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The Experiment of the SST Data Fusion with FengYun Geostationary Satellite Data in China
It plays a crucial role in the model of numerical weather prediction in North China that the sea surface temperature (SST) of the high resolution was merged with FengYun Geostationary Satellite Data.
By Wei Wang,Danzhu Wu,Pin Qu, Engineer and Yi Lin
Sep. 2, 2016

It plays a crucial role in the model of numerical weather prediction in North China that the sea surface temperature (SST) of the high resolution was merged with FengYun Geostationary Satellite Data.

In a recent paper by author Dr. Wang, the merged SST with FengYun Geostationary Satellite data solved a problem that the high resolution SST was very scarce in Huang-Bohai sea in North China.

“The sea surface temperature is an important factor of affecting weather and climate system, But there was lack of the high resolution SST in Huang-Bohai sea in the CIMISS database of China meteorological administration, so that the present SST data are unable to meet the needs of marine forecast operation”. Dr. Wei Wang said.

In the paper, Dr. Wei Wang tried to retrieve the high resolution SST data in Huang-Bohai Sea with FY2G-based satellite data in order to acquire the high resolution SST data. The authors compared the retrieve SST with remote sensing data with buoy data and grid data, and then they found that the fitting equation of buoy data and grid data was a good method as quality control standard. After the quality control, the large error of the retrieve SST was avoided in merged data, and the retrieve SST and grid SST was merged, which the merged SST could improve the low precision problem of the retrieval SST with satellite data under the situation of the lower SST. The method also made that the satellite SST space characteristic information was merged into weekly average optimal interpolation SST data and it improved SST spatial-temporal resolution in Huang Bohaisea.

Dr. Wei Wang also suggested that” Although the work laid a foundation of the detailed SST in Huang-Bohai sea for the numerical weather prediction mode, it is necessary to further improve satellite retrieval SST algorithm and fusion algorithm in order to promote the precision of daily fusion SST and the semidiurnal fusion SST”.

SST is an important factor in the air-sea energy exchange. Some research results show that the energy exchange and marine advection on the air-sea interface together control the formation, maintain and attenuation of sea surface temperature anomalies. Another results show that SST changes have influence on the typhoon path. Moreover, some typhoons moving path is the more sensitive to the change of SST. Under the influence of SST anomaly, synoptic-scale oscillation frequency significantly change and prone to unstable oscillation. The oscillation is stability when SST value is low. With the SST value increasing, the oscillation frequency becomes the lower and wave velocity also is the slower. So detailed SST information is necessary for marine weather forecast.

Author:

Wei Wang, Techincal Director, Tianjin Institute of Meteorological Science, Tianjin, China.

Danzhu Wu, Senior Engineer, Tianjin Institute of Meteorological Science, Tianjin, China.

Pin Qu, Engineer, Tianjin Institute of Meteorological Science, Tianjin, China.

Yi Lin, Senior Engineer, Tianjin Institute of Meteorological Science, Tianjin, China.

A paper about the study appeared recently in Journal of Water Resources and Ocean Science.

Paper link:
http://article.sciencepublishinggroup.com/html/10.11648.j.wros.20160504.12.html

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