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Global Validation of Columnar Water Vapor Derived from EOS MODIS-MAIAC Algorithm Against the Ground-Based AERONET ObservationsThe water vapor is a relevant greenhouse gas in the Earth's climate system, and satellite products become one of the most effective way to characterize and monitor the columnar water vapor (CWV) content at global scale. Recently, a new product (MCD19) was released as part of MODIS (Moderate Resolution Imaging Spectroradiometer) Collection 6 (C6). This operational product from the Multi-Angle Implementation for Atmospheric Correction (MAIAC) algorithm includes a high 1-kilometer resolution CWV retrievals. This study presents the first global validation of MAIAC C6 CWV obtained from MODIS MCD19A2 product. This evaluation was performed using Aerosol Robotic Network (AERONET) observations at 265 sites (2000-2017). Overall, the results show a good agreement between MAIAC/AERONET CWV retrievals, with correlation coefficient higher than 0.95 and RMS (Root Mean Square) error lower than 0.250 centimeters. The binned error analysis revealed an underestimation (approximately 10 percent) of Aqua CWV retrievals with negative bias for CWV higher than 3.0 centimeters. In contrast, Terra CWV retrievals show a slope of regression close to unity and a low mean bias of 0.075 centimeters. While the accuracy is relatively similar between 1.0 and 5.0 centimeters for both sensor products, Terra dataset is more reliable for applications in humid tropical areas (less than 5.0 centimeters). The expected error was defined as plus or minus 15 percent, with less than 68 percent of retrievals falling within this envelope. However, the accuracy is regionally dependent, and lower error should be expected in some regions, such as South America and Oceania. Since MODIS instruments have exceeded their design lifetime, time series analysis was also presented for both sensor products. The temporal analysis revealed a systematic offset of global average between Terra and Aqua CWV records. We also found an upward trend (approximately 0.2 centimeters per decade) in Terra CWV retrievals, while Aqua CWV retrievals remain stable over time. The sensor degradation influences the ability to detect climate signals, and this study indicates the need for revisiting calibration of the MODIS bands 17-19, mainly for Terra instrument, to assure the quality of the MODIS water vapor product. Finally, this study presents a comprehensive validation analysis of MAIAC CWV over land, raising the understanding of its overall quality.
Document ID
20190025332
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Martins, Vitor S.
(Iowa State Univ. Ames, IA, United States)
Lyapustin, Alexei
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Wang, Yujie
(Maryland Univ. Baltimore County (UMBC) Baltimore, MD, United States)
Giles, David M.
(Science Systems and Applications, Inc. Lanham, MD, United States)
Smirnov, Alexander
(Science Systems and Applications, Inc. Lanham, MD, United States)
Slutsker, Ilya
(Science Systems and Applications, Inc. Lanham, MD, United States)
Korkin, Sergey
(Universities Space Research Association (USRA) Columbia, MD, United States)
Date Acquired
May 23, 2019
Publication Date
May 8, 2019
Publication Information
Publication: Atmospheric Research
Publisher: Elsevier
Volume: 225
ISSN: 0169-8095
Subject Category
Meteorology And Climatology
Report/Patent Number
GSFC-E-DAA-TN68951
Report Number: GSFC-E-DAA-TN68951
ISSN: 0169-8095
Funding Number(s)
CONTRACT_GRANT: NNG11HP16A
CONTRACT_GRANT: NNX15AT34A
CONTRACT_GRANT: NNG15HQ01C
Distribution Limits
Public
Copyright
Other
Technical Review
Single Expert
Keywords
MAIAC
Satellite Remote Sensing
MODIS
Algorithms

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