Visible Infrared Imaging Radiometer Suite Instrument Research Articles

Evaluation of VIIRS Thermal Emissive Bands Long-Term Calibration Stability and Inter-Sensor Consistency Using Radiative Transfer Modeling

This study investigates the long-term stability of the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) moderate-resolution Thermal Emissive Bands (M TEBs; M12–M16) covering a period from February 2012 to August 2020. It also assesses inter-sensor consistency of the VIIRS M TEBs among three satellites (S-NPP, NOAA-20, and NOAA-21) over eight months spanning from 18 March to 30 November 2023. The field of interest is limited to the ocean surface between 60°S and 60°N, specifically under clear-sky conditions. Taking radiative transfer modeling (RTM) as the transfer reference, we employed the Community Radiative Transfer Model (CRTM) to simulate VIIRS TEB brightness temperature (BTs), incorporating European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data as inputs. Our results reveal two key findings. Firstly, the reprocessed S-NPP VIIRS TEBs exhibit a robust long-term stability, as demonstrated through analyses of the observation minus background BT differences (O-B ∆BTs) between VIIRS measurements (O) and CRTM simulations (B). The drifts of the O-B BT differences are consistently less than 0.102 K/Decade across all S-NPP VIIRS M TEB bands. Notably, observations from VIIRS M14 and M16 stand out with drifts well within 0.04 K/Decade, reinforcing their exceptional reliability for climate change studies. Secondly, excellent inter-sensor consistency among these three VIIRS instruments is confirmed through the double-difference analysis method (O-O). This method relies on the O-B BT differences obtained from daily VIIRS operational data. The mean inter-VIIRS O-O BT differences remain within 0.08 K for all M TEBs, except for M13. Even in the case of M13, the O-O BT differences between NOAA-21 and NOAA-20/S-NPP have values of 0.312 K and 0.234 K, respectively, which are comparable to the 0.2 K difference observed in overlapping TEBs between VIIRS and MODIS. These disparities are primarily attributed to the significant differences in the Spectral Response Function (SRF) of NOAA-21 compared to NOAA-20 and S-NPP. It is also found that the remnant scene temperature dependence of NOAA-21 versus NOAA-20/S-NPP M13 O-O BT difference after accounting for SRF difference is ~0.0033 K/K, an order of magnitude smaller than the corresponding rates in the direct BT comparisons between NOAA-21 and NOAA-20/S-NPP. Our study confirms the versatility and effectiveness of the RTM-based TEB quality evaluation method in assessing long-term sensor stability and inter-sensor consistency. The double-difference approach effectively mitigates uncertainties and biases inherent to CRTM simulations, establishing a robust mechanism for assessing inter-sensor consistency. Moreover, for M12 operating as a shortwave infrared channel, it is found that the daytime O-B BT differences of S-NPP M12 exhibit greater seasonal variability compared to the nighttime data, which can be attributed to the idea that M12 radiance is affected by the reflected solar radiation during the daytime. Furthermore, in this study, we’ve also characterized the spatial distributions of inter-VIIRS BT differences, identifying variations among VIIRS M TEBs, as well as spatial discrepancies between the daytime and nighttime data.

Enhancement of Nighttime Fire Detection and Combustion Efficiency Characterization Using Suomi-NPP and NOAA-20 VIIRS Instruments

We present the second-generation Fire Light Detection Algorithm (FILDA-2), which includes advances in fire detection and retrievals of radiative power (FRP), fire visible energy fraction (VEF), and fire modified combustion efficiency (MCE) at nighttime from the holistic use of multiple-spectral radiances measured by the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi-NPP (VNP) and NOAA-20/JPSS-1 (VJ1) satellites. Key enhancements include: (1) a new fast algorithm that maps VIIRS Day/Night Band (DNB) radiances to the pixel footprints of VIIRS Moderate (M) and Imagery (I) bands; (2) identification of potential fire pixels through the use of the DNB anomalies and I-Band thermal anomalies; (3) dynamic thresholds for contextual testing of fire pixels; and (4) pixel-specific estimates of FRP, VEF, and MCE. The global benchmark test demonstrates that FILDA-2 can detect approximately 25-30% more smaller and cooler fires than the operational VIIRS Active Fire 375 m I-band algorithm with the added benefit of providing daily global pixel-level characterizations of MCE for nighttime surface fires. The MCE derived by FILDA-2 is in good agreement with limited ground-based observations near the fires. Additionally, FILDA-2 reduces angular dependence in FRP estimates and significantly reduces the ”bow-tie” (double-counting) effect in fire detection compared to the AF-I product. The cross-validation of FILDA-2 products from VNP and VJ1 retrievals confirms good consistency in FRP and MCE retrievals globally. FILDA-2 is being implemented by NASA to generate a new VIIRS data product for fire monitoring, chemical-speciated fire emission estimates, and fire line characterization.

Pre-Launch Polarization Assessment of JPSS-2 VIIRS VNIR Bands

The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments on-board the Suomi National Polar-orbiting Partnership (S-NPP), National Oceanic and Atmospheric Administration 20 (NOAA-20) and Joint Polar Satellite System (JPSS-2) spacecraft, with launch dates of October 2011, November 2017 and late 2022, respectively, have polarization sensitivity that affects the at-aperture radiometric Sensor Data Record (SDR) calibration in the Visible Near InfraRed (VNIR) spectral region. These SDRs are used as inputs into the VIIRS atmospheric, land, and water Environmental Data Records (EDRs) that are integral to climate and weather applications. Pre-launch characterization of the VIIRS polarization sensitivity was performed that provides an SDR radiance correction factor to enable high fidelity EDR products for the user community. The pre-launch polarization sensitivity used an external source that consisted of a 100 cm diameter Spherical Integrating Source (SIS) in combination with several sheet polarizers. These sheet polarizers were illuminated by the SIS and viewed by the VIIRS instrument. The sheet was then rotated to measure the variation in the VIIRS response relative to the at-aperture polarization orientation. There are sensor requirements that define the maximum allowed polarization amplitude to be below 2.5–3.0% depending on the band and have an uncertainty in both amplitude and phase of less than 0.5%. The pre-launch data analysis evaluated the VIIRS response through the rotating sheet polarizer to quantify each VNIR bands polarization amplitude, phase, and uncertainty. These parameters were compared with the sensor requirements and used to create on-orbit Look-Up Tables (LUTs) for EDR ground processing. The results of the analysis showed that all bands met the uncertainty requirement of 0.5%, but band M1 failed the 3% polarization amplitude requirement. A root-cause analysis identified the optical element responsible for the non-compliance and has been modified for JPSS-3 and -4 builds. The large polarization amplitudes observed in the NOAA-20 VIIRS build, for bands M1-M4, are greatly reduced for JPSS-2 VIIRS. This improved polarization performance was due to modifications to the band M1-M4 bandpass filters between these sensor builds.

Unscheduled Lunar Observations for Radiometric Characterization of VIIRS Reflective Solar Bands

Regularly scheduled lunar observations are a major component of the on-orbit calibration of the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) reflective solar bands (RSBs). With a few exceptions, these scheduled lunar observations have been performed with the same phase angles ranging from -51.5° to -50.5°. In addition to these observations that require a roll maneuver, the VIIRS instruments also view the Moon via its space-view (SV) port without a roll maneuver, covering a wide range of phase angles. In this article, we present techniques used to derive the radiometric gain for the VIIRS RSB using unscheduled lunar observations that are made over a range of phase angles. An empirical correction to account for residual phase angle dependencies is derived from on-orbit SNPP VIIRS unscheduled lunar events and is successfully applied to estimate the radiometric gain that shows good agreement with the gains derived from the scheduled lunar events and those derived from the solar diffuser (SD). In addition to the follow-on VIIRS instrument on the NOAA-20 satellite, three more VIIRS instruments are scheduled to be launched in the next decade. The methodologies developed in this work are expected to be applied to unscheduled lunar events from other VIIRS instruments to support their on-orbit RSB calibration.

On-Orbit Calibration and Performance of NOAA-20 VIIRS Reflective Solar Bands

The NOAA-20 (N20) satellite was launched on November 18, 2017 carrying the second Visible Infrared Imaging Radiometer Suite (VIIRS) instrument. Immediately following the launch, the VIIRS passed a series of intensive calibration and validation tests, after which regular calibration and operation activities have continued successfully for more than three years. The production of NASA Collection 2 Level 1B (C2 L1B) for N20 VIIRS began in summer 2019. In this article, we evaluate the early mission performance of the N20 VIIRS reflective solar bands (RSB) covering the first three full years of operation. The calibrated RSB gains are calculated primarily from the onboard solar diffuser (SD) and used in generating the C2 L1B reflectance and radiance products. We also show the on-orbit performance of the instrument noise, signal-to-noise ratio (SNR), and a reflectance uncertainty assessment. Comparisons are made to the first three years of operation of the first VIIRS instrument, aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. We evaluate the long-term stability of the calibrated N20 RSB reflectance product by looking at the long-term trends of lunar observations and data from the pseudo-invariant Libya 4 desert site. The N20 RSB have had excellent early mission performance, with changes in the gain of less than 0.5% in the first three years across all detectors, stable L1B reflectance, and very stable values of detector SNR and reflectance uncertainty.

NOAA-20 and S-NPP VIIRS Thermal Emissive Bands On-Orbit Calibration Algorithm Update and Long-Term Performance Inter-Comparison

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the National Oceanic and Atmospheric Administration-20 (NOAA-20) and the Suomi National Polar-orbiting Partnership Program (S-NPP) satellites were launched in late 2017 and 2011, respectively. This paper presents a recent update in the VIIRS thermal emissive bands (TEB) on-orbit calibration algorithm and inter-compares long-term instrument and TEB sensor data records (SDR) performances of the two VIIRS, to support user communities. The VIIRS TEB calibration algorithm was improved to mitigate calibration biases during the blackbody warm-up/cool-down (WUCD) events. Four WUCD bias correction methods were implemented in the NOAA operational processing in 2019: (1) the Nominal-F method, (2) the WUCD-C method, (3) the Ltrace method, and (4) the Ltrace-2 method. Our evaluation results indicate that the on-orbit performances of the two VIIRS instruments have been generally stable and comparable with each other, except that NOAA-20 VIIRS blackbody and instrument temperatures are lower than those of the S-NPP VIIRS. The degradations in the S-NPP TEB detector responsivities remain small after 9 years on-orbit. NOAA-20 detector responsivities have been generally stable after the longwave infrared degradation during its early mission was resolved by the mid-mission outgassing. NOAA-20 and S-NPP VIIRS TEB SDRs agree with co-located Cross-track Infrared Sounder observations, with daily averaged biases within 0.1 K at nadir. After the implementation of operational WUCD bias correction, residual TEB WUCD biases are similar for NOAA-20 and S-NPP, with daily averaged biases ~0.01 K in all bands.

Gas flaring activity and black carbon emissions in 2017 derived from the Sentinel-3A Sea and Land Surface Temperature Radiometer

Abstract. Gas flares are a regionally and globally significant source of atmospheric pollutants. They can be detected by satellite remote sensing. We calculate the global flared gas volume and black carbon emissions in 2017 by applying (1) a previously developed hot spot detection and characterisation algorithm to all observations of the Sea and Land Surface Temperature Radiometer (SLSTR) instrument on board the Copernicus satellite Sentinel-3A and (2) newly developed filters for identifying gas flares and corrections for calculating both flared gas volumes (billion cubic metres, BCM) and black carbon (BC) emissions (g). The filter to discriminate gas flares from other hot spots uses the observed hot spot characteristics in terms of temperature and persistence. A regression function is used to correct for the variability of detection opportunities. A total of 6232 flaring sites are identified worldwide. The best estimates of the annual flared gas volume and the BC emissions are 129 BCM with a confidence interval of [35, 419 BCM] and 73 Gg with a confidence interval of [20, 239 Gg], respectively. Comparison of our activity (i.e. BCM) results with those of the Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire data set and SWIR-based calculations show general agreement but distinct differences in several details. The calculation of black carbon emissions using our gas flaring data set with a newly developed dynamic assignment of emission factors lie in the range of recently published black carbon inventories, albeit towards the lower end. The data presented here can therefore be used e.g. in atmospheric dispersion simulations. The advantage of using our algorithm with Sentinel-3 data lies in the previously demonstrated ability to detect and quantify small flares, the long-term data availability from the Copernicus programme, and the increased detection opportunity of global gas flare monitoring when used in conjunction with the VIIRS instruments. The flaring activity and related black carbon emissions are available as “GFlaringS3” on the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) website (https://doi.org/10.25326/19, Caseiro and Kaiser, 2019).

Radiometric consistency between GOES-16 ABI and VIIRS on Suomi NPP and NOAA-20

NOAA has both geostationary (GEO) and polar orbiting (LEO) satellites that are procured through different vendors. For long-term environmental studies, it is essential to establish consistent radiometric calibration among satellite instruments irrespective of the satellite platforms. The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 satellites has been providing critical weather and climate-related data. With the launch of NOAA-20 in November 2017, the global coverage of VIIRS has doubled. With more than 7 years in space, S-NPP VIIRS has been rigorously calibrated and validated. We aim to quantify the radiometric consistency between the two VIIRS instruments through double differencing using GOES-16 Advanced Baseline Imager (ABI) as a reference instrument. We also provide insight into the temporal radiometric consistency between VIIRS and ABI. Since no direct simultaneous nadir overpasses (SNOs) exist between SNPP and NOAA-20 for intercomparison, GEO-LEO intercalibration is performed using SNOs between ABI and VIIRS instruments. We show that the NOAA-20 VIIRS measured top-of-atmosphere (TOA) reflectance is consistently lower than that of the S-NPP, mostly on the order of 2% to 3%, consistent with the past studies. GOES-16 ABI-observed reflectance is higher than both VIIRS instruments. SNOs over the all-sky tropical ocean are analyzed to quantify the bias for both NOAA-20 and S-NPP VIIRS relative to ABI. The impact on bias due to spectral differences is accounted for using spectral band adjustment factors estimated using hyperspectral measurements from SCIAMACHY. Uncertainties exist mainly due to calibration uncertainties in VIIRS and ABI, the time difference between the VIIRS and ABI observations, differences in cloud contamination, spectral response function differences, and lack of in-situ hyperspectral data to account for the spectral bias.

Intercomparison of the SNPP and NOAA-20 VIIRS DNB High-Gain Stage Using Observations of Bright Stars

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi-NPP (SNPP) and NOAA-20 (N20) spacecrafts is a multispectral Earth-observing instrument with bands covering wavelengths from visible to long-wave infrared. Among these bands is a panchromatic day/night band (DNB) with a broad spectral response ranging from 500 to 900 nm, and a high dynamic range spanning over seven orders of magnitude, allowing for observations to take place during both daytime and nighttime. The DNB operates at three gain levels, with low- and mid-gain stages and two high-gain stages (HGSs). The HGS is capable of detecting dim city lights during Earth-view observations at night as well as bright stars through the instrument space-view port. Since SNPP and N20 are at opposite points of the same orbit, each VIIRS instrument is able to observe the same stars with the DNB in successive orbits. This will allow us to make a direct comparison of the relative calibration of each instrument using stars over a range of spectral classes. In this article, we develop methodology for accurately identifying target stars in order to make proper comparisons between the DNB HGS of each instrument. We then take observations from multiple stars in order to compute the ratio in the measured irradiance for each instrument as a function of spectral class. For K-type stars, which have the least spectral change over the DNB wavelength range, we measure a calibration bias between the SNPP and N20 DNB HGS of approximately 4%, which is stable over the duration of the N20 mission.

Estimating Daily PM2.5 Concentrations in Beijing Using 750-M VIIRS IP AOD Retrievals and a Nested Spatiotemporal Statistical Model

Satellite-retrieved aerosol optical depth (AOD) data have been widely used to predict PM2.5 concentrations. Most of their spatial resolutions (~1 km or greater), however, are too coarse to support PM2.5-related studies at fine scales (e.g., urban-scale PM2.5 exposure assessments). Space-time regression models have been widely developed and applied to predict PM2.5 concentrations from satellite-retrieved AOD. Their accuracies, however, are not satisfactory particularly on days that lack a model dataset. The present study aimed to evaluate the effectiveness of recent high-resolution (i.e., ~750 m at nadir) AOD obtained from the Visible Infrared Imaging Radiometer Suite instrument (VIIRS) Intermediate Product (IP) in estimating PM2.5 concentrations with a newly developed nested spatiotemporal statistical model. The nested spatiotemporal statistical model consisted of two parts: a nested time fixed effects regression (TFER) model and a series of geographically weighted regression (GWR) models. The TFER model, containing daily, weekly, or monthly intercepts, used the VIIRS IP AOD as the main predictor alongside several auxiliary variables to predict daily PM2.5 concentrations. Meanwhile, the series of GWR models used the VIIRS IP AOD as the independent variable to correct residuals from the first-stage nested TFER model. The average spatiotemporal coverage of the VIIRS IP AOD was approximately 16.12%. The sample-based ten-fold cross validation goodness of fit (R2) for the first-stage TFER models with daily, weekly, and monthly intercepts were 0.81, 0.66, and 0.45, respectively. The second-stage GWR models further captured the spatial heterogeneities of the PM2.5-AOD relationships. The nested spatiotemporal statistical model produced more daily PM2.5 estimates and improved the accuracies of summer, autumn, and annual PM2.5 estimates. This study contributes to the knowledge of how well VIIRS IP AOD can predict PM2.5 concentrations at urban scales and offers strategies for improving the coverage and accuracy of daily PM2.5 estimates on days that lack a model dataset.

On-Orbit Line Spread Function Estimation of the SNPP VIIRS Imaging System From Lake Pontchartrain Causeway Bridge Images

The visible infrared imaging radiometer suite (VIIRS) instrument was launched on October 28, 2011 onboard the Suomi National Polar-Orbiting Partnership (SNPP) satellite. The VIIRS instrument is a whiskbroom system with 22 spectral and thermal bands split between 16 moderate resolution bands (M-bands), five imagery resolution bands (I-bands), and a day–night band. In this study, we estimate the along-scan line spread function (LSF) of the I-bands and M-bands based on measurements performed on images of the Lake Pontchartrain Causeway Bridge. In doing so, we develop a model for the LSF that closely matches the prelaunch laboratory measurements. We utilize VIIRS images co-geolocated with a Landsat TM image to precisely locate the bridge linear feature in the VIIRS images as a linear best fit to a straight line. We then utilize nonlinear optimization to compute the best fit equation of the VIIRS image measurements in the vicinity of the bridge to the developed model equation. From the found parameterization of the model equation, we derive the full-width at half-maximum as an approximation of the sensor field of view for all bands, and compare these on-orbit measured values with prelaunch laboratory results.

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Abstract. Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6; https://nsidc.org/data/modis/data_summaries) and VIIRS Collection 1 (C1; https://doi.org/10.5067/VIIRS/VNP10.001) represent the state-of-the-art global snow-cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow-cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map. The increased data content allows flexibility in using the datasets for specific regions and end-user applications. Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375 m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16+ year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms. These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Measurement of the Band-to-Band Registration of the SNPP VIIRS Imaging System from On-Orbit Data.

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched 28 October 2011 onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. The VIIRS instrument is a whiskbroom system with 22 spectral and thermal bands split between 16 moderate resolution bands (M-bands), five imagery resolution bands (I-bands) and a day-night band. In this study we measure the along-scan and along-track band-to-band registration between the I-bands and M-bands from on-orbit data. This measurement is performed by computing the Normalized Mutual Information (NMI) between shifted image band pairs and finding the amount of shift required (if any) to produce the peak in NMI value. Subpixel accuracy is obtained by utilizing bicubic interpolation. The product of the NMI peak slope and the NMI peak value is shown to be a better criterion for evaluating the quality of the NMI result than just the NMI peak value. Registration shifts are found to be similar to pre-launch measurements and stable (within measurement error) over the instrument's first four years in orbit.

Pre-Launch Radiometric Characterization of JPSS-1 VIIRS Thermal Emissive Bands

Pre-launch characterization and calibration of the thermal emissive spectral bands on the Joint Polar Satellite System (JPSS-1) Visible Infrared Imaging Radiometer Suite (VIIRS) is critical to ensure high quality data products for environmental and climate data records post-launch. A comprehensive test program was conducted at the Raytheon El Segundo facility in 2013–2014, including extensive environmental testing. This work is focused on the thermal band radiometric performance and stability, including evaluation of a number of sensor performance metrics and estimation of uncertainties. Analysis has shown that JPSS-1 VIIRS thermal bands perform very well in relation to their design specifications, and comparisons to the Suomi National Polar-orbiting Partnership (SNPP) VIIRS instrument have shown their performance to be comparable.

JPSS-1 VIIRS Radiometric Characterization and Calibration Based on Pre-Launch Testing

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the first Joint Polar Satellite System (JPSS) completed its sensor level testing on December 2014. The JPSS-1 (J1) mission is scheduled to launch in December 2016, and will be very similar to the Suomi-National Polar-orbiting Partnership (SNPP) mission. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 μm. It is a cross-track scanning radiometer capable of providing global measurements twice daily, through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging and moderate bands, respectively. This paper will briefly describe J1 VIIRS characterization and calibration performance and methodologies executed during the pre-launch testing phases by the government independent team to generate the at-launch baseline radiometric performance and the metrics needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). This paper will also provide an assessment of the sensor pre-launch radiometric performance, such as the sensor signal to noise ratios (SNRs), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response-vs-scan (RVS), and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the VIIRS sensor specification and the SNPP VIIRS pre-launch performance.

On-orbit characterization of the VIIRS solar diffuser and solar diffuser screen.

We analyze bidirectional reflectance factors (BRF) of the solar diffuser (SD) and vignetting function (VF) of the SD screen (SDS) for on-board calibration of the visible infrared imaging radiometer suite (VIIRS). Specific focus is placed on the products of the BRF and VF, which are the main inputs for calibration of the SD and its accompanying solar diffuser stability monitor (SDSM), which tracks SD degradation. A set of 14 spacecraft yaw maneuvers for the Suomi National Polar-Orbiting Partnership satellite, which houses the VIIRS instrument, was carefully planned and carried out over many orbits to provide the necessary information on the dependence of VIIRS instrument response on solar angles. Along with the prelaunch measurements for the SDS VF and SD BRF, the absolute form of the BRF-VF product is determined for each of the reflective solar bands (RSB) and the SDSM detectors. Consequently, the absolute form of the SDS VF also is obtained from the RSB and SDSM detectors using the yaw maneuver data. The results show that the BRF-VF product for an RSB is independent of the detector, gain status, and half-angle mirror side. The derived VFs from the RSB and the SDSM detectors also show reasonable agreement with each other, as well as with the prelaunch VF measurements, and further demonstrate only geometrical dependence, which, in this work, is characterized by solar angles. The derived calibration coefficients, called the F-factors, from the application of the derived functions in this study show a significantly improved pattern. A small band-dependent residual seasonal fluctuation on the level of ∼0.2%-0.4% remains in the F-factors for each RSB and is further improved by a corrective function with linear dependence on the solar azimuth angle in the nominal attitude instrument coordinate system to the VF. For satellite ocean color remote sensing, on-orbit instrument calibration and characterization are particularly important for producing accurate and consistent ocean color products. The result of this work has the most significant and direct impact on ocean color products.

Land and cryosphere products from Suomi NPP VIIRS: Overview and status.

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA’s Earth Observing System’s Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA’s focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team’s evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS.

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

Abstract The authors have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (IST) algorithm. Daily and monthly quality-controlled MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are presented at 6.25-km spatial resolution on a polar stereographic grid along with metadata to permit detailed accuracy assessment. The ultimate goal is to develop a climate data record (CDR) that starts in 1981 with the Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the Visible Infrared Imager Radiometer Suite (VIIRS) era (the first VIIRS instrument was launched in October 2011). Differences in the APP and MODIS cloud masks have thus far precluded merging the APP and MODIS IST records, though this will be revisited after the APP dataset has been reprocessed with an improved cloud mask. IST of Greenland may be used to study temperature and melt trends and may also be used in data assimilation modeling and to calculate ice sheet mass balance. The MODIS IST climate-quality dataset provides a highly consistent and well-characterized record suitable for merging with earlier and future IST data records for climate studies. The complete MODIS IST daily and monthly data record is available online.