The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data

Wang Wei; Wu Danzhu; Qu Pin; Li Yi; Liu Lili; Wu Bingui

doi:doi:10.11648/j.wros.20160504.12

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The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data

Wang Wei, Wu Danzhu, Qu Pin, Li Yi, Liu Lili, Wu Bingui

Published in Journal of Water Resources and Ocean Science (Volume 5, Issue 4)

Received: 12 July 2016 Accepted: 22 July 2016 Published: 6 August 2016

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Abstract

The numerical weather prediction (NWP) model about marine meteorological disasters requires sea surface temperature (SST) data which represents the parameters of marine dynamic process. However, the SST data of high spatial-temporal resolution are scarce in Huang Bohai sea in China. In order to acquire the high resolution SST data, the authors try to retrieve the high resolution SST data in Huang Bohai sea with FY2G-based satellite data. Moreover, the data differences of the satellite retrieval data with both buoys observation SST and NCEP optimal interpolation SST are compared, respectively, in terms of the statistical analysis method. Meanwhile the statistical equations are determined about the satellite retrieval SST with observed SST and of optimal interpolation SST. The equations are referred as a standard of data quality control equations when the differences of the revised values of the statistical equations and satellite inversion are calculated. While the data fusion is done, authors retain the data that the differences of the satellite retrieval SST and the statistical equation are less than 3.0°C. Above method could make that the satellite SST space characteristic information is merged into weekly average optimal interpolation SST data, and it improves SST spatial-temporal resolution in Huang Bohai sea. The work lays a foundation for numerical models using the high resolution SST in Huang Bohai area.

Published in	Journal of Water Resources and Ocean Science (Volume 5, Issue 4)
DOI	10.11648/j.wros.20160504.12
Page(s)	53-63
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

FY Geostationary Satellite, SST, Inversion Data, Data Fusion

References

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[4]	Knievel, J. C., Rife, D. L., Grim, J. A., et al. A Simple Technique for Creating Regional Composites of Sea Surface Temperature from MODIS for Use in Operational Mesoscale NWP [J]. JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY, 2010, 49: 2267-2284.
[5]	MaulG, A.. Application of GOES visible-infraed data to quantifying mesoscale ocean surface temperature [J]. Geophys. Res., 1981, 86: 8007-8021.
[6]	Riehl, H. A model for hurricane formation [J]. Journal of Applied physics, 1950, 21: 917-925.
[7]	Su J., Li L., Bao, X. W., et al. Numerical Experiment of SST Response to Typhoon Process in Yellow Sea and Bohai Sea [J]. JOURNAL OF OCEAN UNIVERSITY OF QINGDAO, 2001, 31 (2): 165-172.
[8]	Tuleya, R. E., Kurihara, Y. A note on the sea surface temperature sensitivity of a numerical model of tropical storm genesis [J]. Mon Weather Rev, 1982, 110: 2063-2069.
[9]	Wang, J. H., Shao, C. X., Miao, C. S., et al. Near-shore SST’s impact on typhoon return to the sea in numerical simulation [J]. JOURNAL OF TROPICAL OCEANOGRAPHY, 2012, 31 (5): 106-115.
[10]	Wang, L., Zhang, R. H., Zhang, H. L. Analyses of Spatial-Temporal Characteristics For Various Seasonal Sea Surface Temperature Versus Summer Rainfall In China [J]. JOURNAL OF TROPICAL METEOROLOGY, 2007, 23 (6): 587-594.
[11]	Wentz, F. J., Gentemann, C. D., Smith, D., et al. Satellite Measurements of Sea Surface Temperature Through Clouds [J]. Science, 2000, 288: 847-850.
[12]	Yu, B., BoerG, J., Zwiers, F. W. Surface heat flux feedback and SST variability [J]. Trans. Atmos. Sci., 2011, 34 (1): 1-7.
[13]	Yu, J. J., He, J. H., Shen, X. Y.. A Dynamical Study about the Impacts of SST and SSTA on Low Frequency Oscillation in Tropical Atmosphere [J]. Journal of Nanjing Institute of Meteorology, 2006, 29 (5): 688-693.

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APA Style

Wang Wei, Wu Danzhu, Qu Pin, Li Yi, Liu Lili, et al. (2016). The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data. Journal of Water Resources and Ocean Science, 5(4), 53-63. https://doi.org/10.11648/j.wros.20160504.12

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ACS Style

Wang Wei; Wu Danzhu; Qu Pin; Li Yi; Liu Lili, et al. The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data. J. Water Resour. Ocean Sci. 2016, 5(4), 53-63. doi: 10.11648/j.wros.20160504.12

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AMA Style

Wang Wei, Wu Danzhu, Qu Pin, Li Yi, Liu Lili, et al. The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data. J Water Resour Ocean Sci. 2016;5(4):53-63. doi: 10.11648/j.wros.20160504.12

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@article{10.11648/j.wros.20160504.12,
  author = {Wang Wei and Wu Danzhu and Qu Pin and Li Yi and Liu Lili and Wu Bingui},
  title = {The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {5},
  number = {4},
  pages = {53-63},
  doi = {10.11648/j.wros.20160504.12},
  url = {https://doi.org/10.11648/j.wros.20160504.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20160504.12},
  abstract = {The numerical weather prediction (NWP) model about marine meteorological disasters requires sea surface temperature (SST) data which represents the parameters of marine dynamic process. However, the SST data of high spatial-temporal resolution are scarce in Huang Bohai sea in China. In order to acquire the high resolution SST data, the authors try to retrieve the high resolution SST data in Huang Bohai sea with FY2G-based satellite data. Moreover, the data differences of the satellite retrieval data with both buoys observation SST and NCEP optimal interpolation SST are compared, respectively, in terms of the statistical analysis method. Meanwhile the statistical equations are determined about the satellite retrieval SST with observed SST and of optimal interpolation SST. The equations are referred as a standard of data quality control equations when the differences of the revised values of the statistical equations and satellite inversion are calculated. While the data fusion is done, authors retain the data that the differences of the satellite retrieval SST and the statistical equation are less than 3.0°C. Above method could make that the satellite SST space characteristic information is merged into weekly average optimal interpolation SST data, and it improves SST spatial-temporal resolution in Huang Bohai sea. The work lays a foundation for numerical models using the high resolution SST in Huang Bohai area.},
 year = {2016}
}

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TY  - JOUR
T1  - The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data
AU  - Wang Wei
AU  - Wu Danzhu
AU  - Qu Pin
AU  - Li Yi
AU  - Liu Lili
AU  - Wu Bingui
Y1  - 2016/08/06
PY  - 2016
N1  - https://doi.org/10.11648/j.wros.20160504.12
DO  - 10.11648/j.wros.20160504.12
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 53
EP  - 63
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20160504.12
AB  - The numerical weather prediction (NWP) model about marine meteorological disasters requires sea surface temperature (SST) data which represents the parameters of marine dynamic process. However, the SST data of high spatial-temporal resolution are scarce in Huang Bohai sea in China. In order to acquire the high resolution SST data, the authors try to retrieve the high resolution SST data in Huang Bohai sea with FY2G-based satellite data. Moreover, the data differences of the satellite retrieval data with both buoys observation SST and NCEP optimal interpolation SST are compared, respectively, in terms of the statistical analysis method. Meanwhile the statistical equations are determined about the satellite retrieval SST with observed SST and of optimal interpolation SST. The equations are referred as a standard of data quality control equations when the differences of the revised values of the statistical equations and satellite inversion are calculated. While the data fusion is done, authors retain the data that the differences of the satellite retrieval SST and the statistical equation are less than 3.0°C. Above method could make that the satellite SST space characteristic information is merged into weekly average optimal interpolation SST data, and it improves SST spatial-temporal resolution in Huang Bohai sea. The work lays a foundation for numerical models using the high resolution SST in Huang Bohai area.
VL  - 5
IS  - 4
ER  -

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Author Information

Wang Wei

Tianjin Institute of Meteorological Science, Tianjin, China
Wu Danzhu

Tianjin Institute of Meteorological Science, Tianjin, China
Qu Pin

Tianjin Institute of Meteorological Science, Tianjin, China
Li Yi

Tianjin Institute of Meteorological Science, Tianjin, China
Liu Lili

Tianjin Institute of Meteorological Science, Tianjin, China
Wu Bingui

Tianjin Institute of Meteorological Science, Tianjin, China

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Plain Text BibTeX RIS

APA Style

Wang Wei, Wu Danzhu, Qu Pin, Li Yi, Liu Lili, et al. (2016). The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data. Journal of Water Resources and Ocean Science, 5(4), 53-63. https://doi.org/10.11648/j.wros.20160504.12

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ACS Style

Wang Wei; Wu Danzhu; Qu Pin; Li Yi; Liu Lili, et al. The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data. J. Water Resour. Ocean Sci. 2016, 5(4), 53-63. doi: 10.11648/j.wros.20160504.12

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AMA Style

Wang Wei, Wu Danzhu, Qu Pin, Li Yi, Liu Lili, et al. The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data. J Water Resour Ocean Sci. 2016;5(4):53-63. doi: 10.11648/j.wros.20160504.12

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@article{10.11648/j.wros.20160504.12,
  author = {Wang Wei and Wu Danzhu and Qu Pin and Li Yi and Liu Lili and Wu Bingui},
  title = {The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {5},
  number = {4},
  pages = {53-63},
  doi = {10.11648/j.wros.20160504.12},
  url = {https://doi.org/10.11648/j.wros.20160504.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20160504.12},
  abstract = {The numerical weather prediction (NWP) model about marine meteorological disasters requires sea surface temperature (SST) data which represents the parameters of marine dynamic process. However, the SST data of high spatial-temporal resolution are scarce in Huang Bohai sea in China. In order to acquire the high resolution SST data, the authors try to retrieve the high resolution SST data in Huang Bohai sea with FY2G-based satellite data. Moreover, the data differences of the satellite retrieval data with both buoys observation SST and NCEP optimal interpolation SST are compared, respectively, in terms of the statistical analysis method. Meanwhile the statistical equations are determined about the satellite retrieval SST with observed SST and of optimal interpolation SST. The equations are referred as a standard of data quality control equations when the differences of the revised values of the statistical equations and satellite inversion are calculated. While the data fusion is done, authors retain the data that the differences of the satellite retrieval SST and the statistical equation are less than 3.0°C. Above method could make that the satellite SST space characteristic information is merged into weekly average optimal interpolation SST data, and it improves SST spatial-temporal resolution in Huang Bohai sea. The work lays a foundation for numerical models using the high resolution SST in Huang Bohai area.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - The Retrieve and Data Fusion of the Sea Surface Temperature with FengYun Geostationary Satellite Data
AU  - Wang Wei
AU  - Wu Danzhu
AU  - Qu Pin
AU  - Li Yi
AU  - Liu Lili
AU  - Wu Bingui
Y1  - 2016/08/06
PY  - 2016
N1  - https://doi.org/10.11648/j.wros.20160504.12
DO  - 10.11648/j.wros.20160504.12
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 53
EP  - 63
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20160504.12
AB  - The numerical weather prediction (NWP) model about marine meteorological disasters requires sea surface temperature (SST) data which represents the parameters of marine dynamic process. However, the SST data of high spatial-temporal resolution are scarce in Huang Bohai sea in China. In order to acquire the high resolution SST data, the authors try to retrieve the high resolution SST data in Huang Bohai sea with FY2G-based satellite data. Moreover, the data differences of the satellite retrieval data with both buoys observation SST and NCEP optimal interpolation SST are compared, respectively, in terms of the statistical analysis method. Meanwhile the statistical equations are determined about the satellite retrieval SST with observed SST and of optimal interpolation SST. The equations are referred as a standard of data quality control equations when the differences of the revised values of the statistical equations and satellite inversion are calculated. While the data fusion is done, authors retain the data that the differences of the satellite retrieval SST and the statistical equation are less than 3.0°C. Above method could make that the satellite SST space characteristic information is merged into weekly average optimal interpolation SST data, and it improves SST spatial-temporal resolution in Huang Bohai sea. The work lays a foundation for numerical models using the high resolution SST in Huang Bohai area.
VL  - 5
IS  - 4
ER  -

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