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At least 19 records

VIIRS DNB time-dependent stray light correction

The stray light contamination of the VIIRS Day-Night-Band (DNB) on-board the S-NPP satellite has been studied intensively. To alleviate its impact, a stray light correction look-up-table (LUT), which represents the stray light contamination, is derived from the new moon night dataset by subtracting the non stray light signal from the stray light affected signal. The derived LUT can be used to remove the majority of the contamination. However, the LUT remains static until the next update to the Level-1B data processing, usually one month later. Between these two updates, changes in the actual stray light are not captured. We present a method to derive a dynamic stray light correction LUT that covers the time period between updates. By analyzing the patterns in the annual stray light variation, a consistent trend was found in the LUT’s characteristic features which can be quantitatively expressed as time factors. These factors are then applied to the monthly LUT to produce a dynamic stray light LUT for any time of interest. The L1B software can use this algorithm to calculate the LUTs at the time of observation. The results show significant improvement in the DNB product compared to using the monthly static LUT. Furthermore, this time-dependent algorithm provides a basis for deriving a universal stray light correction LUT for VIIRS.

VIIRS↗

New VIIRS DNB Stray Light Correction Method

The Day/Night Band (DNB) broadband (500-900nm) imager is one of the sensors in the Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the Suomi National Polar-orbiting Partnership (SNPP) and the NOAA-20 satellites, which are polar-orbiting and fly at about 830km above the surface of the Earth. Depending on the satellite location and the sensor viewing geometry, for a short period just before (or after) the satellite enters into (or emerges from) the shadow of the Earth, unwanted stray light, seemingly caused by the reflection of solar beam on the slightly exposed inner side of the leading (or trailing) nadir door, can enter the instrument and impose noticeable impacts to a narrow portion of DNB satellite images in every orbit. The impacted images can be modified to look normal, and the current DNB stray light correction algorithm empirically assigns corrections. There is also an alternative approach using image-processing techniques. Both methods rely mainly on the stray light impacted measurements. To simplify the approach and for better correction results, the new method presented in this paper incorporates the observed asymptotic nature of measurements surrounding the stray light impacted region by fitting to the drop off in sun light from day to night. The new method can be applied to the raw measurements in real-time, and it can help to advance our understanding of this special type of DNB stray light that happens over the polar regions

VIIRS↗

SIMBIOS Normalized Water-Leaving Radiance Calibration and Validation: Sensor Response, Atmospheric Corrections, Stray Light and Sun Glint

This Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) contract supports acquisition of match up radiometric and bio-optical data for validation of Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and other ocean color satellites, and evaluation of uncertainty budgets and protocols for in situ measurements of normalized water leaving radiances.

Mueller, James L.↗

Stray-Light Correction of the Marine Optical Buoy

In ocean-color remote sensing, approximately 90% of the flux at the sensor originates from atmospheric scattering, with the water-leaving radiance contributing the remaining 10% of the total flux. Consequently, errors in the measured top-of-the atmosphere radiance are magnified a factor of 10 in the determination of water-leaving radiance. Proper characterization of the atmosphere is thus a critical part of the analysis of ocean-color remote sensing data. It has always been necessary to calibrate the ocean-color satellite sensor vicariously, using in situ, ground-based results, independent of the status of the pre-flight radiometric calibration or the utility of on-board calibration strategies. Because the atmosphere contributes significantly to the measured flux at the instrument sensor, both the instrument and the atmospheric correction algorithm are simultaneously calibrated vicariously. The Marine Optical Buoy (MOBY), deployed in support of the Earth Observing System (EOS) since 1996, serves as the primary calibration station for a variety of ocean-color satellite instruments, including the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Japanese Ocean Color Temperature Scanner (OCTS) , and the French Polarization and Directionality of the Earth's Reflectances (POLDER). MOBY is located off the coast of Lanai, Hawaii. The site was selected to simplify the application of the atmospheric correction algorithms. Vicarious calibration using MOBY data allows for a thorough comparison and merger of ocean-color data from these multiple sensors.

Brown, Steven W.↗

Radiometric and spectral stray light correction for the Portable Remote Imaging Spectrometer (PRISM) coastal ocean sensor

The airborne Portable Remote Imaging Spectrometer (PRISM) instrument is based on a fast (F/1.8) Dyson spectrometer operating at 350-1050 nm and a two-mirror telescope combined with a Teledyne HyViSI 6604A detector array. Raw PRISM data contain electronic and optical artifacts that must be removed prior to radiometric calibration. We provide an overview of the process transforming raw digital numbers to calibrated radiance values. Electronic panel artifacts are first corrected using empirical relationships developed from laboratory data. The instrument spectral response functions (SRF) are reconstructed using a measurement-based optimization technique. Removal of SRF effects from the data improves retrieval of true spectra, particularly in the typically low-signal near-ultraviolet and near-infrared regions. As a final step, radiometric calibration is performed using corrected measurements of an object of known radiance. Implementation of the complete calibration procedure maximizes data quality in preparation for subsequent processing steps, such as atmospheric removal and spectral signature classification.

Thompson, David R.↗

A Consistent EPIC Visible Channel Calibration using VIIRS and MODIS as a Reference

The Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) satellite constantly images the sunlit disk of Earth from the Lagrange-1 (L1) point in 10 spectral channels spanning the UV, VIS, and NIR spectrums. Recently, the DSCOVR EPIC team has publicly released version 2 dataset, which has implemented improved navigation, stray-light correction, and flat-fielding of the CCD array. The EPIC 2-year data record must be well-calibrated for consistent cloud, aerosol, trace gas, land use and other retrievals. Because EPIC lacks onboard calibrators, the observations made by EPIC channels must be calibrated vicariously using the coincident measurements from radiometrically stable instruments that have onboard calibration systems. MODIS and VIIRS are best-suited instruments for this task as they contain similar spectral bands that are well-calibrated onboard using solar diffusers and lunar tracking. We have previously calibrated the EPIC version 1 dataset by using EPIC and VIIRS angularly matched radiance pairs over both all-sky ocean and deep convective clouds (DCC). We noted that the EPIC image required navigations adjustments, and that the EPIC stray-light correction provided an offset term closer to zero based on the linear regression of the EPIC and VIIRS ray-matched radiance pairs. We will evaluate the EPIC version 2 navigation and stray-light improvements using the same techniques. In addition, we will monitor the EPIC channel calibration over the two years for any temporal degradation or anomalous behavior. These two calibration methods will be further validated using desert and DCC invariant Earth targets. The radiometric characterization of the selected invariant targets is performed using multiple years of MODIS and VIIRS measurements. Results of these studies will be shown at the conference.

Haney, C. O.↗

Algorithm Updates for the Fourth SeaWiFS Data Reprocessing

The efforts to improve the data quality for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data products have continued, following the third reprocessing of the global data set in May 2000. Analyses have been ongoing to address all aspects of the processing algorithms, particularly the calibration methodologies, atmospheric correction, and data flagging and masking. All proposed changes were subjected to rigorous testing, evaluation and validation. The results of these activities culminated in the fourth reprocessing, which was completed in July 2002. The algorithm changes, which were implemented for this reprocessing, are described in the chapters of this volume. Chapter 1 presents an overview of the activities leading up to the fourth reprocessing, and summarizes the effects of the changes. Chapter 2 describes the modifications to the on-orbit calibration, specifically the focal plane temperature correction and the temporal dependence. Chapter 3 describes the changes to the vicarious calibration, including the stray light correction to the Marine Optical Buoy (MOBY) data and improved data screening procedures. Chapter 4 describes improvements to the near-infrared (NIR) band correction algorithm. Chapter 5 describes changes to the atmospheric correction and the oceanic property retrieval algorithms, including out-of-band corrections, NIR noise reduction, and handling of unusual conditions. Chapter 6 describes various changes to the flags and masks, to increase the number of valid retrievals, improve the detection of the flag conditions, and add new flags. Chapter 7 describes modifications to the level-la and level-3 algorithms, to improve the navigation accuracy, correct certain types of spacecraft time anomalies, and correct a binning logic error. Chapter 8 describes the algorithm used to generate the SeaWiFS photosynthetically available radiation (PAR) product. Chapter 9 describes a coupled ocean-atmosphere model, which is used in one of the changes described in Chapter 4. Finally, Chapter 10 describes a comparison of results from the third and fourth reprocessings along the US. Northeast coast.

Hooker, Stanford, B.↗

SeaWiFS Technical Report Series: Case Studies for SeaWiFS Calibration and Validation - Volume 41

This document provides brief reports, or case studies, on a number of investigations sponsored by the Calibration and Validation Team (CVT) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. Chapter I describes the calibration and characterization of the GSFC sphere, which was used in the recent recalibration of the SeaWiFS instrument. Chapter 2 presents a revision of the diffuse attenuation coefficient, K(490), algorithm based on the SeaWiFS wavelengths. Chapter 3 provides an implementation scheme for an algorithm to remove out-of-band radiance when using a sensor calibration based on a finite width (truncated) spectral response function, e.g., between the 1% transmission points. Chapter 4 describes the implementation schemes for the stray light quality flag (local area coverage [LAC] and global area coverage [GAC]) and the LAC stray light correction.

Yeh, Eueng-nan↗

High Precision, Absolute Total Column Ozone Measurements from the Pandora Spectrometer System: Comparisons with Data from a Brewer Double Monochromator and Aura OMI

We present new, high precision, high temporal resolution measurements of total column ozone (TCO) amounts derived from ground-based direct-sun irradiance measurements using our recently deployed Pandora single-grating spectrometers. Pandora's small size and portability allow deployment at multiple sites within an urban air-shed and development of a ground-based monitoring network for studying small-scale atmospheric dynamics, spatial heterogeneities in trace gas distribution, local pollution conditions, photochemical processes and interdependencies of ozone and its major precursors. Results are shown for four mid- to high-latitude sites where different Pandora instruments were used. Comparisons with a well calibrated double-grating Brewer spectrometer over a period of more than a year in Greenbelt MD showed excellent agreement and a small bias of approximately 2 DU (or, 0.6%). This was constant with slant column ozone amount over the full range of observed solar zenith angles (15-80), indicating adequate Pandora stray light correction. A small (1-2%) seasonal difference was found, consistent with sensitivity studies showing that the Pandora spectral fitting TCO retrieval has a temperature dependence of 1% per 3K, with an underestimation in temperature (e.g., during summer) resulting in an underestimation of TCO. Pandora agreed well with Aura-OMI (Ozone Measuring Instrument) satellite data, with average residuals of <1% at the different sites when the OMI view was within 50 km from the Pandora location and OMI-measured cloud fraction was <0.2. The frequent and continuous measurements by Pandora revealed significant short-term (hourly) temporal changes in TCO, not possible to capture by sun-synchronous satellites, such as OMI, alone.

Ozone↗

NASA's Black Marble Product Suite: Validation Strategy

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500m resolution since January 2012 with data fro the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-terrain, vegetation, snow, lunar and stray light corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Current and planned validation activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at difference geographic locations and time periods representing the full range of retrieval conditions.

GEO Human Planet↗

TPSAS-NF1676L-32020-DND

The Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) satellite has a constant unique view of the sunlit disk of the Earth from the Lagrange-1 (L1) point nearly a million miles away from the Earth. The DSCOVR EPIC team released the version 2 dataset last year which included many enhancements, such as improved navigation, stray-light correction, and flat-fielding. Since there is no on-board calibration for EPIC, its 10 spectral channels must be calibrated using other methods, such as inter-calibrating with sensors with on-board calibration hardware. VIIRS is a well-calibrated instrument with similar spectral channels as EPIC. Spectral band induced radiance differences between VIIRS and EPIC are mitigated using Spectral Band Adjustment Factor (SBAF). We will extend the previous calibrations from prior studies to include more recent data by ray-matching EPIC with VIIRS over all-sky tropical ocean (ATO) and deep convective cloud (DCC) conditions. In addition to ATO and DCC ray-matching, we will validate these results by utilizing DCC as invariant targets to monitor sensor degradation. DCC behave as solar diffusers in the tropics and when collectively analyzed can be used to monitor the degradation of the EPIC sensor. Improvement to our dynamic navigation adjustment algorithm, as well as exploring the view angle response of the EPIC CCD array, will be examined for their effectiveness and presented at the conference.

C O Haney↗

Ten Year Ozone Profile Record From Suomi NPP OMPS Limb Profiler

In this study, we evaluate a decadal ozone profile record derived from Suomi NPP Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP). The data from OMPS LP were re-processed with the new retrieval algorithm from 2012 to present. The new reprocessing includes adjustments in both Level 1 and Level 2 algorithms. The sensor’s altitude registration, updates in radiometric calibrations, under-sampling and stray light corrections were addressed in Level 1 processing. The new retrieval algorithm (version 2.7) combines measurements from UV and VIS parts of the spectra to retrieve a single vertical ozone profile between 12.5 km (or cloud tops) and 57.5 km, unlike to previous version 2.5 where ozone profiles were retrieved independently from UV and VIS. To improve ozone retrievals in the Upper Troposphere Lower Stratosphere (UTLS) region, we implemented a new aerosol correction that assumes a gamma-function particle size distribution. In addition, ozone and nitrogen dioxide cross sections and climatologies were updated. We discuss sensitivity of the ozone retrievals to implemented changes in Level 1 and Level 2 algorithms. We focus our analysis on evaluation of the stability of the 10-year record from OMPS LP. We show results from the internal methods for characterizing the stability of the LP altitude registration and compare the LP reflectivity and ozone with the similar quantities measured by OMPS nadir sensors. Finally, we will show results from comparisons with independent satellite (MLS and SAGE III) and ozone sonde measurements.

Ozone↗

SNPP VIIRS Day Night Band: Ten Years of On-Orbit Calibration and Performance

Aboard the polar-orbiting SNPP satellite, the VIIRS instrument has been in operation since launch in October 2011. It is a visible and infrared radiometer with a unique panchromatic channel capability designated as a day-night band (DNB). This channel covers wavelengths from 0.5 to 0.9 µm and is designed with a near-constant spatial resolution for Earth observations 24 h a day. The DNB operates at 3 gain stages (low, middle, and high) to cover a large dynamic range. An onboard solar diffuser (SD) is used for calibration in the low gain stage, and to enable the derivation of gain ratios between the different stages. In this paper, we present the SNPP VIIRS DNB calibration performed by the NASA VIIRS characterization support team (VCST). The DNB calibration algorithms are described to generate the calibration coefficient look up tables (LUTs) for the latest NASA Level 1B Collection 2 products. We provide an evaluation of DNB on-orbit calibration performance. This activity supports the NASA Earth science community by delivering consistent VIIRS sensor data products via the Land Science Investigator-led Processing Systems, including the SD degradation applied for DNB calibrations in detector gain and gain ratio trending. The DNB stray light contamination and its correction are highlighted. Performance validations are presented using comparisons to the calibration methods employed by NOAA’s operational Interface Data Processing Segment. Further work on stray light corrections is also discussed.

VIIRS↗

NASA's Black Marble Nighttime Lights Product Suite

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500 meters resolution since January 2012 with data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-, terrain-, vegetation-, snow-, lunar-, and stray light-corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Key algorithm enhancements include: (1) lunar irradiance modeling to resolve non-linear changes in phase and libration; (2) vector radiative transfer and lunar bidirectional surface anisotropic reflectance modeling to correct for atmospheric and BRDF (Bidirectional Reflectance Distribution Function) effects; (3) geometric-optical and canopy radiative transfer modeling to account for seasonal variations in NTL; and (4) temporal gap-filling to reduce persistent data gaps. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Initial validation results are presented together with example case studies illustrating the scientific utility of the products. This includes an evaluation of temporal patterns of NTL dynamics associated with urbanization, socioeconomic variability, cultural characteristics, and displaced populations affected by conflict. Current and planned activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at different geographic locations and time periods representing the full range of retrieval conditions.

Suomi-NPP↗

Landsat-8 TIRS Thermal Radiometric Calibration Status

The Landsat-8 Thermal Infrared Sensor (TIRS) has been acquiring two-band thermal infrared images of the Earth’s surface since 2013. The calibration of the two-band system has been monitored using the on-board calibrator and validated with vicarious calibration performed by NASA/JPL and RIT since launch. Soon after launch, it was discovered that the instrument had a significant stray light effect that was affecting the radiometric calibration. The stray light was corrected in the processing system in 2017. Since then, it has become apparent that there was an additional radiometric error, based on the vicarious calibration results. With a failure within the primary electronic system and subsequent switch to the redundant electronic system, the TIRS instrument effectively has two separate calibration regimes. The vicarious calibration found a statistically significant calibration error, primarily a constant over time, in Band 11 on the primary electronics (Feb 11,2013 through March 5,2015) of about -0.6K at 300K. The calibration error in Band 10 was smaller though still statistically significant at about 0.2K at 300K. On the redundant side(March 5,2015 to present), the calibration error is more signal dependent than time dependent. Both bands are affected, with Band 10 having an error between 1K and -0.4K (between 273-320K) and Band 11 having an error between 0.8K and -1.44K (between 273-320K).This calibration error will be corrected within the USGS Landsat Product Generation System with the release of Landsat Collection-2 products. The Collection-2 release also includes a correction to the relative radiometric calibration of TIRS data. Striping as a result of poor detector-to-detector normalization has been increasing in the imagery since launch. The TIRS relative radiometric calibration will be updated based on internal calibrator data to remove the stripes on a quarterly basis. The visible stripes are generally at 0.1-0.2% level, though there are some detectors in each band that have changed by 1% or more. The Collection-2 release will result in much more uniform TIRS images.

Julia A Barsi↗

OMPS Limb Profiler Instrument Performance Assessment

Following the successful launch of the Ozone Mapping and Profiler Suite (OMPS) aboard the Suomi National Polar-orbiting Partnership (SNPP) spacecraft, the NASA OMPS Limb team began an evaluation of instrument and data product performance. The focus of this paper is the instrument performance in relation to the original design criteria. Performance that is closer to expectations increases the likelihood that limb scatter measurements by SNPP OMPS and successor instruments can form the basis for accurate long-term monitoring of ozone vertical profiles. The team finds that the Limb instrument operates mostly as designed and basic performance meets or exceeds the original design criteria. Internally scattered stray light and sensor pointing knowledge are two design challenges with the potential to seriously degrade performance. A thorough prelaunch characterization of stray light supports software corrections that are accurate to within 1% in radiances up to 60 km for the wavelengths used in deriving ozone. Residual stray light errors at 1000nm, which is useful in retrievals of stratospheric aerosols, currently exceed 10%. Height registration errors in the range of 1 km to 2 km have been observed that cannot be fully explained by known error sources. An unexpected thermal sensitivity of the sensor also causes wavelengths and pointing to shift each orbit in the northern hemisphere. Spectral shifts of as much as 0.5nm in the ultraviolet and 5 nm in the visible, and up to 0.3 km shifts in registered height, must be corrected in ground processing.

ozone↗

SeaWiFS technical report series. Volume 31: Stray light in the SeaWiFS radiometer

Some of the measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) will not be useful as ocean measurements. For the ocean data set, there are procedures in place to mask the SeaWiFS measurements of clouds and ice. Land measurements will also be masked using a geographic technique based on each measurment's latitude and longitude. Each of these masks involves a source of light much brighter than the ocean. Because of stray light in the SeaWiFS radiometer, light from these bright sources can contaminate ocean measurements located a variable number of pixels away from a bright source. In this document, the sources of stray light in the sensor are examined, and a method is developed for masking measurements near bright targets for stray light effects. In addition, a procedure is proposed for reducing the effects of stray light in the flight data from SeaWiFS. This correction can also reduce the number of pixels masked for stray light. Without these corrections, local area scenes must be masked 10 pixels before and after bright targets in the along-scan direction. The addition of these corrections reduces the along-scan masks to four pixels before and after bright sources. In the along-track direction, the flight data are not corrected, and are masked two pixels before and after. Laboratory measurements have shown that stray light within the instrument changes in a direct ratio to the intensity of the bright source. The measurements have also shown that none of the bands show peculiarities in their stray light response. In other words, the instrument's response is uniform from band to band. The along-scan correction is based on each band's response to a 1 pixel wide bright sources. Since these results are based solely on preflight laboratory measurements, their successful implementation requires compliance with two additional criteria. First, since SeaWiFS has a large data volume, the correction and masking procedures must be such that they can be converted into computationally fast algorithms. Second, they must be shown to operate properly on flight data. The laboratory results, and the corrections and masking procedures that derive from them, should be considered as zeroeth order estimates of the effects that will be found on orbit.

Hooker, Stanford B.↗