A quasi-physical sea surface temperature method for the split-window data from the Second-generation Global Imager (SGLI) onboard the Global Change Observation Mission-Climate (GCOM-C) satellite
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Kurihara, Yukio
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Japan Aerosp Explorat Agcy JAXA, Earth Observat Res Ctr EORC, 2-1-1 Sengen, Tsukuba, Ibaraki 3058505, JapanJapan Aerosp Explorat Agcy JAXA, Earth Observat Res Ctr EORC, 2-1-1 Sengen, Tsukuba, Ibaraki 3058505, Japan
Kurihara, Yukio
[1
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Murakami, Hiroshi
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Japan Aerosp Explorat Agcy JAXA, Earth Observat Res Ctr EORC, 2-1-1 Sengen, Tsukuba, Ibaraki 3058505, JapanJapan Aerosp Explorat Agcy JAXA, Earth Observat Res Ctr EORC, 2-1-1 Sengen, Tsukuba, Ibaraki 3058505, Japan
Murakami, Hiroshi
[1
]
Ogata, Kazunori
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Japan Aerosp Explorat Agcy JAXA, Earth Observat Res Ctr EORC, 2-1-1 Sengen, Tsukuba, Ibaraki 3058505, JapanJapan Aerosp Explorat Agcy JAXA, Earth Observat Res Ctr EORC, 2-1-1 Sengen, Tsukuba, Ibaraki 3058505, Japan
Ogata, Kazunori
[1
]
Kachi, Misako
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Japan Aerosp Explorat Agcy JAXA, Earth Observat Res Ctr EORC, 2-1-1 Sengen, Tsukuba, Ibaraki 3058505, JapanJapan Aerosp Explorat Agcy JAXA, Earth Observat Res Ctr EORC, 2-1-1 Sengen, Tsukuba, Ibaraki 3058505, Japan
Kachi, Misako
[1
]
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[1] Japan Aerosp Explorat Agcy JAXA, Earth Observat Res Ctr EORC, 2-1-1 Sengen, Tsukuba, Ibaraki 3058505, Japan
This paper describes a quasi-physical method (the Q-method) for determining the sea surface temperatures (SSTs). The Q-method is a coefficient-based technique developed for processing the multiband infrared (IR) data of the geostationary Himawari-8 satellite. We applied the Q-method to the split-window data from the Second generation Global Imager (SGLI) onboard the Global Change Observation Mission-Climate (GCOM-C) satellite. A comparison of the determined SGLI SSTs and buoy data shows a bias with a robust standard deviation of-0.097 K and 0.28 K in the daytime and-0.18 K and 0.28 K at night, respectively. Meanwhile, high biases of nearly-0.5 K were calculated for SSTs at and around 305 K. A residuals analysis suggests that the high negative bias is caused by insufficient information on the atmospheric correction brought by split-window data. This paper discusses the physical and mathematical background of the Q-method and compares it with another coefficient based physical scheme.