen transmittance function combining yaw maneuver data and on-orbit SDSM data sets. After the H-factor improvements, the VIIRS RSB calibration coefficients (F-factors) are updated and applied to the operational Sensor Data Record (SDR) product generation. To validate the SD F-factors, the lunar F-factors are calculated by using a lunar irradiance model and comparing the trend differences between them. Over the two years of operation, decreasing trends have been calculated with the SD F-factors, whereas constant lunar F-factors were observed in bands M1-M4. With these discrepancies, the operational F-factors remained unchanged since April 2018 because the deep convective cloud (DCC) and cross-calibration comparison results did not show any further degradations in these bands. All the possible radiometric calibration sources, such as SD and lunar F-factors, DCC trends, and cross-calibration results, are monitored, compared, and applied by the NOAA VIIRS SDR science team for the best quality of the VIIRS SDR product.

The NOAA-20 VIIRS, launched in late 2017, has produced one year of NOAA operational sensor data records (SDR) up-to-date. This study presents NOAA-20 VIIRS geolocation, Reflective Solar Bands (RSB), and Thermal Emissive Bands (TEB) on-orbit calibration performance to support user communities. I-bands/M-bands geolocation errors are comparable to S-NPP since February 6, 2018, according to global Control Point Matching analysis results. Daily Deep Convective Clouds statistics indicate that NOAA-20 RSB calibration has been stable since April 27, 2018. NOAA-20 RSBs are ~2-4% lower than those of S-NPP for most bands and are currently being studied. TEB calibration has been stable during nominal operations since March 15, 2018, after the mid-mission outgassing to resolve the longwave infrared responsivity degradation. TEBs radiances agree with co-located CrIS observations within 0.1 K. NOAA-20 VIIRS SDRs in the early mission have been reprocessed and will be released to the public in 2019.

The Suomi National Polar-orbiting Partnership Program Visible Infrared Imaging Radiometer Suite (VIIRS) thermal emissive bands (TEB) have been performing well during nominal operations since launch. However, small but persistent calibration anomalies are observed in all TEBs during the quarterly blackbody (BB) warm-up/cool-down (WUCD) events. As a result, the time series of daytime sea surface temperature (SST) (derived from bands M15-M16) show warm spikes on the order of 0.25 K. This paper suggests that VIIRS TEB WUCD biases are band dependent, with daily-averaged biases about -0.04 and 0.05 K for I4 and I5, and -0.05, -0.05, 0.11, 0.09, and 0.05 K for M12-M16, respectively. Two correction methods-Ltrace and WUCD-C-have been implemented and evaluated using colocated observations from the Cross-track Infrared Sounder (CrIS), radiative transfer simulations, and SST retrievals. Also an error in the National Oceanic and Atmospheric Administration operational processing was identified and fixed. Both correction methods effectively minimize WUCD-induced SST anomalies. The Ltrace method works well for I5, M12, and M14-M16, with residual biases about 0.01 K. The WUCD-C method, on the other hand, performs well to correct WUCD biases in all TEBs, with residual biases also about 0.01 K. However, it introduces warm biases relative to CrIS at cold scene temperatures, which requires further study. Applying nonequal BB thermistor weights improves calibration at BB temperature set points, but its impact on daily-averaged WUCD biases is small. The proposed methodologies may also be applied to the VIIRS onboard the follow-on Joint Polar Satellite System satellites.

The Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) provides day and night observation capabilities in the visible and near infrared spectrum from full sunlight to night light under lunar illumination conditions. The second VIIRS onboard the NOAA-20 (previously named JPSS-l) satellite was launched in late 2017, following six-years of successful operation by its predecessor on Suomi-NPP (S-NPP). NOAA-20 VIIRS sensor data records (SDR) achieved Beta maturity status on February 1, 2018 and provisional maturity status on February 19, 2018. After the operational SDR products (since February 1, 2018) were opened to the public, data users are greeted by a unique feature of NOAA-20 DNB, i.e., ~600 km (~300 samples) extended Earth view (EV) samples at the end of each scan, compared to S-NPP DNB and other VIIRS bands. This study introduces this unique feature, including its underlying cause, our prelaunch efforts to accommodate the extended EV data, preliminary on-orbit verification results, and new opportunities it provides.

Since launch in November 2018, the VIIRS on-board the NOAA-20 (or JPSS-1) satellite has completed its initial intensive on-orbit check-outs and several key calibration and validation activities scheduled to help evaluate sensor at launch performance. This paper provides a brief overview of NOAA-20 VIIRS on-orbit operation and calibration activities, presents early results derived from its on-board calibrators and lunar observations, and discusses potential improvements and future effort to assure sensor data product quality.

This paper presents the recent progress in the cal/val of the Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi National Polar Orbiting Partnership (NPP) since launch, and Joint Polar Satellite System (JPSS) J1 which will be launched in 2017. The Suomi NPP VIIRS instrument continues to perform well with a very stable calibration according to extensive comparisons with other instruments and at vicarious validation sites. The calibration accuracy for most bands meet the specification and user needs, although additional efforts are being made to meet more stringent needs such as ocean color applications. The VIIRS Sensor Data Records (SDR) have been operationally used at the Alaska National Weather Service, and have been used to generate a large number of environmental data records ranging from aerosols, fire, to ocean color, sea surface temperature, vegetation, and many others. However, since many updates have been made to the operational processing of VIIRS since launch, inconsistency exists in the long term data records. To address this issue, the VIIRS SDR team is preparing for the reprocessing of the VIIRS historical data using the new automated calibration module RSBAutocal, with the latest calibration coefficients. The reprocessed data will be more consistent over the entire history of VIIRS with all known corrections. At the same time, significant efforts are devoted to the prelaunch calibration of the JPSS J1 VIIRS. While in general the J1 VIIRS performance meets specifications, there are performance waivers and as a result, mitigations have to be developed. This includes the implementation of a new aggregation scheme to address the nonlinear response of the VIIRS Day/Night Band (DNB). Other waivers include the larger than expected polarization sensitivity which will impact the ocean color bands and additional corrections will be needed postlaunch. In addition, the team has also been performing a trade study for adding a water vapor band to future VIIRS. Many of these efforts have been documented in the VIIRS special issue in the remote sensing open access journal which is being finalized to reach out to a broader user community.

VIIRS sensor data records (SDR) will be reprocessed at NOAA using the latest coefficients and corrections in the algorithms to address the data inconsistency issues in the operational processing due to several major calibration changes since the launch of Suomi NPP satellite. This study investigates the feasibility of validating the reprocessed VIIRS imagery resolution bands (I-bands, 375 m) SDRs using time series analysis of cloud cover climatology over large metropolitan areas. An I-bands cloud mask algorithm was assessed for cloud detection over urban areas. Reprocessed I-bands SDRs over Beijing, China were generated using the same calibration parameters and VIIRS SDR science code to be used by the future NOAA reprocessing. The operational and reprocessed I-bands SDRs were compared and the impacts of reprocessing on the monthly percent cloud cover time series over Beijing were studied. Our results indicate that monthly percent cloud cover time series over metropolitan area are sensitive to major VIIRS radiometric calibration changes. Therefore, urban cloud climatology can be served as a testbed for the reprocessing of VIIRS I-bands SDRs.

This letter presents new models for estimating clear-sky instantaneous longwave radiation over land surfaces using the Geostationary Operational Environmental Satellites (GOES) Sounders and GOES-R Advanced Baseline Imager (ABI) thermal infrared top-of-atmosphere (TOA) radiances. The method used in this study shares the same hybrid method framework designed for Moderate Resolution Imaging Spectroradiometer. We propose separate surface downward longwave radiation (LWDN) and upwelling longwave radiation (LWUP) models because the two components are dominated by different surface/atmospheric properties. A nonlinear model was developed to estimate LWDN, and a linear model was developed to estimate LWUP. The GOES-12 Sounder-derived LWDN, LWUP, and surface net longwave radiation (LWNT = LWUP-LWDN) were evaluated using one full-year of ground data from the Surface Radiation Budget Network. The root-mean-squared errors (rmses) are less than 22.03 W/m2at all four sites. Our study indicates that the hybrid method can also be applied to estimate LWUP using the future GOES-R ABI TOA radiances. The lack of a channel beyond 13.3 m in the proposed ABI design may cause larger rmses when estimating LWDN.

Surface upwelling longwave radiation (LWUP) is an important component in the surface radiation budget. Existing satellite-derived LWUP data sets are too coarse to support high-resolution numerical models, and their accuracy needs to be improved. In this paper, we evaluate three methods for estimating clear-sky land LWUP from the Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1-km spatial resolution. The three methods are as follows: (1) the temperature-emissivity method; (2) the linear model method; and (3) the artificial neural network (ANN) model method. Methods 2 and 3 are new methods based on extensive radiative transfer simulations and statistical analysis. We explicitly considered surface emissivity effects by incorporating the University of California Santa Barbara emissivity library in the radiative transfer simulation. The three methods were evaluated using ground-measured LWUP from six SURFRAD sites. Although methods 2 and 3 were developed using MODIS Terra atmospheric profiles, they were applied to both Terra and Aqua data because the designs of the two sensors are similar. The root mean squared errors (rmses) of the ANN model method are smaller than that of the other two methods at all sites. The averaged rmses of the ANN model method are 15.89 W/m2(Terra) and 14.57 W/m>2(Aqua); the averaged biases are -8.67 W/m2(Terra) and -7.21 W/m2(Aqua). The biases and rmses for Aqua are ~1.3 W/m2smaller than that of Terra. The biases and rmses of the ANN model method are ~5 W/m2smaller than that of the temperature-emissivity method and ~2.5 W/m2smaller than that of the linear model method.