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A Fundamental Climate Data Record Derived from AMSR-E, MWRI, and AMSR2
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2020
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Source: IEEE Transactions on Geoscience and Remote Sensing, 58(8), 5450-5461
[PDF-6.84 MB]
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Journal Title:IEEE Transactions on Geoscience and Remote Sensing
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Description:Fundamental climate data records (FCDRs) play a vital role in monitoring climate change. In this article, we develop a spaceborne passive microwave-based FCDR by recalibrating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) on the Aqua satellite, the microwave radiometer imager (MWRI) onboard the Feng-Yun-3B (FY3B) satellite, and the Advanced Microwave Scanning Radiometer-2 (AMSR2) onboard the JAXA’s Global Change Observation Mission first-Water (GCOM-W1) satellite. Before recalibration, it is found that AMSR-E and AMSR2 observations are stable over time, but MWRI drifted colder before May 2015 and had nonnegligible errors in geolocation for most channels. In addition, intersensor differences of brightness temperatures (TBs) are as large as 5–10 K. To improve data consistency and continuity, several intersensor calibration methods are applied by using AMSR2 as a reference while using MWRI to bridge the data gap between AMSR2 and AMSR-E. The double difference method is used to provide intersensor difference time series for correcting calibration biases, such as scene temperature-dependent bias, solar-heating-induced bias, and systematic constant bias. Hardware differences between sensors are corrected using principal component analysis. After recalibration, the mean biases of both MWRI and AMSR-E are less than 0.3 K compared to the AMSR2 reference and their standard deviations are less than 1 K for all channels. Under oceanic rain-free conditions, the TB biases are less than 0.2 K for all channels and no significant relative bias drifts were found between sensors for overlapping observations. These statistics suggest that the consistency between these instruments was significantly improved and the derived FCDR could be useful to obtain long-term water cycle-related variables for climate research.
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Source:IEEE Transactions on Geoscience and Remote Sensing, 58(8), 5450-5461
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ISSN:0196-2892;1558-0644;
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Rights Information:Accepted Manuscript
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