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 Joint Polar Satellite System-2 (JPSS-2) was successfully launched on November 10, 2022 and renamed as NOAA-21 after it reached its final polar orbit. Twenty-five days after launch, on December 5, 2022, the NOAA-21 Visible Infrared Imaging Radiometer Suite (VIIRS) started collecting science data. After intensive analysis, calibration and validation of VIIRS science raw data record (RDR), telemetry RDR, and sensor data record (SDR) radiometric and geolocation data products, the NOAA-21 VIIRS SDRs reached Beta maturity on Feb. 23, 2023 and provisional maturity on March 30, 2023. This paper provides an update on the NOAA-21 VIIRS SDR availability, post-launch calibration and validation activities, and SDR quality assessments.

Passive microwave radiometer sounders are the backbones for numerical weather prediction under all sky conditions. Modern 5G technology represents a significant advancement in internet and communication technology, but may overlap with some of the passive microwave sounder channels, in particular the 5G’s 24 GHz channel may interfere with the 23.8 GHz total column water vapor channel measurements over land. This paper assesses the importance of the 23.8GHz channel for atmospheric sounding by analyzing the vertical weighting functions at different pressure levels to address the issue of sensitivity of this channel over land, and related issues such as land surface emissivity. Modeling experiments are also performed to assess the impacts of this channel on water vapor retrievals using the Microwave Integrated Retrieval System (MiRS). The role of this channel in detecting planetary boundary layer (PBL) water vapor is also discussed.

Due to the limited spatial or temporal resolution, current satellite-based products from VIIRS (Visible Infrared Imaging Radiometer Suite), MODIS (Moderate Resolution Imaging Spectroradiometer), and GOES ABI (Geostationary Operational Environmental Satellite Advanced Baseline Imager) are often inadequate for real-time applications such as wildfire edge detection and wildfire suppression. The overarching goal of this research is to employ deep learning to create high spatial and temporal resolution fire products needed by fire managers for real-time wildfire monitoring and perimeter mapping. To create a super-resolution GOES fire product, this paper will adapt an Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) to train the 2-km GOES ABI data (Channels 2, 7, 14, and 15 in particular). The concurrent overlapping higher spatial resolution VIIRS data (Channels I1-I5, 375 m resolution) from Suomi NPP, NOAA-20, and NOAA-21 (nominal temporal resolution is 12 h or less depending on the latitude) will be used as target labels in training the deep learning super-resolution model for downscaling GOES ABI data. The adapted ESRGAN model can then be applied to the real-time high temporal resolution GOES ABI data to produce high spatial resolution, i.e., 375-m, fire products.

Since early 2012, the cross-track infrared sounder (CrIS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has continually provided the hyperspectral infrared observations for profiling atmospheric temperature, moisture, and greenhouse gases. In this study, the CrIS sensor data record (SDR) data are improved for climate applications with its fine-tuning of calibration coefficients in an NOAA reprocessing project. A specific software system was developed to reprocess the CrIS SDR. This software system was updated with a new calibration algorithm, nonlinearity, and geolocation to improve the SDR data quality and long-term consistency. The calibration coefficients are refined with the latest updates, which were used to calibrate the latest operational SDR products and replace those in the engineering packet (EP) in the raw data record (RDR) data stream. The resampling wavelength was updated based on the metrology laser wavelength and resulted in zero sampling error in the spectral calibration. All the historical SDRs (from February 2012 to March 2017) were generated with the same calibration coefficients and same version of the processing software system, resulting in improved accuracy and stability in terms of spectral and radiometric calibration during the CrIS lifetime mission. The quality of the reprocessed CrIS SDR data at nominal spectral resolution (NSR) is assessed in terms of its radiometric and spectral calibration. Comparisons against the operational SDR data are carried out to demonstrate the improved long-term stability of the reprocessed CrIS SDR data. Overall radiometric biases are found to be small and highly stable over the instrument mission, the FOV-to-FOV differences are less than ~10 mK, and much better than that from the operational SDR data. It is shown that the CrIS metrology laser wavelength varies within 4 ppm as measured by the neon calibration system. The reprocessed SDR data have spectral errors less than 0.5 ppm, which is much better than the operational SDR data with about 4 ppm. This baseline version of the reprocessed SNPP CrIS SDR data is suitable for long-term climate monitoring and model assessments and can provide an infrared reference observation to assess other narrow- or broadband infrared instruments’ calibration accuracy.

The Visible Infrared Imaging Radiometer Suite (VIIRS) on the National Oceanic and Atmospheric Administration-20 (NOAA-20) satellite performs on-orbit radiometric calibration based on regular solar diffuser (SD) observations illuminated by the Sun at the termination point near the South Pole. Due to exposure to the ultraviolet portion of the solar irradiance spectrum, the SD bidirectional reflectance distribution function (BRDF) has been degrading over time. The SD degradation (called H-factor) was measured by the on-board calibrator called the SD stability monitor (SDSM). Nevertheless, over two years of operation, there have been systematic on-orbit calibration differences between the SD-based and independent moon-based calibration results. In this study, the NOAA VIIRS team used a surface roughness Rayleigh scattering (SRRS) model as a baseline SD degradation, simulated on-orbit center wavelength-based approach of SD degradation, and a new SDSM relative spectral response (RSR)-dependent SD degradation estimation method to evaluate the degradation. There were time-dependent growing differences between the SDSM RSR-applied H-factors and center wavelength interpolated H-factors especially in the short wavelength detectors (SDSM detector 1–4). The NOAA-20 SD-based calibration coefficients (SD F-factors) were reprocessed using the RSR-applied H-factors, and the new SD F-factors show similar long-term trends compared with the independent monthly lunar F-factors. The newly processed SD F-factor suggested that the NOAA-20 VIIRS detectors in the reflective solar bands (M1–M11 and I1–I3) showed very stable responses within 0.5% level over the two years of on-orbit operation.

The second Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the National Oceanic and Atmospheric Administration (NOAA) 20 satellite has been successfully operating since its launch on November 18, 2017. Since VIIRS does not include onboard calibrators to perform the on-orbit geometric data quality characterization for parameters such as the modulation transfer function (MTF) and band-to-band registration (BBR), the monthly scheduled lunar observations are used in this study. The radiometric property of the moon surface has demonstrated its long-term stability and it is also a suitable spatial target for the on-orbit calibration of remote sensing instruments. Using the commonly practiced methodologies, the VIIRS BBR results are derived in the scan and track directions. The initial trends show that the VIIRS BBR is very stable on-orbit within ±0.1 pixels in both scan and track directions meeting the highest requirements of within 0.2 pixels. Using the sharp edge of the moon, the scan-direction MTF at the Nyquist frequency was approximately 0.23. The MTF values are well above the specification of 0.3 in imaging (I)-bands and they are very stable over the study period, whereas the moderate-resolution (M)-bands results were slightly below the specification line as suggested by prelaunch test results. The scan-direction MTF estimations were consistently near 0.2 over four years of operations. Track-direction MTF values showed oscillations because of the annual cycle of lunar shadow angle and spatial features in the moon side. However, the track-direction MTF values met the specification with large margin.

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.

The Ozone Mapping and Profiler Suite (OMPS) Nadir Profilers (NPs) are advanced backscatter ultraviolet (BUV) hyperspectral instruments that measure ozone profiles in the Earth atmosphere. The first NP sensor onboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite began its science observations on January 26, 2012, after its aperture door opened. The second OMPS NP, flying on the NOAA-20 satellite, opened its aperture door on January 8, 2018, starting science its data collection. The two NP sensors acquire Earth spectral images along their satellite flight path with a 16.7° wide swath, enabling weekly coverage of vertical ozone distribution in the Earth atmosphere. A successful thorough sensor calibration enables the NP sensors’ data records (SDRs) to meet measurement accuracy requirements. The largest error term in the albedo calibration came from the spectral wavelength calibration. This article provides SDRs accuracy analysis for both NP sensors and discusses important aspects of the SDRs performance in relation to the sensors’ characterization and calibration.

As a panchromatic band, the Day-Night Band (DNB) on National Oceanic Atmospheric Administration (NOAA)-20 Visible Infrared Imaging Radiometer Suite (VIIRS) has a unique capability of observing very low radiances down to Nano-watt [cm-1sr-1] level, because of its three different focal planes with gain stages. The DNB radiometric calibration is based on the Solar Diffuser observations near the night to day time termination points. Besides the primary calibration source of SD, the moon provides alternative source of calibration with a specific lunar roll maneuvers. This study provides detailed methodology and results of lunar calibration for NOAA-20 VIIRS sensor and initial two year DNB radiometric calibration results from SD and scheduled lunar calibration. Over two years of NOAA-20 VIIRS operation, the Low Gain Stage (LGS) slope (inverse gain) trend showed a decreasing trend, whereas the calculated monthly lunar F-factor showed a stable response (inverse gain normalized to the lunar irradiance model) using a lunar irradiance model. These differences are monitored, compared, and applied for the best quality of NOAA-20 VIIRS DNB product.

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 National Oceanic and Atmospheric Administration (NOAA)-20 Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on November 18, 2017 and has been in operation for about one year. It has 14 Reflective Solar Bands (RSBs) covering a spectral range of 412nm to 2.25 um at two spatial resolutions at nadir 750m for Moderate resolution (M) bands and 350m for Imaging (I) bands. The spatial characterization of the VIIRS instrument was performed during the prelaunch calibration with parameters such as Band-to-Band Registration (BBR). Accurate estimation of BBR is a key spatial parameter when the inter-band calculation is required. Because there is no on-board spatial calibration source like Spectro Radiometric Calibration Assembly (SRCA) with Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), VIIRS instrument does not have on-board capability of measuring on-orbit BBR. As an alternative method, scheduled moon collections can be used to estimate on-orbit BBR characterization within the RSBs. In this paper, NOAA-20 VIIRS on-orbit BBR estimation methodology and initial results are presented.

In this work, the current performance of the calibrated Joint Polar Satellite System (JPSS) Cross-track Infrared Sensor (CrIS) observations is reported. The CrIS instrument is currently on-board the Suomi National Polar-orbiting Partnership (SNPP) and NOAA-20 spacecraft, and planned for the JPSS-2, -3 and -4 satellites. Presently, calibrated and validated CrIS observations, in the form of sensor data record (SDR) products, are being assimilated by operational NWP models and atmospheric retrieval systems. CrIS measurements from SNPP and NOAA-20 are expected to improve our understanding of the dynamics of the atmosphere due to the higher temporal and spatial coverage resulting from optimally blending the hyperspectral Earth observations. This work also reports recent improvements performed on the CrIS SDR products, including: 1) the implementation of the polarization correction, 2) the optimization of the spike detection and correction algorithm, and 3) the optimization of the lunar intrusion algorithm.

National Oceanic and Atmospheric Administration's (NOAA) Advanced Very High Resolution Radiometers (AVHRR) which has been flying on polar orbiting weather satellites since 1978 provide the longest global daily record of Earth observations. Data from AVHRRs have been vital for studying global change through their remote sensing observations of land, oceans, atmosphere and the cryosphere. MetOp-C satellites that was launched successful this year carries the last AVHRR. This paper reviews the glorious contributions of AVHRR during the past 40 years.

The NOAA-20 Ozone Mapping and Profiler Suite (OMPS) is one of the five instruments in the US Joint Polar Satellite System (JPSS) program. Like the first OMPS instrument [1],[2], the N20 OMPS contains two advanced nadir viewing hyper-spectral instruments, the Nadir Profiler and the Nadir Mapper, to track the health of the ozone layer via measurements the concentration of ozone in the Earth's atmosphere. This paper presents the NOAA-20 OMPS in-flight spectral calibration through solar observations and Earth views. Using a working solar diffuser and a reference solar diffuser, changes in the instruments' wavelength registration are determined through the OMPS solar calibrations. The observed sensor degradation at the shortest wavelengths is less than 0.5% for the sensor optics, but in excess of 1.0% for the OMPS working solar diffuser. The absolute irradiance calibration uncertainties meet system requirement of 7% for most of the channels. The in-flight sensor wavelength variation due to thermal-optical influence is less than 0.02 nm, which could cause about 1.6% error, not compliant with a 2% allocation, so a routine wavelength calibration will take place to accommodate the exceedance.

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.

On February 15 and 16, 2012, a series of yaw maneuvers was performed on the Suomi National Polar-Orbiting Partnership (S-NPP) spacecraft for Visible Infrared Imaging Radiometer Suite (VIIRS) to characterize screen transmission functions and Bidirectional Reflectance Distribution Functions (BRDFs). For accurate time-dependent calibration coefficient (or F-factor) calculation in the Reflective Solar Bands (RSBs), the Solar Diffuser (SD) and SD Stability Monitor (SDSM) screen transmission functions are measured using the on-orbit yaw maneuver data with three screen transmission functions. The SD screen transmittance function coupled with the SD BRDF (τSD BRDF) is updated and then the SDSM Sun and SDSM SD BRDF functions are updated. The SDSM solar and SD view functions are used in the SD degradation estimation, which affects the VIIRS view of the SD BRDF through the rotating telescope over time. The prelaunch measurements of these transmission or BRDF functions were too coarse to capture the small features of the transmission functions. There have been several efforts to derive better models but the annual oscillations in the F-factors remained to be a major issue. To mitigate these F-factor oscillations, the yaw maneuver data are reanalyzed to derive the transmittance and BRDF functions. This paper shows that the annual oscillations are caused by the imperfect SDSM Sun screen transmittance and SDSM SD BRDF functions. When the newly calculated SDSM SD BRDF and Sun transmittance lookup tables (LUTs) are applied, the annual oscillations in the H-and F-factors are significantly reduced, especially in the bands M1-M4.

The ozone mapping and profiler suite (OMPS) is carried onboard the Suomi National Polar-orbiting Partnership satellite that was launched on October 28, 2011. The OMPS mission objectives concern atmospheric ozone concentrations and their variations in the earth atmosphere. A successful thorough on-orbit sensor calibration enabled current validated operational sensor data record (SDR) stage, providing quality sensor data that meet the requirements and users' expectations. The calibration coefficients derived from this paper have been successfully used in a life-cycle SDR reprocessing to improve sensor data quality. In this paper, we present our qualitative analyses and the results of OMPS nadir mapper SDR on-orbit calibration, and address current SDR data quality in relation to instrument detector performance, stray light correction, and wavelength registration. Our OMPS SDR calibration experience sets a reference for the successor instruments for accurate long-term monitoring of ozone total column concentrations.

Solar diffusers (SDs) have often been used as the onboard calibrators for the radiometric calibration of reflective solar band imaging sensors. After being spaceborne, the reflectance of SDs is observed to degrade with spectral dependence due to exposure to solar UV and energetic particle radiation. Long-term spectral reflectance data of SDs onboard multiple LEO imaging sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) on SNPP, are analyzed. The reflectance of SDs on these three instruments degrades faster for the shorter wavelength (0.4-0.6 μm) bands than the longer wavelength bands. The Surface Roughness-induced Rayleigh Scattering (SRRS) model is applied to simulate the SD degradation on these instruments, and the growth of the surface roughness parameter of the SDs is derived. It is determined that the change of surface roughness scale length is ~tens of nanometers. To show the consistency of roughness growth rates among the SDs on Terra/Aqua MODIS and SNPP VIIRS instruments, the functional dependences of the growth rates are characterized according to the SD exposure time and the stage of surface roughness. It is also found that the flattening or reverse in the growth trend of the surface roughness for these three SDs occurred around the same interval between October 2013 and October 2015. The confirmation of the applicability of SRRS model with the long-term spectral reflectance data from three independent spaceborne SDs facilitates a better understanding of the origin and physical processes of the SD degradation.

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard Suomi-NPP is equipped with a Day/Night Band (DNB), a major advancement in nighttime imaging capability. DNB data quality has been largely improved through several calibration updates since early launch. The reprocessed VIIRS DNB sensor data record (SDR) data at the NOAA Center for Satellite Applications and Research (STAR) accommodate all updates, such as DNB modulated relative spectral responses (RSRs), monthly DNB offset and gain ratio, straylight correction, and geolocation terrain correction since launch. In addition, one of the major improvements is in the DNB offset computing using the pitch maneuver-based deep space view that is free of airglow. The reprocessed DNB data results in radiometrically consistent calibrated SDR that allows the user community to use high-quality DNB data in long-term applications. Until the end of 2016, DNB high gain stage (HGS) operational calibration involved estimation of dark offsets using the new moon-based nighttime measurements over the Pacific Ocean. However, the faint emission from airglow during the new moon nights led to an overestimation of the dark offset by an amount equivalent to that of the airglow. This directly impacts the calibrated data by underestimating the calibrated radiance values. The impact is prominent at low light radiance, which can also lead to negative radiances. This paper quantifies the reprocessing led improvements in the calibrated VIIRS DNB data, analyzes the impact of airglow on operational calibrated radiance product, and explains how the absolute accuracy for low light radiance has been largely improved for the entire reprocessed DNB archive.

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.

The NOAA-20 satellite was successfully launched on November 18,2017 into an afternoon orbit with local equator crossing time ~1: 30pm, in the same orbital plane as that of the Suomi National Polar-orbiting Partnership (NPP) but with a time separation of half an orbit or ~50 minutes. The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard NOAA-20 will become the primary operational imager succeeding the VIIRS onboard Suomi NPP which has been in-orbit for more than six years. Although the VIIRS onboard Suomi NPP and NOAA-20 have identical design, there are small differences in the relative spectral response (RSR) in most bands. Previous studies have shown that minor differences in RSR can lead to a number of effects at detector level, such as striping. This study investigates the VIIRS RSR differences between Suomi NPP and NOAA-20 for the Thermal Emissive Bands (TEB) including M12-M16. The Line-By-Line radiative transfer model (LBLRTM) is used at very high spectral resolution for convolving with the RSR of VIIRS on both satellites. The impact of RSR difference between Suomi NPP and NOAA-20 are evaluated for radiometric biases and potential striping in TEB. This study will contribute to the measurement consistency for the long term observations in the thermal infrared bands, and ensure the quality of the data produced by VIIRS, such as sea surface temperature (SST), fire and other retrievals.

The NOAA-20 Ozone Mapping Profiler Suite (OMPS) is the second Ultraviolet (UV) sensor suite in the US Joint Polar Satellite System (JPSS) program. The sensor suite was launched aboard the NOAA-20 spacecraft on Nov. 18, 2017. Like the first OMPS instrument which is flying on the Suomi National Polar-orbiting Partnership spacecraft (S-NPP), the NOAA-20 OMPS contains two advanced nadir viewing hyper-spectral instruments, the Nadir Profiler (NP) and the Nadir Mapper (NM), tracks the health of the ozone layer and measure the concentration of ozone in the Earth's atmosphere. A successful thorough early orbital calibration enabled the current provisional Sensor Data Records (SDRs) stage. We present our analyses and results of the NOAA-20 OMPS early-orbit SDR performance, demonstrate that the sensor smoothly transitioned from ground to orbit by meeting or exceeding sensor level requirements. Our results suggest that a routine calibration of dark current as well as wavelength shifts is critical in the SDR data processing.

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.

Emerging technologies such as IoT(Internet of Things) and UAS(Unmanned Aircraft Systems) enable new observing capabilities. In particular, infrared sensing of CO2and surface temperature with satellite infrared radiometers have been operationally used since the 1970s for atmospheric soundings, and sea/land surface temperatures, such as with NOAA's HIRS/AVHRR radiometers. Recent advances also allow the unprecedented CO2retrieval accuracy with the launch of OCO-2, GOSAT, IASI, CrIS, as well as ground measurements by the TCCON network. However, the retrievals from satellites have very coarse spatial resolution (a few kilometers) which limits their usefulness especially for urban areas, in addition to latency issues. This study explores the use of portable infrared sensors inter-connected through IOT as payloads on mobile platforms such as UAS, automobile, and on distributed networks to demonstrate in-situ dynamic measurements of CO2, as well as surface temperature over water and land. While the IoT enables realtime monitoring with high temporal resolution, the UAS allows high spatial resolution measurements in areas with greater CO2and surface temperature variability. The low system cost allows its potential proliferation towards a large distributed network with IOT. Such a system could fill in a gap in existing observation systems, and complement the ground based network for the monitoring and satellite validation of a large number of geophysical variables for environmental intelligence, which is a desired observation capability but currently limited to a number of sparsely distributed stations.

To ensure the post-launch performance of the National Oceanic and Atmospheric Administration's (NOAA) next generation geostationary optical Earth observing sensors a post-launch validation field campaign was developed. The GOES-R field campaign was focused to support post-launch validation of the Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM). This effort will discuss an overview of the GOES-R field campaign, field campaign reference measurements to validate ABI SI traceability and GLM flash detection efficiency, geophysical measurements for ABI product validation, as well as preliminary results. The GOES-R field campaign enabled the collection of reference data that provided advanced post-launch validation capabilities and fostered new perspectives in the post-launch validation and monitoring of NOAA's next generation of operational environmental satellites.

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard Suomi-NPP is equipped with a Day/Night Band (DNB), a major advancement in nighttime imaging capability as compared to the heritage Operational Linescan System (OLS) onboard Defense Meteorological Satellite Program (DMSP). DNB High Gain Stage (HGS) operational radiometric calibration involves estimation of dark offsets using the nighttime measurements over Pacific Ocean during new moon. However, the DNB detectors were found to be highly sensitive, enough to detect faint emission from airglow even during the moonless nights. Thus, the on orbit calculated dark offset is overestimated by an amount equivalent to that of airglow. This causes direct impact in calibrated data such that the radiance values are underestimated in the absolute scale. The impact is prominent at low light radiance. This study focuses on analyzing the airglow using DNB measurements. In addition, the impact on operational calibrated radiance product and how the absolute accuracy can be improved especially at low light radiance are also explored.

This study describes the improved calibration applied for VIIRS SDR reprocessing. At reflective solar bands (RSBs), the earth-view F-factor is adjusted with the lunar observations and changes about 2% in band M2-M4 in past five years. An empirical method is applied to remove the radiance spikes in VIIRS thermal emissive bands (TEBs) during the blackbody Warm-Up-Cool-Down (WUCD). VIIRS DNB calibration is improved by applying continuous spectral response changes, new bias tables, updated gain ratio tables, stray light tables, and terrain corrections.

The Advanced Baseline Imager (ABI) is the primary payload for NOAA's Geostationary Operational Environmental Satellite R-series (GOES-R). The first of this new generation GOES was launched on November 19, 2016, and named GOES-16 when it reached the orbit on November 29, 2016. ABI incorporated numerous advanced technologies to meet the ever-demanding users' requirements. There is great interest in the GOES-R Program, user community, and international partners whether ABI lives up to its expectations and how does it compare to Imager, the existing GOES imaging system. This paper will offer a preliminary glimpse of answers addressing those questions.

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument which is onboard the Suomi National Polar-orbiting Partnership (S-NPP)/Joint Polar Satellite System (JPSS) satellites has transitioned much of the capability of the experimental MODerate Resolution Imaging Spectroradiometer (MODIS) instruments into the operational domain. VIIRS provides a continuation of global environment monitoring for Land, Ocean, Cloud, and Atmosphere. The high quality observations and derived products generated from VIIRS have been used to improve operational environmental forecast skills and enhance our understanding of climate change processes. Since S-NPP successfully launched in October 2011, NOAA STAR science teams have been focused on maintaining, development, calibration/validation, and upgrade of the VIIRS algorithms. By far, most of the S-NPP VIIRS sensor and environmental data products have been fully validated and characterized through rigorous cal/val review process. The validated science algorithms are now used for reprocessing of the entire S-NPP mission lifetime of the VIIRS data product records. This paper presents an insight into these processes with examples of science data products operationally available from the S-NPP VIIRS Instrument. In addition, plans and preparations towards JPSS-1 launch and pre-operational evaluation JPSS-1 algorithms and product performance using proxy and Thermal Vacuum measurements are presented.

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.

Recently, the National Oceanic and Atmospheric Administration (NOAA) performed sea surface temperature (SST) reanalysis (RAN1) from seven AVHRR/3s onboard NOAA-15 to -19 and Metop-A and -B, from 2002-present using operational L1b input. The time series of clear-sky ocean brightness temperatures (BTs) and derived SSTs were found to be unstable. While the SSTs were empirically stabilized against in situ SSTs, the measured BTs were left intact. To better understand the AVHRR calibration and stabilize its BTs, the Sensor Stability for SST (3S) system was established at NOAA, which monitors orbital statistics of the sensor measured blackbody temperatures (BBTs), blackbody counts (BCs), and the space counts (SCs), along with the derived calibration gains and offsets. Other factors affecting the calibration are also monitored, including the Sun and Moon position relative to the sensor, local equator crossing time, and duration of the satellite night. All AVHRRs show long-term and band-specific smooth changes in the calibration gains and offsets, which are occasionally perturbed by spurious non-monotonic anomalies. We argue that the operational quality control (QC) and calibration procedures are suboptimal and should be improved. More stringent QC should be applied, and scan lines with bad calibration should be filled in by interpolation from the best parts of orbit or satellite lifetime. Work is underway to redesign the AVHRR QC and calibration algorithms, reprocess L1b, and use in the subsequent ACSPO SST RANs.

The Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard Suomi-NPP represents a major advance in night time imaging capabilities. During geomagnetic storms, auroras can be observed by the DNB on the night side over both hemispheres. The radiometrically calibrated DNB observations can enable quantitative analysis of the spatial distribution and temporal evolution of aurora during geomagnetic storms. Two coronal mass ejections (CME) occurred on June 19 and 21, 2015 and had made their way to Earth to cause a G4 (severe) geomagnetic storm on June 22 afternoon. This paper presents an analysis of the radiance data from DNB observations of the aurora during the geomagnetic storm on June 22, 2015. Regions of aurora during each orbital pass are identified and the evolution of aurora is characterized with time series of the auroral boundary, area and total light emission of the aurora region in the DNB observation. The good correlation of aurora activities with ground geomagnetic index during the geomagnetic storm suggests that DNB observations of aurora can provide new details of the magnetospheric and ionospheric responses during severe geomagnetic storms.

The mid-wavelength infrared (MWIR) imageries of Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) and HIMAWARI-8 Advanced Himawari Imager (AHI) enable monitoring temperature variation of heat sources such as hot spots and urban heat islands. The 3.75 um band of VIIRS provides imagery in high spatial resolution (~375 m) twice a day and can be used to monitor temperature variation of hot spots due to industrial activities. The 3.9 um channel of AHI imagery in 10-minute time resolution enables continuous monitoring of temporal variation of urban heat island temperature. This paper compared using imageries of VIIRS and AHI MWIR channel to monitor both spatial distribution and temporal (seasonal and diurnal) variation of hot spots and urban heat islands. It was shown that the MWIR imageries of VIIRS and AHI complement each other in understanding the spatial structure and temporal variation of social economic activities-related heat sources.

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.

The first VIIRS instrument has successfully operated for more than 4 years on-board the Suomi-National Polar-orbiting Partnership (S-NPP) spacecraft. The sensor data records (SDR) derived from VIIRS on-orbit observations have been used to produce many environment data records (EDR), enabling a wide range of applications by the users from operational and research community. This paper provides an overview of instrument operations and its calibration activities, and presents an update of its radiometric performance, in terms of on-orbit changes in sensor spectral band responses and noise characterization. It also describes the effort made to improve sensor calibration, and the strategies developed in support of producing consistent SDR and, consequently, the EDR with improved quality.

Water vapor observation at channels with central wavelength around 6.5 um is of great importance in weather forecasting and climate change detection, such as in MODIS, GOES, and GOES-R series of satellites. The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard Suomi NPP has 22 bands, however, does not have a water vapor sensing band, and the current VIIRS design cannot make space for additional band. Since the high resolution (375m) imagery band I03 and moderate resolution (750m) band M10, have very similar Spectral Response Functions centered at 1.61 um, it is possible to replace M10 observations with that from I03 to make space for a new water vapor band. However, the impact of removing M10 on different users should be assessed thoroughly. M10 and I03 are mainly used for obtaining surface reflectance at different resolution and for snow detection. M10 can also be used in cloud and aerosol detection, and in detecting night fire from gas flares and combustion sources. In this study, we examined the VIIRS Sensor Data Record (SDR) dataset and compared the radiance from M10 and aggregated I03 (to M10) with different earth observations. At day time, the M10 and I03 have very good agreement, but the radiance ratio between them is affected mainly by the uniformity of I03 pixels and different surface types. Over snow surface, the radiance scatterplot shows less scattered than that with no snow, indicating I03 has similar ability as M10 in snow detection. Limited night datasets indicate radiance of I03 and M10 are different, but I03 may also have superior ability in detecting night fire from gas flares and combustion sources. This study provides an early assessment of the feasibility of aggregating I03 to M10 in order to replace the M10 with a water vapor band.

The first Visible Infrared Imaging Radiometer Suite (VIIRS) is onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. As a primary sensor, it collects imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans in the spectral regions from visible (VIS) to long-wave infrared. NASA's National Polar-orbiting Partnership (NPP) VIIRS Characterization Support Team has been actively involved in the VIIRS radiometric and geometric calibration to support its Science Team Principal Investigators for their independent quality assessment of VIIRS Environmental Data Records. This paper presents the performance assessment of the radiometric calibration stability of the VIIRS VIS and NIR spectral bands using measurements from SNPP VIIRS and Aqua MODIS simultaneous nadir overpasses and over the invariant surface targets at the Libya-4 desert and Antarctic Dome Concordia snow sites. The VIIRS sensor data records (SDRs) used in this paper are reprocessed by the NASA SNPP Land Product Evaluation and Analysis Tool Element. This paper shows that the reprocessed VIIRS SDRs have been consistently calibrated from the beginning of the mission, and the calibration stability is similar to or better than MODIS. Results from different approaches indicate that the calibrations of the VIIRS VIS and NIR spectral bands are maintained to be stable to within 1% over the first three-year mission. The absolute calibration differences between VIIRS and MODIS are within 2%, with an exception for the 0.865- μm band, after correction of their spectral response differences.

Radiometric calibration coefficients for the VIIRS reflective solar bands have been reprocessed from the beginning of the Suomi NPP mission until present. An automated calibration procedure, implemented in the JPSS operational data production system, was applied to reprocess onboard solar calibration data and solar diffuser degradation measurements. The latest processing parameters from the operational system were used to include corrected solar vectors, optimized directional dependence of attenuation screens transmittance and solar diffuser reflectance, updated pre-launch calibration coefficients without an offset term, and optimized Robust Holt-Winters filter parameters. The parameters were consistently used to generate a complete set of the radiometric calibration coefficients for the entire duration of the Suomi NPP mission. The reprocessing has also demonstrated that the automated calibration procedure can be successfully applied to all solar measurements acquired from the beginning of the mission until the full deployment of the automated procedure in the operational processing system.

Radiometric sensor calibration is critical for quantitative use of the data obtained from the FeungYun-3A MEdium-Resolution Spectral Imager (MERSI) sensor. To meet the required calibration criteria, several vicarious calibration (VC) techniques are being employed in the current operational calibration of MERSI. This letter presents the independent results of sensor degradation assessment which were obtained directly from sequences of top-of-atmosphere (TOA) reflectance from calibration sites. The absolute calibration approaches and the desert tracking approach used in the current operational process involve a radiative transfer model (RTM) when simulating the reference TOA reflectance. However, collecting synchronous in situ measurements for an RTM is usually expensive and time consuming, thus greatly limiting the frequency of such calibration processes. The direct approach developed in this study is an efficient and complementary VC technique that can increase the reliability of VC results in concert with other techniques. TOA reflectance measurements from three pseudoinvariant calibration sites are used to estimate sensor degradation rates. The results are compared with those obtained by other operational methods such as the multisite and the deep convective cloud tracking methods. The direct approach is consistent across the three calibration sites, producing degradation estimates comparable to those of the two other operational methods, suggesting the effectiveness of the direct approach for the MERSI radiometric sensor calibration.

The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key environmental remote-sensing instruments onboard the Suomi National Polar-Orbiting Partnership spacecraft, which was successfully launched on October 28, 2011 from the Vandenberg Air Force Base, California. Following a series of spacecraft and sensor activation operations, the VIIRS nadir door was opened on November 21, 2011. The first VIIRS image acquired signifies a new generation of operational moderate resolution-imaging capabilities following the legacy of the advanced very high-resolution radiometer series on NOAA satellites and Terra and Aqua Moderate-Resolution Imaging Spectroradiometer for NASA's Earth Observing system. VIIRS provides significant enhancements to the operational environmental monitoring and numerical weather forecasting, with 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns, providing the sensor data records for 23 environmental data records including aerosol, cloud properties, fire, albedo, snow and ice, vegetation, sea surface temperature, ocean color, and nigh-time visible-light-related applications. Preliminary results from the on-orbit verification in the postlaunch check-out and intensive calibration and validation have shown that VIIRS is performing well and producing high-quality images. This paper provides an overview of the on-orbit performance of VIIRS, the calibration/validation (cal/val) activities and methodologies used. It presents an assessment of the sensor initial on-orbit calibration and performance based on the efforts from the VIIRS-SDR team. Known anomalies, issues, and future calibration efforts, including the long-term monitoring, and intercalibration are also discussed.

This paper presents a generic self-emission model for infrared (IR) radiometers where the relationship between the instrument self-emission and calibration intercept is analyzed. This model is applied to both the prelaunch and on-orbit MetOp/High-Resolution IR Radiation Sounder (HIRS) calibration data. For MetOp/HIRS, the changes in intercept due to self-emission variations between calibration events are up to 1% of the onboard blackbody calibration radiance. The impact is dependent on Earth scene brightness temperature and channel wavelength. The investigation shows that the intercept variation due to self-emission is significant and, if not corrected, can induce errors of up to 1 K for Earth scenes with 285 K brightness temperature and higher for Earth scenes with lower brightness temperatures. Based on this self-emission model, an improved in-flight calibration algorithm is proposed to reduce systematic calibration errors. We believe that this model can improve accuracy and consistency of level 1b radiance for climate studies and can be applied to other IR radiometers.

The monitoring of top-of-atmosphere (TOA) reflectance time series provides useful information regarding the long-term degradation of satellite sensors. For a precise assessment of sensor degradation, the TOA reflectance time series is usually corrected for surface and atmospheric anisotropy by using bidirectional reflectance models so that the angular effects do not compromise the trend estimates. However, the models sometimes fail to correct the angular effects, particularly for spectral bands that exhibit a large seasonal oscillation due to atmospheric variability. This paper investigates the use of time series algorithms to identify both the angular effects and the atmospheric variability simultaneously in the time domain using their periodical patterns within the time series. Two nonstationary time series algorithms were tested with the Landsat 5 Thematic Mapper time series data acquired over two pseudoinvariant desert sites, the Sonoran and Libyan Deserts, to compute a precise long-term trend of the time series by removing the seasonal variability. The trending results of the time series algorithms were compared to those of the original TOA reflectance time series and those normalized by a widely used bidirectional-reflectance-distribution-function model. The time series results showed an effective removal of seasonal oscillation, caused by angular and atmospheric effects, producing trending results that have a higher statistical significance than other approaches.

Power outages after a major storm affect the lives of millions of people and cause massive light outages. The launch of the Suomi National Polar-orbiting Partnership satellite with the Visible Infrared Imaging Radiometer Suite (VIIRS) significantly enhances our capability to monitor and detect light outages with the well-calibrated day/night band (DNB) and to use light loss signatures as indication of regional power outages. This study explores the use of the DNB in quantifying light outages due to the derecho storm in the Washington DC metropolitan area in June 2012 and Hurricane Sandy at the end of October 2012 on the East Coast of U.S. The results show that the DNB data are very useful in detecting power outages by quantifying light loss, but it also has some challenges due to clouds, lunar illumination, and straylight effect. Comparison of light outage and recovery trend determined from DNB data with power company survey shows reasonable agreement, demonstrating the usefulness of DNB in independently verifying and complementing the statistics from power companies.

In this study, two methods were used to evaluate radiometric calibration of the VIIRS sensor data records: (1) imaging of radiometrically stable Earth's surfaces and (2) SNO (Simultaneous Nadir Overpass) observations by VIIRS and other satellite instruments. Measurements acquired by VIIRS at the stable Dome C calibration site in Antarctica confirm that a faster-than-expected degradation of the radiometric response occurs for selected spectral bands in the visible and near-infrared region, with other bands remaining stable. SNO comparisons with MODIS show that the implemented regular updates of the radiometric calibration coefficients have stabilized the calibration and that the VIIRS and MODIS measurements are in agreement.

The launch of the SNPP with VIIRS signifies a new era of continued operational global earth observations with moderate resolutions. In the calibration/validation of VIIRS, it is essential to ensure that its measurements are consistent with those from previous instruments such as MODIS and AVHRR because longterm study of the earth relies on consistent satellite measurements with decadal data sets. This study focuses on the use of an extension of the traditional simultaneous nadir overpass (SNO) approach for performance evaluation and intercomparison of the VIIRS instrument with MODIS and AVHRR. Unlike SNO approach which is limited to polar regions only, the extended SNO (SNOx) provides an opportunity to compare satellite instruments at low latitudes over wide dynamic ranges. In addition, a new Geolocation Matching Method (GSM) method is developed to match a full VIIRS scene to MODIS. This tool uses an optimized algorithm with reduced run time and has been primarily used to analyze the intersatellite radiometric consistency and geolocation accuracy.

Sonoran Desert is a potential pseudo-invariant site that can be used for vicarious calibration of satellite sensors. However, the surface and atmospheric anisotropy of the site first needs to be characterized for the precise evaluation of the long-term stability of the sensors. In this study, the anisotropy of the desert site is investigated by applying widely used bidirectional reflectance distribution function (BRDF) models to the top-of-atmosphere (TOA) reflectance of Landsat 5 TM data. Time series of the original and BRDF-normalized TOA reflectance are first presented, and the radiometric stability of the time series is computed by using the BRDF-normalized TOA reflectance of the Landsat data.

VIIRS thermal emissive bands (TEB) have been analyzed. The analysis results indicate the VIIRS TEB is stable and exceeds the specification. Comparisons between the VIIRS and other sensors such as AVHRR, MODIS and CrIS demonstrated that VIIRS TEB agrees well with those sensors. Using Community Radiative Transfer Model (CRTM), developed at U.S. Joint Center for Satellite Data Assimilation (JCSDA), we found that M12 band image striping at day time over a uniform ocean was caused by the difference of sensor azimuthal angles among detectors.

A significant challenge for the Global Earth Observation System of Systems (GEOSS) interoperability is the lack of consistency in the Earth observations from satellites developed, calibrated, and operated by different space agencies worldwide, and the potential for significant discrepancies among products exists. The Committee on Earth Observation Satellites (CEOS) and its Working Group on Calibration and Validation (WGCV) are taking specific steps to facilitate interoperability by developing data quality assurance strategies and conducting joint cross-calibration studies. In this study, the Antarctic Plateau Dome C site is used for cross-comparison of visible/near infrared, and microwave instruments. Observations from AVHRR, MODIS, Hyperion, AMSR-E, and other instruments were intercompared. The findings suggest that the site is stable with relatively low radiometric uncertainties, and is a good candidate for CEOS endorsed cal/val site for satellite cross-comparison to facilitate GEOSS interoperability.

Accurate and precise satellite radiance measurements are important for data assimilations in numerical weather prediction models and for climate-change detection. After the successful launch of the infrared atmospheric sounding interferometer (IASI), several studies have indicated that the IASI radiance measurements are well calibrated and maintain superb spectral and radiometric calibration accuracy. Owing to its hyperspectral nature and high-quality measurements, the IASI radiance can serve as a relative reference to independently assess the radiance measurements of broad- or narrow-band instruments that share the same spectral region. In this paper, we demonstrate the utility of the IASI radiances to evaluate the Advanced Very High Resolution Radiometer (AVHRR) infrared (IR) channel measurements. The coregistered AVHRR pixels inside each IASI pixel are averaged spatially. We then compared the spatially averaged radiance from AVHRR IR channels with IASI by convolving the IASI-measured spectra with the AVHRR spectral response functions. It was found that, statistically, the temperature observed from AVHRR channels 4 and 5 is slightly warmer than that in IASI for the brightness temperature (BT) range of 200 K-300 K. The mean BT difference (IASI minus AVHRR) is less than 0.4 K with a standard deviation of ~0.3 K for AVHRR channels 4 and 5. The BT difference between IASI and AVHRR IR channels is scene-temperature dependent for both channels 4 and 5, which is probably caused by the nonlinearity of the AVHRR detectors. Both AVHRR channels 4 and 5 show slight scan-dependent bias with maximum differences of approximately ~0.2 K (with AVHRR being warmer than IASI) at both ends of the scan.

Although the Simultaneous Nadir Overpass (SNO) method has been used in several previous studies, the uncertainty of this method has not been well quantified for the solar reflective bands. In this study, the accuracy of the SNO method is evaluated first based on a four year time series of SNO data between AVHRR/NOAA16 and MODIS/AQUA. It was found that the nominal accuracy for the 0.63 mum band is better than 0.9%, which can unambiguously identify the large offset (~9%) between AVHRR/NOAA16 and MODIS/AQUA. This discrepancy is thought to be caused by the calibration traceability and standard used for AVHRR. For the 0.84 mum band, the uncertainty varies with a variety of factors, including atmosphere, water vapor, and landcover types. Therefore, although a 10-20% difference is found between AVHRR/NOAA16 and MODIS/AQUA, the uncertainty in this analysis is estimated to be greater than +1-5%. Based on these baseline uncertainty assessments, a preliminary analysis of the calibration differences between AVHRR/MetOP and MODIS/AQUA is also performed, and small biases are found when the AVHRR prelaunch calibration coefficients are used. The use of global full resolution area coverage (FRAC) AVHRR data reduced the uncertainty in the analysis but a longer time series is needed in order to evaluate the ability of the SNO method for quantifying the relative degradation rate, since this rate appears to be relatively small for the 0.63 mum channel for newer instruments than that the previous AVHRR series. It is expected that the accuracy of the SNO method can be further improved with the FRAC data which can contribute to the generation of fundamental climate data records.

The harmonization of operational data products and the creation of higher level information products such as global maps and time series (from different sensor sources) are required to satisfy the operational service requirements of the societal benefit areas as outlined in the GEOSS implementation plan. The CEOS Worldng Group on Calibration and Validation (WGCV) concentrates on defining standards and procedures aimed at allowing for the inter-comparison and ultimate utilization of data from all Earth observing platforms, both current and future. WGCV strives to establish common approaches to validation, calibration and data exchange formats to ensure effective cooperative use of all CEOS member space assets in addressing important global scale problems. This paper reviews the WGCV data assurance strategy, detailed system element requirements to guarantee data quality, and current WGCV activities for the generation and validation of products..

The long-term trend of aerosol optical thickness (AOT) over the global oceans has been studied by using a nearly 25-year aerosol record from the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmosphere (PATMOS) climate data. Both global and regional analyses have been performed to derive the AOT tendencies for monthly, seasonal, and annual mean AOT values at AVHRR 0.63μm channel (or Channel-1). A linear decadal change of ‒0.01 is obtained for globally and monthly averaged aerosol optical thicknesses of AVHRR Channel-1. Sensitivity analyses have also been performed to study the effects of radiance calibration and aerosol retrieval algorithm on the global aerosol long-term tendencies.

There is an increasing demand for intercalibrating the polar-orbiting radiometers on different satellites to achieve the consistency and traceability required for long-term climate studies with the 25+ years of NOAA satellite data. Also, the calibration of current operational radiometers needs to be linked to those of the next generation NPOESS (National Polar-orbiting Operational Environmental Satellite System) satellites. The simultaneous nadir overpasses (SNOs)/simultaneous conical overpass (SCO) method developed at NOAA/NESDIS has been applied to the intersatellite calibration of radiometers in the infrared, visible/near-infrared, and microwave with excellent results. In this paper, the SNO/SCO methodology is introduced. Preliminary intersatellite calibration results for AVHRR, MODIS, SSM/I, AIRS, HIRS, and AMSU on operational and historical satellites are presented. The plans for establishing the calibration links between POES (Polar Operational Environmental Satellites) and NPOESS radiometers using the SNO/SCO method are discussed.