Application of satellite altimeter data in three-dimension sea temperature and salinity numerical prediction

LI Yun; WAN Li-ying; LIU Qin-zheng

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LI Yun, WAN Li-ying, LIU Qin-zheng. Application of satellite altimeter data in three-dimension sea temperature and salinity numerical prediction[J]. Haiyang Xuebao, 2011, 33(6): 64-72.

Citation:

LI Yun, WAN Li-ying, LIU Qin-zheng. Application of satellite altimeter data in three-dimension sea temperature and salinity numerical prediction[J]. Haiyang Xuebao, 2011, 33(6): 64-72.

LI Yun, WAN Li-ying, LIU Qin-zheng. Application of satellite altimeter data in three-dimension sea temperature and salinity numerical prediction[J]. Haiyang Xuebao, 2011, 33(6): 64-72.

Citation:

LI Yun, WAN Li-ying, LIU Qin-zheng. Application of satellite altimeter data in three-dimension sea temperature and salinity numerical prediction[J]. Haiyang Xuebao, 2011, 33(6): 64-72.

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Application of satellite altimeter data in three-dimension sea temperature and salinity numerical prediction

1.
Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing 100081, China;Institude of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
2.
Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing 100081, China

Received Date: 2010-01-11
Rev Recd Date: 2011-05-21

Abstract

Abstract

With the development of remote sensing technology, satellite observation data have been used to study the numerical model assimilation technology. The 3-D northwest Pacific sea temperature, salinity and current forecast system developed by the National Marine Environment Forecasting Center is applied here to assimilating the sea surface height abnormal (SSHA) of the Collecte Localisation Satellites altimeter data with OVALS(ocean variational analysis system) which is based on 3-D-VAR scheme. The sea temperature and salinity profile data transformed from altimeter data are assimilated in the horizontal layer to find out the effect of the altimeter data on the numerical prediction. The results show that the forecasting accuracy by adding altimeter data assimilation is better than without assimilation, which verifies that the altimeter data assimilation for the improvement of the short-term numerical prediction is valid.
- altimeter data,
- assimilation,
- ocean variational analysis system,
- numerical prediction

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References(17)

References

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