Journal of Tropical Oceanography ›› 2020, Vol. 39 ›› Issue (6): 57-65.doi: 10.11978/2019128CSTR: 32234.14.2019128

Special Issue: 海洋大数据及应用

• Marine Hydrology • Previous Articles     Next Articles

Study on the correction of SST prediction in South China Sea using remotely sensed SST

ZHANG Peijun1,2(), ZHOU Shuihua1,2, LIANG Changxia1,2   

  1. 1. South China Sea Marine Prediction Center, State Oceanic Administration, Guangzhou, Guangdong 510310, China
    2. Key Laboratory of Marine Environment Survey Technology and Application, Ministry of Natural Resource, Guangzhou, Guangdong 510330, China
  • Received:2019-12-09 Revised:2020-03-29 Online:2020-10-10 Published:2020-04-09
  • Contact: ZHANG Peijun E-mail:zpj@hyyb.org
  • Supported by:
    National Key Research and Development Program of China(2017YFC1404700);Special Project for Economic Development of Guangdong(GDME-2018B001)

Abstract:

A new error-correction forecast model for sea surface temperature (SST) is proposed in this paper, where the SST errors are derived from the Group for High Resolution Sea Surface Temperature (GHRSST) data and operational numerical prediction SST product. First of all, the reliability of the GHRSST data was validated with the upper temperature data of Argo floats in the South China Sea. The results showed that the Root Mean Square Error (RMSE) between the two sets of data was about 0.3℃ while the correlation coefficient was 0.98; the GHRSST data could be used for the correction of operational numerical forecast model on SST in the South China Sea. After being corrected, the RMSEs of 24-hr, 48-hr and 72-hr SST forecast results were dropped from 0.8 ℃ to 0.5 ℃ compared with the upper temperature data of Argo floats. Meanwhile, the 24-hr, 48-hr and 72-hr SST forecast errors between the GHRSST data and model results were significantly reduced after the correction in the northern South China Sea (110°E -121°E, 13°N -23°N). During the influence of the cold air or the mesoscale eddy in the South China Sea, the effect of SST forecast correction was also quite significant. Therefore, this method should be considered to apply in the operational numerical forecast system on SST in the South China Sea.

Key words: SST, Operational numerical prediction, Error correction, GHRSST, Argo, South China Sea

CLC Number: 

  • P731.31