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

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 proce...

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Published in:Journal of geophysical research. Atmospheres 2018-09, Vol.123 (17), p.9238-9255
Main Authors: Wu, Wan, Liu, Xu, Xiong, Xiaoxiong, Li, Yonghong, Yang, Qiguang, Wu, Aisheng, Kizer, Susan, Cao, Changyong
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Liu, Xu
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Li, Yonghong
Yang, Qiguang
Wu, Aisheng
Kizer, Susan
Cao, Changyong
description 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 signicant when it is compared with the stringent calibration requirement imposed by future climate missions like the Climate Absolute Radiance and Refractivity Observatory (CLARREO). 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 lled. 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 Inter
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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 signicant when it is compared with the stringent calibration requirement imposed by future climate missions like the Climate Absolute Radiance and Refractivity Observatory (CLARREO). 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 lled. 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 bya hyperspectral measurement.The large spectral gap-filling methodology is validated by demonstrating the accurate prediction of the MODIS radiance of band 29 using the Cross-track Infrared Sounder spectra, with the real IASI spectral data being used as the reference.</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1029/2018JD028585</identifier><language>eng</language><publisher>Goddard Space Flight Center: American Geophysical Union (AGU)</publisher><subject>Accuracy ; AIRS ; Atmospheric sounding ; Broadband ; Calibration ; Channels ; Climate ; Convolution ; Corrections ; CrIS ; Data ; Earth ; Earth Resources And Remote Sensing ; Error correction ; Errors ; Evaluation ; Future climates ; Geophysics ; hyperspectral ; IASI ; Imaging techniques ; Infrared interferometers ; Infrared spectra ; Infrared tracking ; Instrument accuracy ; Intercalibration ; Meteorology And Climatology ; Methodology ; Missions ; MODIS ; Observatories ; Radiance ; Refractive index ; Refractivity ; Resolution ; Response functions ; Satellite data ; Satellite observation ; Satellites ; Spectral resolution ; Spectral sensitivity ; Spectroradiometers</subject><ispartof>Journal of geophysical research. Atmospheres, 2018-09, Vol.123 (17), p.9238-9255</ispartof><rights>2018. The Authors.</rights><rights>2018. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3667-a1e4ef94c1c21c594962f8a5d068da14f4b6195d4796448154a962bccd588bd23</citedby><cites>FETCH-LOGICAL-c3667-a1e4ef94c1c21c594962f8a5d068da14f4b6195d4796448154a962bccd588bd23</cites><orcidid>0000-0002-0473-3143 ; 0000-0003-3572-6525</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Wu, Wan</creatorcontrib><creatorcontrib>Liu, Xu</creatorcontrib><creatorcontrib>Xiong, Xiaoxiong</creatorcontrib><creatorcontrib>Li, Yonghong</creatorcontrib><creatorcontrib>Yang, Qiguang</creatorcontrib><creatorcontrib>Wu, Aisheng</creatorcontrib><creatorcontrib>Kizer, Susan</creatorcontrib><creatorcontrib>Cao, Changyong</creatorcontrib><title>An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral Sensors</title><title>Journal of geophysical research. Atmospheres</title><description>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 signicant when it is compared with the stringent calibration requirement imposed by future climate missions like the Climate Absolute Radiance and Refractivity Observatory (CLARREO). 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 lled. 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). 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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 lled. 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 bya hyperspectral measurement.The large spectral gap-filling methodology is validated by demonstrating the accurate prediction of the MODIS radiance of band 29 using the Cross-track Infrared Sounder spectra, with the real IASI spectral data being used as the reference.</abstract><cop>Goddard Space Flight Center</cop><pub>American Geophysical Union (AGU)</pub><doi>10.1029/2018JD028585</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0002-0473-3143</orcidid><orcidid>https://orcid.org/0000-0003-3572-6525</orcidid><oa>free_for_read</oa></addata></record>
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subjects Accuracy
AIRS
Atmospheric sounding
Broadband
Calibration
Channels
Climate
Convolution
Corrections
CrIS
Data
Earth
Earth Resources And Remote Sensing
Error correction
Errors
Evaluation
Future climates
Geophysics
hyperspectral
IASI
Imaging techniques
Infrared interferometers
Infrared spectra
Infrared tracking
Instrument accuracy
Intercalibration
Meteorology And Climatology
Methodology
Missions
MODIS
Observatories
Radiance
Refractive index
Refractivity
Resolution
Response functions
Satellite data
Satellite observation
Satellites
Spectral resolution
Spectral sensitivity
Spectroradiometers
title An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral Sensors
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