Inter-Comparison of S-NPP VIIRS and Aqua MODIS Thermal Emissive Bands Using Hyperspectral Infrared Sounder Measurements as a Transfer Reference

Li, Yonghong; Wu, Aisheng; Xiong, Xiaoxiong

doi:10.3390/rs8010072

Cited by 14 publications

(13 citation statements)

References 20 publications

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“…Specifically, only the channels with a quality assurance value less than 3 were used. Similar approaches have been used for various other studies and therefore been confirmed as an efficient and reliable method suitable for the MODIS‐AIRS intercalibration study here (Efremova et al, ; Li et al, ; Li et al, ; A. Wu et al, ). The Simultaneous Nadir Overpass (SNO) data sets of IASI and MODIS are collected from two pairs of IASI footprints from each side of nadir and MODIS pixels in a range of ±10° near the nadir frame.…”

Section: Application On Real Airs/modis Datasupporting

confidence: 57%

Section: 1029/2018jd028585mentioning

confidence: 59%

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An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral Sensors

Liu

Xiong

et al. 2018

JGR Atmospheres

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The intercalibration between a broadband and a hyperspectral satellite Earth observation system requires the convolution of the hyperspectral data with the spectral response functions (SRFs) of the corresponding broadband channels. There are two potential issues associated with the convolution procedure. First, the finite resolution of a hyperspectral spectrum, that is, the deviation from the highly accurate line‐by‐line monochromatic radiances, will contribute to convolution errors. The magnitude of the errors depends on the spectral resolution and the SRF shape of the hyperspectral instrument. This type of the convolution error has not been well recognized, and there is a lack of corresponding discussion in most published papers. Although it is small as compared with the instrument accuracy of existing hyperspectral sounders, the error is deemed to be significant when it is compared with the stringent calibration requirement imposed by future climate missions like the Climate Absolute Radiance and Refractivity Observatory. Second, some broadband channels are insufficiently covered by the hyperspectral data, causing spectral gaps that lead to convolution errors. Although several methods have been developed to fill the spectral gaps and hence compensate for the second type of convolution error, the correction accuracy may still need improvement especially when a large spectral gap needs to be filled. This paper presents a methodology to accurately quantify and compensate for both types of convolution errors. This methodology utilizes the available hyperspectral information to correct the scene‐dependent convolution errors due to either the limited spectral resolution or spectral gaps. We use simulations to characterize the intercalibration errors between the Moderate resolution Imaging Spectroradiometer (MODIS) and current operational infrared sounders. We demonstrate that convolution errors can be effectively removed to meet the highly accurate intersatellite calibration requirement proposed by the Climate Absolute Radiance and Refractivity Observatory. Our methodology is also validated using real satellite data for the intercalibration between Aqua MODIS and Aqua Atmospheric Infrared Sounders (AIRS). Our study demonstrates that the accurate characterization and correction for the convolution errors greatly reduces the scene‐dependent and spectrally dependent errors, being critical to the consistency check between Infrared Atmospheric Sounding Interferometer (IASI) and AIRS using the double‐difference method. The convolution correction also facilitates the evaluation for other intercalibration errors (e.g., the drift of MODIS SRFs). Our derived SRF shift values from MODIS‐AIRS (after convolution error corrections) and from MODIS‐IASI intercalibration are consistent with each other. We further extend the methodology to study the calibration of a broadband channel which is either completely or largely uncovered by a hyperspectral measurement. The large spectral gap filling methodology is validated by demo...

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Section: Application On Real Airs/modis Datasupporting

confidence: 57%

Section: 1029/2018jd028585mentioning

confidence: 59%

An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral Sensors

Liu

Xiong

et al. 2018

JGR Atmospheres

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“…The RSR correction factor is derived as a radiance ratio between S-VIIRS and A-MODIS theoretical values, derived from RSR integration using AIRS hyper-spectral data. Results from the work reported in [23] indicate that the RSR correction reduces the differences by approximately 0.10 K and 0.29 K for M15/B31 and M16/B32 respectively. For M14/B29, since there is not enough spectral coverage for both A-AIRS and S-Cross track Infrared Sounder (CrIS), there is no RSR factor derived for this band.…”

Section: Calibration Consistencymentioning

confidence: 90%

“…The remaining bias does point to the inadequacy of the calibration model of S-VIIRS. The impacts of spectral correction for the RSR differences using measured simultaneous hyper-spectral data from A-Atmospheric Infrared Sounder (AIRS) for M15/B31 and M16 B32 are described in [23]. The RSR correction factor is derived as a radiance ratio between S-VIIRS and A-MODIS theoretical values, derived from RSR integration using AIRS hyper-spectral data.…”

Section: Calibration Consistencymentioning

confidence: 99%

Evaluation of VIIRS and MODIS Thermal Emissive Band Calibration Stability Using Ground Target

et al. 2016

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Abstract:The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, a polar orbiting Earth remote sensing instrument built using a strong MODIS background, employs a similarly designed on-board calibrating source-a V-grooved blackbody for the Thermal Emissive Bands (TEB). The central wavelengths of most VIIRS TEBs are very close to those of MODIS with the exception of the 10.7 µm channel. To ensure the long term continuity of climate data records derived using VIIRS and MODIS TEB, it is necessary to assess any systematic differences between the two instruments, including scenes with temperatures significantly lower than blackbody operating temperatures at approximately 290 K. Previous work performed by the MODIS Characterization Support Team (MCST) at NASA/GSFC used the frequent observations of the Dome Concordia site located in Antarctica to evaluate the calibration stability and consistency of Terra and Aqua MODIS over the mission lifetime. The near-surface temperature measurements from an automatic weather station (AWS) provide a direct reference useful for tracking the stability and determining the relative bias between the two MODIS instruments. In this study, the same technique is applied to the VIIRS TEB and the results are compared with those from the matched MODIS TEB. The results of this study show a small negative bias when comparing the matching VIIRS and Aqua MODIS TEB, implying a higher brightness temperature for S-VIIRS at the cold end. Statistically no significant drift is observed for VIIRS TEB performance over the first 3.5 years of the mission.

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“…The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the same platform is a filter radiometer with 17 visible/near‐infrared and 5 infrared (IR) spectral bands between 0.412 and 12.01 μm, collecting imagery and radiometric data of the Earth and its atmosphere (Cao et al, ; De Luccia et al, ; Hillger et al, ). With its high radiometric accuracy and spatial resolution (750 m for moderate‐resolution bands [M bands] and 375 m for imaging resolution bands [I bands] at nadir), VIIRS continues the heritage measurements from the Advanced Very High Resolution Radiometer (AVHRR) on Polar Operational Environmental Satellites (POES), the Operational Linescan System (OLS) on Defense Meteorological Satellite Program (DMSP; Elvidge et al, ), and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites (Cao et al, ; Li et al, ; Liang & Ignatov, ; Madhavan et al, ). More than 20 Environmental Data Records (EDR), such as sea surface temperature (SST), cloud properties, and fires, are produced from the calibrated VIIRS SDR (Cao et al, ; Liu et al, ; Xiong et al, ).…”

Section: Introductionmentioning

confidence: 99%

Intercomparison Between VIIRS and CrIS by Taking Into Account the CrIS Subpixel Cloudiness and Viewing Geometry

Gong

et al. 2018

JGR Atmospheres

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The Cross‐track Infrared Sounder (CrIS) onboard the Suomi National Polar‐orbiting Partnership (SNPP) has high radiometric accuracy, which can be used to intercompare and understand the radiometric performance of the thermal emissive bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the same platform. Previous studies usually selected uniform scenes to avoid potential uncertainties due to geolocation errors. This study focuses on all scenes (including nonuniform scenes), as well as CrIS subpixel cloudiness, local zenith angle and surface type, and their impacts on VIIRS/CrIS intercomparisons. A geolocation error correction scheme is applied to mitigate the geolocation mismatch between CrIS and VIIRS. Intercomparison results of three days from 19 to 21 September 2016, a quarterly warm up/cool down calibration period, show overall good agreement in terms of radiance biases (less than 0.2 K in terms of brightness temperature) between VIIRS and CrIS, for scene temperatures between 220 and 300 K; however, larger biases are evident outside of this range. The three factors—CrIS subpixel cloudiness, local zenith angle, and surface type—show weak impacts on VIIRS radiance biases. Both clear‐sky and overcast conditions have slightly different radiance biases from other partially cloudy conditions because of more contributions from colder or warmer scenes. The time series show the impact of warm up/cool down and the effectiveness of the correction algorithm for reprocessing VIIRS M15 and M16 data sets. The methods and tools can be applied to monitor and validate other infrared imager/sounder duos onboard the same platform.

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Inter-Comparison of S-NPP VIIRS and Aqua MODIS Thermal Emissive Bands Using Hyperspectral Infrared Sounder Measurements as a Transfer Reference

Cited by 14 publications

References 20 publications

An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral Sensors

An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral Sensors

Evaluation of VIIRS and MODIS Thermal Emissive Band Calibration Stability Using Ground Target

Intercomparison Between VIIRS and CrIS by Taking Into Account the CrIS Subpixel Cloudiness and Viewing Geometry

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