Articles | Volume 13, issue 5
https://doi.org/10.5194/essd-13-2111-2021
https://doi.org/10.5194/essd-13-2111-2021
Data description paper
 | 
18 May 2021
Data description paper |  | 18 May 2021

A new global gridded sea surface temperature data product based on multisource data

Mengmeng Cao, Kebiao Mao, Yibo Yan, Jiancheng Shi, Han Wang, Tongren Xu, Shu Fang, and Zijin Yuan

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Cited articles

Ackerman, S. A., Holz, R. E., Frey, R., Eloranta, E. W., Maddux, B. C., and McGill, M.: Cloud detection with MODIS. Part ii: validation, J. Atmos. Ocean. Tech., 25, 1073–1086, https://doi.org/10.1175/2007JTECHA1053.1, 2008. 
Alerskans, E., Høyer, J. L., Gentemann, C. L., Pedersen, L. T., Nielsen-Englyst, P., and Donlon, C.: Construction of a climate data record of sea surface temperature from passive microwave measurements, Remote Sens. Environ., 236, 11485, https://doi.org/10.1016/j.rse.2019.111485, 2020. 
Banzon, V., Smith, T. M., Steele, M., Huang, B., and Zhang, H.-M.: Improved estimation of proxy sea surface temperature in the Arctic, J. Atmos. Ocean. Tech., 37, 341–349, https://doi.org/10.1175/jtech-d-19-0177.1, 2020. 
Banzon, V. F. and Reynolds, R. W.: Use of windsat to extend a microwave-based daily optimum interpolation sea surface temperature time series, J. Climate, 26, 2557–2562, https://doi.org/10.1175/jcli-d-12-00628.1, 2013. 
Barton, I. and Pearce, A.: Validation of GLI and other satellite-derived sea surface temperatures using data from the Rottnest Island ferry, Western Australia, J. Oceanogr., 62, 303–310, https://doi.org/10.1007/s10872-006-0055-5, 2006. 
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We constructed a temperature depth and observation time correction model to eliminate the sampling depth and temporal differences among different data. Then, we proposed a reconstructed spatial model that filters and removes missing pixels and low-quality pixels contaminated by clouds from raw SST images and retrieves real sea surface temperatures under cloud coverage based on multisource data to generate a high-quality unified global SST product with long-term spatiotemporal continuity.
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