Search NASA⌕ Search

SEARCH · Search NASA

Results for “SNPP”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

The NASA OBPG 2020 On-Orbit Calibration of SNPP VIIRS for Ocean Color Applications

The NASA Ocean Biology Processing Group (OBPG) has continued monitoring the SNPP VIIRS on-orbit calibration for bands M1-M11 over its mission to optimize the calibration for ocean color applications. The OBPG has recently implemented several changes to the calibration scheme: using solar-derived f-factors to detrend the lunar observations; using long-term exponentials of time as basis vectors (along with libration angles) for radiometric fits to any resulting lunar temporal drifts; deriving gain adjustments to the solar f-factors from these exponentials; and deriving gain adjustments due to modulated RSRs outside of the solar/lunar calibration using TOA reference spectra. These calibration changes minimize the impact of uncertainties in any one component of the calibration on the derived f-factors. The final f-factors incorporate VIIRS solar diffuser measurements, h-factor BRDF corrections, lunar-derived gains, and modulated RSR gains. The combined BRDF corrections, lunar gain adjustments, and mRSR gain adjustments define effective h-factors for each band. The improvements in the on-orbit calibration are validated by evaluation of globally-derived anomaly plots of remote sensing reflectance for the ocean color bands. The ultimate goal of the OBPG calibration effort is incorporation of a consistent SNPP VIIRS ocean color data set into the NASA multi-mission ocean color climate data record.

VIIRS↗
NASA NTRS2020

Performance Assessments of the SNPP and N20 VIIRS DNB 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 multi-spectral Earth-observing instrument with spectral channels ranging from the visible to the long-wave infrared. In addition to these spectral channels, the VIIRS instrument features a panchromatic Day/Night band (DNB) with 3 gain stages (low, mid, and high) which allows for Earth-view (EV) radiance retrievals over 7 orders of magnitude. The DNB is able to collect data ranging from dim city lights during nighttime up to reflected sunlight from cloud-tops during daytime. The DNB data collection is divided into 32 aggregation modes, where sub-pixel aggregation is used to maintain a nearly constant pixel footprint on ground during EV data collection throughout each scan. The DNB is also sensitive enough to observe bright stars through the instrument space-view (SV) port. Data from these bright stars can be used to track the temporal stability of the sensor gain and as a method of intercomparison between the two VIIRS instruments. In this work, we will present several sensor performance assessments of the VIIRS DNB using stars. In addition to the sensor gain trending, these assessments will include a comparison of the differences between the daytime and nighttime data due to the effects of stray-light, a comparison of the measured signal as a function of aggregation mode, a comparison between the two high-gain sub-stages, and half-angle mirror side for both the SNPP and N20 VIIRS DNB.

VIIRS↗
NASA NTRS2023

SNPP and N20 VIIRS Day/Night Band (DNB) Calibration and Performance

The first two Visible Infrared Imaging Radiometer Suite (VIIRS) instruments, on-board the Suomi National Polar-orbiting Partnership (SNPP) and the NOAA-20 (N20) satellites, have been operating for over 11 and 5 years since their launches on28 October 2011 and 18 November 2017 respectively. The day-night band (DNB) onboard VIIRS is a panchromatic visible/near-infrared (Vis/NIR) channel designed to detect radiance from the brightest daytime scenes down to very dim nighttime scenes illuminated by a quarter moon. In this paper, we present the SNPP and N20 VIIRS DNB calibration results performed by the NASA VIIRS Characterization Support Team (VCST) to generate the calibration coefficient look up tables (LUTs) for the latest NASA Level 1B Collection 2 products. The differing DNB straylight contamination between VIIRS instruments is discussed along with the correction methodology and performance.

Junqiang Sun↗
NASA NTRSDate not supplied

Estimating Bidirectional Reflectance and Monitoring Stability of SNPP-VIIRS Reflective Solar Bands Using A Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System project provides the scientific community with observed top-of-atmosphere shortwave and longwave fluxes for climate monitoring and climate model validation. To provide consistent VIIRS cloud retrievals, the CERES Imager and Geostationary Calibration Group (IGCG) must understand and quantify the stability of the VIIRS instruments. To achieve this, the IGCG utilizes tropical deep convective clouds (DCCs) as invariant targets. Proper seasonal characterization of the DCC bidirectional reflectance distribution function (BRDF) is key to the success of DCC-based calibration methods, particularly for shortwave infrared (SWIR) bands. This article proposes the use of a deep neural network (DNN) to characterize VIIRS solar reflective band BRDF reflectance, with which individual channel trends are isolated by manipulating the DNN time input. Initial results show that the DNN method can extract statistically significant SNPP-VIIRS band trends, using only SNPP-VIIRS inputs, that are correlative to and match the magnitude of significant trends determined using methods that rely on an external angular distribution model. It may be possible to apply this approach to actively monitor the stability of new instruments without the need for predetermined seasonal BRDF corrections.

Benjamin Scarino↗
NASA NTRS2017

SNPP VIIRS RSB Earth View Reflectance Uncertainty

The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite uses its 14 reflective solar bands to passively collect solar radiant energy reflected off the Earth. The Level 1 product is the geolocated and radiometrically calibrated top-of- the-atmosphere solar reflectance. The absolute radiometric uncertainty associated with this product includes contributions from the noise associated with measured detector digital counts and the radiometric calibration bias. Here, we provide a detailed algorithm for calculating the estimated standard deviation of the retrieved top-of-the-atmosphere spectral solar radiation reflectance.

VIIRS↗
NASA NTRS2020

SNPP and N20 VIIRS Solar Vector Orientation Knowledge Error Detected by SDSM Sun Views

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a passive scanning Earth observing satellite radiometer. The VIIRS has 22 spectral bands with design center wavelengths from 0.41 to 12.01 μm, providing data to generate more than 20 Earth’s biogeophysical parameters. Fourteen of the 22 VIIRS bands are the reflective solar bands (RSBs), detecting Earth reflected sunlight. To ensure data quality, regular on-orbit radiometric calibrations of the RSBs are performed, mainly through observations of an onboard solar diffuser (SD). The spectral radiance provided by the sunlit SD depends on the SD screen transmittance which is a function of the solar vector orientation. Additionally, on orbit the SD’s bidirectional reflectance distribution function (BRDF) changes its value due to solar bombardment. The BRDF change is derived from the SD stability monitor (SDSM) measurements. The SDSM views the Sun through a screen with through holes (the SDSM screen) and the SD at almost the same time. The time series of the ratio of the signal strengths is a measure of the SD BRDF on-orbit change. Hence the measurements of the on-orbit SD BRDF change depends on the SDSM screen relative transmittance which is also solar vector orientation dependent. In this paper for both the SNPP and the NOAA-20 VIIRS instruments we examine the solar vector orientation knowledge error through matching the SDSM screen relative effective transmittances derived from the calibration data collected on the yaw maneuver and the regular orbits.

SNPP↗
NASA NTRS2019

On-Orbit Tracking of Sub-Sample Gain Differences in SNPP and NOAA-20 VIIRS Imagery Bands

The VIIRS instruments on board the SNPP and NOAA-20 (N20) satellites have 14 reflective solar bands covering a spectral range from 412 nm to 2250 nm. Three of these are imaging bands (I bands) with a nadir spatial resolution of 375 m and 11 are moderate resolution bands (M bands) with a resolution of 750 m. The higher resolution in the I bands is achieved by a combination of more detectors, with the I bands having twice as many detectors of half the size for every M band detector, and a higher data rate, with the I bands having two sub-samples for every sample of M band data. To ensure calibration accuracy, any systematic difference in the response of the two sub-samples needs to be monitored and corrected in the calibrated products. In this paper, we use the solar diffuser calibrations to monitor the gain differences between the two sub-samples of the I bands both as a function of time and signal level. We find gain differences of about 0.1% for I1, 0.3% for I2, and <0.1% for I3 that are mostly constant over the range of signal values available in the SD calibration. These values are mostly consistent throughout the mission for both instruments. The results are remarkably similar for the two VIIRS instruments, including a slightly out-of-family behavior seen in a few detectors. We discuss possible causes for the difference and the impact on the aggregated Earth view images.

On-orbit↗
NASA NTRS2021

Deconvolution of SNPP VIIRS Solar Diffuser Bidirectional Reflectance Distribution Function On-orbit Change Factor

The Earth-observing Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite regularly calibrates its reflective solar bands (RSBs), primarily through observing an onboard sunlit solar diffuser (SD). The on-orbit change of the value of the SD bidirectional reflectance distribution function (BRDF) is quantified by a numerical factor, called the H-factor, and is determined by the onboard SD stability monitor (SDSM). Because the spectral response function of an SDSM detector spreads in wavelength, the directly measured H-factor is the true H-factor convolved with the spectral response function. To find the true H-factor, we use the traditional direct method and an innovative iterative approach to separately deconvolve the measured H-factor. Our iterative approach relies on two properties of the SDSM detector spectral response function: the central peak width is narrow enough so that the H-factor does not change much over the peak width, and the dominance of the spectral response function’s integral with respect to the wavelength over the width. The iterative approach is more accurate, of a smaller noise impact, much more flexible in terms of interpolation and extrapolation of function values, and faster. We have used deconvolved H-factors to calibrate the NASA SNPP VIIRS RSB Collections 1 and 2 Level-1B products.

SNPP VIIRS↗
NASA NTRS2013

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↗
NASA NTRS2015

Determination of the SNPP VIIRS SDSM Screen Relative Transmittance From Both Yaw Maneuver and Regular On-Orbit Data

The Visible Infrared Imaging Radiometer Suiteaboard the Suomi National Polar-orbiting Partnership (SNPP) satellite performs radiometric calibration of its reflective solar bands primarily through observing a sunlit onboard solar diffuser (SD). The SD bidirectional reflectance distribution function(BRDF) degradation factor is determined by an onboard SD stability monitor (SDSM), which observes the Sun through a pinhole screen and the sunlit SD. The transmittance of the SDSM pinhole screen over a range of solar angles was determined prelaunch and used initially to determine the BRDF degradation factor.The degradation-factor-versus-time curves were found to have a number of very large unphysical undulations likely due to the inaccuracy in the prelaunch determined SDSM screen transmittance.To refine the SDSM screen transmittance, satellite yaw maneuvers were carried out. With the SDSM screen relative transmittance determined from the yaw maneuver data, the computed BRDFdegradation factor curves still have large unphysical ripples, indicating that the projected solar horizontal angular step size in the yaw maneuver data is too large to resolve the transmittance at a fine angular scale. We develop a methodology to use both the yaw maneuver and a small portion of regular on-orbit data to determine the SDSM screen relative transmittance at a fine angular scale. We determine that the error standard deviation of the calculated relative transmittance ranges from 0.00030 (672 nm) to 0.00092 (926 nm). With the newly determined SDSM screen relative transmittance, the computed BRDF degradation factor behaves much more smoothly over time.

Lei, Ning↗
NASA NTRS2016

Functional Form of the Radiometric Equation for the SNPP VIIRS Reflective Solar Bands: An Initial Study

The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite is a passive scanning radiometer and an imager, observing radiative energy from the Earth in 22 spectral bands from 0.41 to 12 microns which include 14 reflective solar bands (RSBs). Extending the formula used by the Moderate Resolution Imaging Spectroradiometer instruments, currently the VIIRS determines the sensor aperture spectral radiance through a quadratic polynomial of its detector digital count. It has been known that for the RSBs the quadratic polynomial is not adequate in the design specified spectral radiance region and using a quadratic polynomial could drastically increase the errors in the polynomial coefficients, leading to possible large errors in the determined aperture spectral radiance. In addition, it is very desirable to be able to extend the radiance calculation formula to correctly retrieve the aperture spectral radiance with the level beyond the design specified range. In order to more accurately determine the aperture spectral radiance from the observed digital count, we examine a few polynomials of the detector digital count to calculate the sensor aperture spectral radiance.

Lei, Ning↗
NASA NTRS2017

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 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 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 non-linear 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 (FWHM) as an approximation of the sensor field of view (FOV) for all bands, and compare these on-orbit measured values with prelaunch laboratory results.

Tilton, James C.↗
NASA NTRS2023

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

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

MAIAC↗
NASA NTRS2020

SNPP VIIRS RSB on-orbit radiometric calibration algorithms Version 2.0 and the performances. Part I: The algorithms

The first VIIRS instrument is aboard the Suomi National Polar-orbiting Partnership satellite. The instrument has 14 reflective solar bands (RSBs) to passively collect photons reflected from the Earth surface in the design wavelengths from 412 to 2250 nm. The instrument uses a solar diffuser (SD) to radiometrically calibrate its RSBs. When lit by the Sun through an attenuation screen (the SD screen), the SD diffusely reflects off the incident sunlight to act as a radiance source for the calibration. An onboard solar diffuser stability monitor (SDSM) yields the on-orbit change of the SD bidirectional reflectance distribution function (BRDF) by comparing the signal strength from the SD with that from the Sun attenuated by another attenuation screen (the SDSM screen). Complications arise due to the discovery that the on-orbit change of the BRDF is angle dependent. Additionally, the SDSM does not cover the wavelengths for the short-wave infrared bands in the RSBs. Furthermore, satellite yaw maneuvers were performed in the early mission to yield data for refining the prelaunch SDSM screen relative effective transmittance and the relative product of the SD screen transmittance and the BRDF at the mission start. But the yaw maneuver data are coarse in the solar azimuth angles and thus are unable to yield accurate values between the measurement angles. Over the years of performing on-orbit radiometric calibration through the SD for the VIIRSRSBs, we have developed several highly effective calibration algorithms to address the issues mentioned above. This paper reviews these algorithms.

on-orbit cailbration↗
NASA NTRS2020

Assessment of SNPP VIIRS RSB detector-to-detector differences using deep convective clouds and deserts

An accurate on-orbit characterization of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership satellite is essential to satisfy the requirements from NOAA, NASA, and the general research community for high-quality operational and research products. NASA’s Land Science Investigator-led Processing System (LSIPS) sensor data records (SDRs) are utilized to assess the stability of the calibrated top of atmosphere reflectance over the deep convective clouds (DCCs) and over the Libya-4desert site. The results from DCCs and desert show detector-to-detector (D2D) reflectance differences in the VIIRS reflective solar bands, 10 moderate-resolution bands (M-bands, M1to M5, M7 to M11), and three imagery resolution bands (I-bands, I1-I3). More importantly, the D2D differences exhibit an increase in magnitude over time for bands M1 to M5 and I1to I2, which induces noticeable striping and higher uncertainties in the downstream data products. The largest D2D difference is observed in bands M1 and M2, with magnitudes greater than1.8% in trends among the 16 detectors and standard deviations less than 0.12% over time. TheD2D stability assessment results over DCCs are consistent with those observed over the Libya-4desert site. To improve the quality of the calibrated SDR reflectance data, NASA’s VIIRS characterization support team has improved the calibration algorithm to incorporate corrections based on these DCC measurements to mitigate the striping (detector differences) observed in the current version of the SDR. These improvements are planned to be included in the next mission reprocessing of the LSIPS land products.

SNPP VIIRS↗
NASA NTRS2016

Second SNPP Cal/Val Campaign: Environmental Data Retrieval Analysis

Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change science. The Suomi National Polar-orbiting Partnership (Soumi NPP) satellite Environmental Data Records (EDRs) are retrieved from calibrated ultraspectral radiance or Sensor Data Records (SDRs). Understanding the accuracy of retrieved EDRs is critical. The second Suomi NPP Calibration/Validation field campaign was conducted during March 2015 with flights over Greenland. The NASA high-altitude ER-2 aircraft carrying ultraspectral interferometer sounders such as the National Airborne Sounder Testbed-Interferometer (NAST-I) flew under the Suomi NPP satellite that carries the Crosstrack Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). Herein we inter-compare the EDRs produced from different retrieval algorithms employed on these satellite and aircraft campaign data. The available radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses are used to assess atmospheric temperature and moisture retrievals from the aircraft and satellite platforms. Preliminary results of this experiment under a winter, Arctic environment are presented.

Zhou, Daniel K.↗