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MODIS Detector Differences Using Deep Convective Clouds and Desert Targets

Authors :
Qiaozhen Mu
Amit Angal
Kevin Twedt
Aisheng Wu
Xiaoxiong Xiong
Source :
Proceedings Volume 11530, Sensors, Systems, and Next-Generation Satellites XXIV
Publication Year :
2020
Publisher :
United States: NASA Center for Aerospace Information (CASI), 2020.

Abstract

An accurate on-orbit characterization of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites is essential to satisfy the requirements from the scientific community for high-quality operational and research products. In this study, NASA’s C6.1 L1B data are utilized to assess the stability of the calibrated top of atmosphere reflectance retrieved from individual detectors within a spectral band over deep convective clouds (DCCs) and desert sites. The results from these invariant Earth targets show detector-to-detector (D2D) differences in the L1B reflectance products for select MODIS reflective solar bands. For Aqua MODIS, the D2D differences have no significant change over time for the bands studied. However, the D2D differences exhibit an increase in magnitude over time for Terra MODIS bands 1, 3-7, and 26, which can induce noticeable striping and higher uncertainties in the downstream data products. The D2D stability assessment results over DCCs are consistent with those observed over desert sites. In addition, the view-angle dependence of the D2D differences is investigated by separating the frames along scan into five zones. The D2D assessment is performed for each of the five zones, and the results will further benefit any improvements in the calibration of a detector-dependent response versus scan angle that can be considered for future MODIS Level 1B Collections.

Details

Language :
English
ISSN :
1996756X and 0277786X
Database :
NASA Technical Reports
Journal :
Proceedings Volume 11530, Sensors, Systems, and Next-Generation Satellites XXIV
Notes :
921266.04.12.01.69, , 80GSFC20C0044
Publication Type :
Report
Accession number :
edsnas.20220000186
Document Type :
Report
Full Text :
https://doi.org/10.1117/12.2571977