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Open AccessArticle

Data Assimilation of the High-Resolution Sea Surface Temperature Obtained from the Aqua-Terra Satellites (MODIS-SST) Using an Ensemble Kalman Filter

1
Japan Agency for Marine-Earth Science and Technology, Yokohama, Kanagawa 236-0001, Japan
2
Japan Aerospace Exploration Agency, Tsukuba, Ibaragi 305-8505, Japan
3
Ehime University, Matsuyama, Ehime 790-8577, Japan
4
The University of Tokyo, Kashiwa, Chiba 277-8561, Japan
*
Author to whom correspondence should be addressed.
Remote Sens. 2013, 5(6), 3123-3139; https://doi.org/10.3390/rs5063123
Received: 20 May 2013 / Revised: 13 June 2013 / Accepted: 18 June 2013 / Published: 21 June 2013
(This article belongs to the Special Issue Observing the Ocean’s Interior from Satellite Remote Sensing)
We develop an assimilation method of high horizontal resolution sea surface temperature data, provided from the Moderate Resolution Imaging Spectroradiometer (MODIS-SST) sensors boarded on the Aqua and Terra satellites operated by National Aeronautics and Space Administration (NASA), focusing on the reproducibility of the Kuroshio front variations south of Japan in February 2010. Major concerns associated with the development are (1) negative temperature bias due to the cloud effects, and (2) the representation of error covariance for detection of highly variable phenomena. We treat them by utilizing an advanced data assimilation method allowing use of spatiotemporally varying error covariance: the Local Ensemble Transformation Kalman Filter (LETKF). It is found that the quality control, by comparing the model forecast variable with the MODIS-SST data, is useful to remove the negative temperature bias and results in the mean negative bias within −0.4 °C. The additional assimilation of MODIS-SST enhances spatial variability of analysis SST over 50 km to 25 km scales. The ensemble spread variance is effectively utilized for excluding the erroneous temperature data from the assimilation process. View Full-Text
Keywords: Moderate Resolution Imaging Spectroradiometer (MODIS) sensors; ocean circulation model; vertical projection; Ensemble Kalman Filter; dynamic quality control Moderate Resolution Imaging Spectroradiometer (MODIS) sensors; ocean circulation model; vertical projection; Ensemble Kalman Filter; dynamic quality control
MDPI and ACS Style

Miyazawa, Y.; Murakami, H.; Miyama, T.; Varlamov, S.M.; Guo, X.; Waseda, T.; Sil, S. Data Assimilation of the High-Resolution Sea Surface Temperature Obtained from the Aqua-Terra Satellites (MODIS-SST) Using an Ensemble Kalman Filter. Remote Sens. 2013, 5, 3123-3139.

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