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NOAA-20 Visible Infrared Imaging Radiometer Suite day–night band on-orbit calibration and performance

The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) instrument has been successfully operating on orbit since November 28, 2017. The day–night band (DNB) onboard NOAA-20 VIIRS is a panchromatic channel covering wavelengths from 0.5 to 0.9 μm, capable of observing the Earth scene in visible/near-infrared spectral range at a spatial resolution of 750 m. The DNB operates at low-, mid-, or high-radiometric gain stages, and it uses an onboard solar diffuser (SD) panel for low-gain stage calibration. The SD observations also provide a means to compute gain ratios between low-to-mid and mid-to-high-gain stages. With their large dynamic range and high sensitivity, the DNB detectors can make observations during both daytime and nighttime. We provide an assessment of the DNB on-orbit performance and behavior in the first two-year mission period and beyond. The calibration methodology used by the VIIRS Characterization Support Team in support of the NASA Earth science community has been described. The trending of on-board calibrators dark-offsets, SD gains, and gain ratios, and signal-to-noise ratio at minimum radiance have been analyzed, especially during key events such as the nadir and cryocooler doors opening. Furthermore, we performed intercomparison studies between Suomi National Polar-orbiting Partnership and NOAA-20 instruments and evaluated DNB radiometric calibration and characterization, including the SD degradation, detector gains, gain ratios, and straylight correction, as well as the calibration comparison between the NOAA Interface Data Processing Segment look-up-tables and our delivery results.

VIIRS↗

JPSS-2 VIIRS Day-Night Band Pre-launch Radiometric Calibration and Performance

The first two flight models of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument continue to operate onboard the Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 spacecrafts. The third flight model is set to be launched as one of a complement of instruments onboard the Joint Polar–orbiting Satellite System-2 (JPSS-2) satellite. In addition to its 14 reflective solar bands and 7 thermal emissive bands, VIIRS has a unique Day-Night Band (DNB). The DNB is a panchromatic imager based on CCD detectors, covering a spectral range of about 500 – 900 nm. The DNB is made up of three gain stages, allowing the sensor to operate over a large dynamic range (3×10(−9) - 0.02 W⁄cm(2)/sr). As part of VIIRS pre-launch ground testing, the DNB has been characterized to determine its functionality and performance under a space-like environment. The results are compared against the design specification and to previous VIIRS flight models when applicable. This paper presents a comprehensive summary of the VIIRS DNB prelaunch testing and the results of radiometric and spectral assessments. The expected impact to on-orbit operations and calibrated data products are also discussed.

Infrared Imaging Radiometer Suite (VIIRS)↗

Improvements in the Calibration of the NOAA-20 VIIRS Day-Night Band Low Gain Stage Using a Solar Diffuser

We aim to introduce and demonstrate several improvements that are applied to the on-orbit solar diffuser (SD) calibration of the day-night band (DNB) low gain stage (LGS) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the NOAA-20 satellite. The most important improvement is the expansion of the angular range, referred to “sweet spot”, from 4° to 7.8° in order to increase the number of fully-illuminated scans considered for the SD calculation. The increase in scan number enables the completion of on-orbit calibration using the SD within one orbit, compared with the multiple orbits approach, which is required in the current standard approach applied in operational DNB LGS calibration coefficients look-up tables (LUTs) updates. The NOAA-20 DNB LGS calibration coefficients have been derived with the new methodology and the results show a more stable, smoother, and less noisy trend when compared with the current standard approach. The results also demonstrate that the NOAA-20 VIIRS DNB overall on-orbit performance has been very stable.

NOAA-20↗

Improving Nocturnal Fire Detection with the VIIRS Day-Night Band

Building on existing techniques for satellite remote sensing of fires, this paper takes advantage of the day-night band (DNB) aboard the Visible Infrared Imaging Radiometer Suite (VIIRS) to develop the Firelight Detection Algorithm (FILDA), which characterizes fire pixels based on both visible-light and infrared (IR) signatures at night. By adjusting fire pixel selection criteria to include visible-light signatures, FILDA allows for significantly improved detection of pixels with smaller and/or cooler subpixel hotspots than the operational Interface Data Processing System (IDPS) algorithm. VIIRS scenes with near-coincident Advanced Spaceborne Thermal Emission and Reflection (ASTER) overpasses are examined after applying the operational VIIRS fire product algorithm and including a modified "candidate fire pixel selection" approach from FILDA that lowers the 4-μm brightness temperature (BT) threshold but includes a minimum DNB radiance. FILDA is shown to be effective in detecting gas flares and characterizing fire lines during large forest fires (such as the Rim Fire in California and High Park fire in Colorado). Compared with the operational VIIRS fire algorithm for the study period, FILDA shows a large increase (up to 90%) in the number of detected fire pixels that can be verified with the finer resolution ASTER data (90 m). Part (30%) of this increase is likely due to a combined use of DNB and lower 4-μm BT thresholds for fire detection in FILDA. Although further studies are needed, quantitative use of the DNB to improve fire detection could lead to reduced response times to wildfires and better estimate of fire characteristics (smoldering and flaming) at night.

Day-night band↗

Aurora Detection From Nighttime Lights for Earth and Space Science Applications

This research leverages data from the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer (VIIRS) instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. We demonstrate the value of mining the VIIRS DNB for aurora and describe our use of unsupervised machine learning to create a binary mask for aurora occurrence. This mask can be used to flag aurora-contaminated observations for NASA's nighttime lights products for Earth science applications. The identification of auroral regions can also be used for Space Weather applications, for example, for comparison with aurora forecast model and with other satellite- or ground-based aurora observations. The DNB is a broadband channel that is sensitive to wavelengths from 500 to 900 nm, which covers most of the visible light spectrum, and as the name implies, captures light even at night with a sensitivity at the nanowatt level. This band is suitable for aurora observations since the light emitted by the aurora tends to be dominated by emissions from atomic oxygen, resulting in a greenish glow at a wavelength of 557.7 nm, especially at an altitude of 110 km. This study compares the global nighttime derived aurora regions for 17 and 18 March with the NOAA Space Weather Prediction Center's (SWPC) probability product for the St. Patrick's Day geomagnetic storm in 2015. VIIRS sensors are slated to be added to the next generation of polar-orbiting operational satellites. Our novel automated approach to aurora identification opens up an efficient way to leverage this unique data source.

Aurora↗

SNPP VIIRS Spectral Bands Co-Registration and Spatial Response Characterization

The Visible Infrared Imager Radiometer Suite (VIIRS) instrument onboard the Suomi National Polar‐orbiting Partnership (SNPP) satellite was launched on 28 October 2011. The VIIRS has 5 imagery spectral bands (I-bands), 16 moderate resolution spectral bands (M-bands) and a panchromatic day/night band (DNB). Performance of the VIIRS spatial response and band-to-band co-registration (BBR) was measured through intensive pre-launch tests. These measurements were made in the non-aggregated zones near the start (or end) of scan for the I-bands and M-bands and for a limited number of aggregation modes for the DNB in order to test requirement compliance. This paper presents results based on a recently re-processed pre-launch test data. Sensor (detector) spatial impulse responses in the scan direction are parameterized in terms of ground dynamic field of view (GDFOV), horizontal spatial resolution (HSR), modulation transfer function (MTF), ensquared energy (EE) and integrated out-of-pixel (IOOP) spatial response. Results are presented for the non-aggregation, 2-sample and 3-sample aggregation zones for the I-bands and M-bands, and for a limited number of aggregation modes for the DNB. On-orbit GDFOVs measured for the 5 I-bands in the scan direction using a straight bridge are also presented. Band-to-band co-registration (BBR) is quantified using the prelaunch measured band-to-band offsets. These offsets may be expressed as fractions of horizontal sampling intervals (HSIs), detector spatial response parameters GDFOV or HSR. BBR bases on HSIs in the non-aggregation, 2-sample and 3-sample aggregation zones are presented. BBR matrices based on scan direction GDFOV and HSR are compared to the BBR matrix based on HSI in the non-aggregation zone. We demonstrate that BBR based on GDFOV is a better representation of footprint overlap and so this definition should be used in BBR requirement specifications. We propose that HSR not be used as the primary image quality indicator, since we show that it is neither an adequate representation of the size of sensor spatial response nor an adequate measure of imaging quality.

Suomi NPP VIIRS↗

Supporting Disaster Assessment and Response with the VIIRS Day-Night Band

When meteorological or man‐made disasters occur, first responders often focus on impacts to the affected population and other human activities. Often, these disasters result in significant impacts to local infrastructure and power, resulting in widespread power outages. For minor events, these power outages are often short-lived, but major disasters often include long‐term outages that have a significant impact on wellness, safety, and recovery efforts within the affected areas. Staff at NASA's Short‐term Prediction Research and Transition (SPoRT) Center have been investigating the use of the VIIRS day‐night band for monitoring power outages that result from significant disasters, and developing techniques to identify damaged areas in near real‐time following events. In addition to immediate assessment, the VIIRS DNB can be used to monitor and assess ongoing recovery efforts. In this presentation, we will highlight previous applications of the VIIRS DNB following Superstorm Sandy in 2012, and other applications of the VIIRS DNB to more recent disaster events, including detection of outages following the Moore, Oklahoma tornado of May 2013 and the Chilean earthquake of April 2014. Examples of current products will be shown, along with future work and other goals for supporting disaster assessment and response with VIIRS capabilities.

Schultz, Lori A.↗

Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas

Natural and anthropogenic hazards are frequently responsible for disaster events, leading to damaged physical infrastructure, which can result in loss of electrical power for affected locations. Remotely-sensed, nighttime satellite imagery from the Suomi National Polar-orbiting Partnership (Suomi-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) can monitor power outages in disaster-affected areas through the identification of missing city lights. When combined with locally-relevant geospatial information, these observations can be used to estimate power outages, defined as geographic locations requiring manual intervention to restore power. In this study, we produced a power outage product based on Suomi-NPP VIIRS DNB observations to estimate power outages following Hurricane Sandy in 2012. This product, combined with known power outage data and ambient population estimates, was then used to predict power outages in a layered, feedforward neural network model. We believe this is the first attempt to synergistically combine such data sources to quantitatively estimate power outages. The VIIRS DNB power outage product was able to identify initial loss of light following Hurricane Sandy, as well as the gradual restoration of electrical power. The neural network model predicted power outages with reasonable spatial accuracy, achieving Pearson coefficients (r) between 0.48 and 0.58 across all folds. Our results show promise for producing a continental United States (CONUS)- or global-scale power outage monitoring network using satellite imagery and locally-relevant geospatial data.

da/night band↗

Detecting Nighttime Fire Combustion Phase by Hybrid Application of Visible and Infrared Radiation from Suomi NPP VIIRS

An accurate estimation of biomass burning emissions is 1 partially limited by the lack of knowledge of fire burning phase (smoldering vs. flaming). In recent years, several fire detection products have been developed to provide information of fire radiative power (FRP), location, size, and temperature of fire pixels, but no information regarding fire burning phase is retrieved. The Day-Night band (DNB) aboard Visible Infrared Imaging Radiometer Suite (VIIRS) is sensitive to visible light from flaming fires in nighttime scenes. In contrast, VIIRS 4 m moderate resolution band #13 (M13), though capable of detecting fires at all phases, has no direct sensitivity for discerning fire phase. However, the hybrid usage of VIIRS DNB and M-bands data is hampered by their different scanning technology and spatial resolution. In this study, we present a novel method to rapidly and accurately resample DNB pixel radiances to the footprint of M-band pixels, accounting for onboard detector aggregation schemes and bowtie effect removals. The visible energy fraction (VEF) is subsequently introduced as an indicator of fire burning phase VEF is calculated as the ratio of visible light power (VLP) to FRP for each fire pixel retrieved from the VIIRS 750 m active fire product. A global distribution of VEF values, and thereby the fire phase, is quantitatively obtained, showing smaller VEF values in regions with mostly smoldering wildfires, such as peatland fires in Indonesia, larger VEF values in regions with flaming wildfires over grasslands and savannas in the sub-Sahelian region, and the largest VEF values associated with gas flaring in the Middle East. Mean VEF for different land cover types or regions is highly correlated with modified combustion efficiency (MCE). These results, together with a case study of the 2018 California Camp Fire, show that the VEF has the potential to be an indicator of fire combustion phase for each fire pixel, appropriate for estimating emission factors at the satellite pixel level.

Jun Wang↗

Characterization and Application of Artificial Light Sources for Nighttime Aerosol Optical Depth Retrievals using the Visible Infrared Imager Radiometer Suite Day/Night Band

Using nighttime observations from Visible Infrared Imager Radiometer Suite (VIIRS) Day/Night band (DNB), the characteristics of artificial light sources are evaluated as functions of observation conditions, and incremental improvements are documented on nighttime aerosol retrievals using VIIRS DNB data on a regional scale. We find that the standard deviation of instantaneous radiance for a given artificial light source is strongly dependent upon the satellite viewing angle but is weakly dependent on lunar fraction and lunar angle. Retrieval of nighttime aerosol optical thickness (AOT) based on the novel use of these artificial light sources is demonstrated for three selected regions (United States, Middle East and India) during 2015. Reason-able agreement is found between nighttime AOTs from the VIIRS DNB and temporally adjacent daytime AOTs from the AErosol RObotic NETwork (AERONET) as well as from coincident nighttime AOT retrievals from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), indicating the potential of this method to begin filling critical gaps in diurnal AOT information at both regional and global scales. Issues related to cloud, snow and ice contamination during the winter season, as well as data loss due to the misclassification of thick aerosol plumes as clouds, must be addressed to make the algorithm operationally robust.

Jianglong Zhang↗

Sensitivity studies of nighttime top-of-atmosphere radiances from artificial light sources using a 3-D radiative transfer model for nighttime aerosol retrievals

By accounting for surface-based light source emissions and top-of-atmosphere (TOA) downward lunar fluxes, we adapted the spherical harmonics discrete ordinate method (SHDOM) 3-dimensional (3-D) radiative transfer model (RTM) to simulate nighttime 3-D TOA radiances as observed from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi-NPP satellite platform. Used previously for daytime 3-D applications, these new SHDOM enhancements allow for the study of the impacts of various observing conditions and aerosol properties on simulated VIIRS-DNB TOA radiances. Observations over Dakar, Senegal, selected for its bright city lights and a large range of aerosol optical depth (AOD), were investigated for potential applications and opportunities for using observed radiances containing VIIRS-DNB “bright pixels” from artificial light sources to conduct aerosol retrievals. We found that using the standard deviation (SD) of such bright pixels provided a more stable quantity for nighttime AOD retrievals than direct retrievals from TOA radiances. Further, both the mean TOA radiance and SD of TOA radiances over artificial sources are significantly impacted by satellite viewing angles. Light domes, the enhanced radiances adjacent to artificial light sources, are strong functions of aerosol properties and especially aerosol vertical distribution, which may be further utilized for retrieving aerosol layer height in future studies. Through inter-comparison with both day- and nighttime Aerosol Robotic Network (AERONET) data, the feasibility of retrieving nighttime AODs using 3-D RTM SHDOM over artificial light sources was demonstrated. Our study shows strong potential for using artificial light sources for nighttime AOD retrievals, while also highlighting larger uncertainties in quantifying surface light source emissions. This study underscores the need for surface light emission source characterizations as a key boundary condition, which is a complex task that requires enhanced input data and further research. We demonstrate how quality-controlled nighttime light data from NASA’s Black Marble product suite could serve as a primary input into estimations of surface light source emissions for nighttime aerosol retrievals.

Jianglong Zhang↗

Ice dynamics at the mouth of ice stream B, Antarctica

Data collected in the region of the mouth of ice stream B, West Antarctica, during three field seasons are presented. The physical characteristics of the mouth of ice stream B are described, and the dynamics in the vicinity of the DNB network are discussed. The dynamics of ice stream B from DNB to the grounding line is briefly considered, and a force analysis of the grounding line region is made. The results demonstrate that the dynamic situation of the region at the mouth of ice stream B is distinctly different from either the greater portion of the ice stream upstream or the Ross ice shelf downstream.

Bindschadler, R. A.↗

Sensitive, Selective Test For Hydrazines

Derivatives of hydrazines formed, then subjected to gas chromatography and detected via chemiluminescence. In method of detecting and quantifying hydrazine vapors, vapors reacted with dinitro compound to enhance sensitivity and selectivity. Hydrazine (HZ), monomethyl hydrazine, (MMH), and unsymmetrical dimethylhydrazine (UDMH) analyzed quantitatively and qualitatively, either alone or in mixtures. Vapors collected and reacted with 2,4-dinitrobenzaldehyde, (DNB), making it possible to concentrate hydrazine in derivative form, thereby increasing sensitivity to low initial concentrations. Increases selectivity because only those constituents of sample reacting with DNB concentrated for analysis.

Roundbehler, David↗

Suomi NPP VIIRS Prelaunch and On-orbit Geometric Calibration and Characterization

The Visible Infrared Imager Radiometer Suite (VIIRS) sensor was launched 28 October 2011 on the Suomi National Polarorbiting Partnership (SNPP) satellite. VIIRS has 22 spectral bands covering the spectrum between 0.412 m and 12.01 m, including 16 moderate resolution bands (M-bands) with a spatial resolution of 750 m at nadir, 5 imaging resolution bands (I-bands) with a spatial resolution of 375 m at nadir, and 1 day-night band (DNB) with a near-constant 750 m spatial resolution throughout the scan. These bands are located in a visible and near infrared (VisNIR) focal plane assembly (FPA), a short- and mid-wave infrared (SWMWIR) FPA and a long-wave infrared (LWIR) FPA. All bands, except the DNB, are co-registered for proper environmental data records (EDRs) retrievals. Observations from VIIRS instrument provide long-term measurements of biogeophysical variables for climate research and polar satellite data stream for the operational communitys use in weather forecasting and disaster relief and other applications. Well Earth-located (geolocated) instrument data is important to retrieving accurate biogeophysical variables. This paper describes prelaunch pointing and alignment measurements, and the two sets of on-orbit correction of geolocation errors, the first of which corrected error from 1,300 m to within 75 m (20 I-band pixel size), and the second of which fine tuned scan angle dependent errors, bringing VIIRS geolocation products to high maturity in one and a half years of the SNPP VIIRS on-orbit operations. Prelaunch calibration and the on-orbit characterization of sensor spatial impulse responses and band-to-band co-registration (BBR) are also described.

Geolocation↗

S-NPP and N20 VIIRS RSB Bands Detector-to-Detector Calibration Differences Assessment Using a Homogeneous Ground Target

The S-NPP and N20 satellites have successfully operated since their launches on October 28, 2011 and November 18, 2017, respectively. This paper provides an assessment of the detector calibration stability for the reflective solar bands (RSBs) observed from both S-NPP and N20 VIIRS. Top-of-atmosphere radiances from near-nadir observations over the homogeneous Libya 4 desert site are extracted from the S-NPP VIIRS Collection 1 and N20 Collection 2 Level-1B products. The radiances from individual detectors per Half‐angle Mirror side are studied. The comparisons of the normalized radiance to all detector average values indicate that the detector calibration differences are wavelength dependent. The S-NPP detector differences have been slowly increasing in the past 8.5 years and bands M1-M4 have 1.3%- 2.2% detector differences in 2019. N20 detector differences are stable and small in the past two years except SWIR M bands. N20 M10 and M11 have 1.3% and 2.1% detector differences, respectively. S-NPP DNB detector differences are about 0.8% and N20 DNB detector differences are about 0.5%. Most bands HAM side differences are less than 0.25% in the past years except N20 VIIRS M1 HAM side differences are 0.57% in 2018 and 0.54% in 2019. The Libya 4 images have small but noticeable striping in S-NPP M1-M4 data as well as in N20 M1, M8, M10, and M11 data. These study results have been applied in the S-NPP Collection 2 new algorithm to remove the detector differences. This research help scientists and VIIRS users better understand detector calibration differences in different version VIIRS products.

Libya 4↗

Silicon controlled rectifier polyphase bridge inverter commutated with gate-turn-off thyristor

A polyphase SCR inverter (10) having N switching poles, each comprised of two SCR switches (1A, 1B; 2A, 2B . . . NA, NB) and two diodes (D1B; D1B; D2A, D2B . . . DNA, DNB) in series opposition with saturable reactors (L1A, L1B; L2A, L2B . . . LNA, LNB) connecting the junctions between the SCR switches and diodes to an output terminal (1, 2 . . . 3) is commutated with only one GTO thyristor (16) connected between the common negative terminal of a dc source and a tap of a series inductor (14) connected to the positive terminal of the dc source. A clamp winding (22) and diode (24) are provided, as is a snubber (18) which may have its capacitance (c) sized for maximum load current divided into a plurality of capacitors (C.sub.1, C.sub.2 . . . C.sub.N), each in series with an SCR switch S.sub.1, S.sub.2 . . . S.sub.N). The total capacitance may be selected by activating selected switches as a function of load current. A resistor 28 and SCR switch 26 shunt reverse current when the load acts as a generator, such as a motor while braking.

Edwards, Dean B.↗

SPoRT Participation in the GOES-R and JPSS Proving Grounds

For the last several years, the NASA Short-term Prediction Research and Transition (SPoRT) project at has been working with the various algorithm working groups and science teams to demonstrate the utility of future operational sensors for GOES-R and the suite of instruments for the JPSS observing platforms. For GOES-R, imagery and products have been developed from polar-orbiting sensors such as MODIS and geostationary observations from SEVIRI, simulated imagery, enhanced products derived from existing GOES satellites, and data from ground-based observing systems to generate pseudo or proxy products for the ABI and GLM instruments. The suite of products include GOES-POES basic and RGB hybrid imagery, total lightning flash products, quantitative precipitation estimates, and convective initiation products. SPoRT is using imagery and products from VIIRS, CrIS, ATMS, and OMPS to show the utility of data and products from their operational counterparts on JPSS. The products include VIIRS imagery in swath form, the GOES-POES hybrid, a suite of RGB products including the air mass RGB using water vapor and ozone channels from CrIS, and several DNB products. Over a dozen SPoRT collaborative WFOs and several National Centers are involved in an intensive evaluation of the operational utility of these products.

Jedlovec, Gary↗

Land, Cryosphere, and Nighttime Environmental Products from Suomi NPP VIIRS: Overview and Status

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-orbiting Partnership (S-NPP: http://npp.gsfc.nasa.gov/). VIIRS was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer (AVHRR) and provide observation continuity with NASA's Earth Observing System's (EOS) 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 derived 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 former National Polar-orbiting Environmental Satellite System (NPOESS). 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 will present 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 (http://viirsland.gsfc.nasa.gov/index.html). The paper will also discuss new capabilities being developed at NASA's Land Product Evaluation and Test Element (http://landweb.nascom.nasa.gov/NPP_QA/); including downstream data and products derived from the VIIRS Day/Night Band (DNB).

land cover land use↗