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An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral SensorsThe 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). 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.
Document ID
20190000665
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Wu, Wan
(Science Systems and Applications, Inc. Hampton, VA, United States)
Liu, Xu
(NASA Langley Research Center Hampton, VA, United States)
Xiong, Xiaoxiong
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Li, Yonghong
(Science Systems and Applications, Inc. Lanham, MD, United States)
Yang, Qiguang
(Science Systems and Applications, Inc. Hampton, VA, United States)
Wu, Aisheng
(Science Systems and Applications, Inc. Lanham, MD, United States)
Kizer, Susan
(Science Systems and Applications, Inc. Hampton, VA, United States)
Cao, Changyong
(National Oceanic and Atmospheric Administration College Park, MD, United States)
Date Acquired
February 12, 2019
Publication Date
August 27, 2018
Publication Information
Publication: Journal of Geophysical Research: Atmospheres (JGR)
Publisher: American Geophysical Union (AGU)
Volume: 123
Issue: 17
ISSN: 2169-897X
e-ISSN: 2169-8996
Subject Category
Meteorology And Climatology
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN64776
ISSN: 2169-897X
E-ISSN: 2169-8996
Report Number: GSFC-E-DAA-TN64776
Funding Number(s)
CONTRACT_GRANT: NNL16AA05C
CONTRACT_GRANT: NNG15HQ01C
Distribution Limits
Public
Copyright
Other
Keywords
Correction Method
Intersatellite Calibration Errors
Satellite-Observed Data
Spectral Gapping
Fïnite Spectral Resolution
Simulated Satellite-Observed Data

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