基于卫星遥感海温数据的南海SST预报误差订正

doi:10.11978/2019128

热带海洋学报 ›› 2020, Vol. 39 ›› Issue (6): 57-65.doi: 10.11978/2019128CSTR: 32234.14.2019128

所属专题：海洋大数据及应用

基于卫星遥感海温数据的南海SST预报误差订正

张培军^1,²(), 周水华^1,², 梁昌霞^1,²

1.国家海洋局南海预报中心, 广东广州 510310
2.自然资源部海洋环境探测技术与应用重点实验室, 广东广州 510330

收稿日期:2019-12-09 修回日期:2020-03-29 出版日期:2020-10-10 发布日期:2020-04-09
通讯作者: 张培军
作者简介:张培军(1984—), 女, 河南省郑州市人, 工程师, 博士, 主要从事海洋环境数值预报和模式检验等方面的研究。email: zpj@hyyb.org.
基金资助:
国家重点研发计划重点专项(2017YFC1404700);广东省促进经济发展专项资金(海洋经济发展用途)项目(GDME-2018B001)

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

ZHANG Peijun^1,²(), ZHOU Shuihua^1,², LIANG Changxia^1,²

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
Supported by:
National Key Research and Development Program of China(2017YFC1404700);Special Project for Economic Development of Guangdong(GDME-2018B001)

摘要/Abstract

摘要：

尝试利用卫星遥感高分辨率海表温度资料GHRSST (Group for High Resolution Sea Surface Temperature) 与海表温度(sea surface temperature, SST)数值预报产品之间的误差, 建立一种南海SST模式预报订正方法。首先, 利用南海的Argo浮标上层海温数据对GHRSST 海温数据进行验证, 结果表明两者之间均方根误差约为0.3℃, 相关系数为0.98, GHRSST 海温数据可用于南海业务化数值预报SST的订正。预报订正后的SST与Argo浮标海温数据相比, 24h、48h和72h的均方根误差均由0.8℃左右下降到0.5℃以内。与GHRSST 海温数据相比, 南海北部海域(110°E—121°E, 13°N—23°N)订正后的24h、48h和72h的SST预报空间误差均显著减小, 在冷空气影响南海期间或中尺度涡存在的过程中, SST预报订正效果也较为显著。因此, 该方法可考虑在南海业务化SST数值预报系统中应用。

关键词: SST, 数值预报, 误差订正, GHRSST, Argo浮标, 南海

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

中图分类号:

P731.31

张培军, 周水华, 梁昌霞. 基于卫星遥感海温数据的南海SST预报误差订正[J]. 热带海洋学报, 2020, 39(6): 57-65.

ZHANG Peijun, ZHOU Shuihua, LIANG Changxia. Study on the correction of SST prediction in South China Sea using remotely sensed SST[J]. Journal of Tropical Oceanography, 2020, 39(6): 57-65.

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序号	浮标编号	时间分布
1	2901479	2016-05-03—2019-02-05
2	2901480	2016-04-27—2018-09-08
3	2901481	2016-04-28—2019-02-20
4	2902045	2015-09-10—2017-07-05
5	2902056	2016-04-27—2016-10-22
6	2902692	2016-09-12—2017-09-18
7	2902694	2016-09-10—2017-09-21
8	2902744	2017-11-22—2019-01-16
9	2902745	2017-11-22—2019-02-15
10	5904539	2015-11-08—2016-05-30
11	5904747	2016-05-03—2018-01-13

	均方根误差		相关系数
	订正前	订正后	订正前	订正后
24h	0.85	0.36	0.94	0.98
48h	0.84	0.42	0.94	0.98
72h	0.86	0.46	0.94	0.97

基于卫星遥感海温数据的南海SST预报误差订正

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

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