Monitoring the VIIRS Sensor Data Records Reflective Solar Band Calibrations Using DCC With Collocated CrIS Measurements

Gong, Xinya; Li, Zhenglong; Li, Jun; Moeller, Christopher C.; Wang, Wenhui

doi:10.1029/2018JD030019

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Monitoring the VIIRS Sensor Data Records Reflective Solar Band Calibrations Using DCC With Collocated CrIS Measurements

2019
By Gong, Xinya ; Li, Zhenglong ; Li, Jun ; ...
Source: Journal of Geophysical Research: Atmospheres, 124(15), 8688-8706

[PDF-4.82 MB]

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Journal Title:

Journal of Geophysical Research: Atmospheres
Personal Author:

Gong, Xinya ; Li, Zhenglong ; Li, Jun ; Moeller, Christopher C. ; Wang, Wenhui

Gong, Xinya ; Li, Zhenglong ; Li, Jun ; Moeller, Christopher C. ; Wang, Wenhui Less -
NOAA Program & Office:

CIMSS (Cooperative Institute for Meteorological Satellite Studies) ; JPSS (Joint Polar Satellite System Program Office) ; NESDIS (National Environmental Satellite, Data, and Information Service)

CIMSS (Cooperative Institute for Meteorological Satellite Studies) ; JPSS (Joint Polar Satellite System Program Office) ; NESDIS (National Environmental Satellite, Data, and Information Service) Less -
Description:

As uniform and stable objects, deep convective clouds (DCCs) are often used to monitor the calibration stabilities of the reflective solar bands (RSBs) of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership. Traditionally, DCCs are identified by the legacy 11-μm brightness temperature (BT11) threshold method. With the collocated Cross-track Infrared Sounder (CrIS), a method of combining the BT difference between a water vapor absorption channel and a window channel to its measurement noise ratio (BNR) is adopted and applied to DCC identification. The BNR method improves the DCC detections over the legacy method because it is less contaminated with high clouds not thick and bright enough. Using observations from 2017 to 2018, the results show BNR has better performances than BT11 for identifying DCCs and monitoring RSBs. When comparing to BT11, BNR has more robust and invariant time series of monthly reflectance for all RSBs; that is, the standard deviation and total variation range (maximum-minimum) are up to 47% smaller. Because BNR affects more on the left tails (less reflective) than the modes of the histograms of reflectance, the improvement is more significant on the mean reflectance than the mode. BNR detects fewer DCCs than BT11, but with more confidence. This allows the weekly and daily time series for monitoring RSBs in higher temporal frequencies. This method can be applied to other imagers with collocated advanced infrared sounders for detecting DCCs and monitoring the calibration stabilities of RSBs.
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Infrared imaging
Source:

Journal of Geophysical Research: Atmospheres, 124(15), 8688-8706
DOI:

https://doi.org/10.1029/2018JD030019
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Journal Article
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Grant no. NA15NES4320001
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urn:sha256:1a8ed23241e151e05600e6c605e645a6bc4d53c3f87ce411b9c1dd757cac37fa
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https://repository.library.noaa.gov/view/noaa/26429/noaa_26429_DS1.pdf
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Monitoring the VIIRS Sensor Data Records Reflective Solar Band Calibrations Using DCC With Collocated CrIS Measurements

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