| YANG Guang,HE Hailun,WANG Yuan,HAN Xiqiu,WANG Yejian.Evaluating a satellite-based sea surface temperature by shipboard survey in the Northwest Indian Ocean[J].Acta Oceanologica Sinica,2016,35(11):52-58 |
| 利用西北印度洋船测数据评估基于卫星的海表面温度 |
| Evaluating a satellite-based sea surface temperature by shipboard survey in the Northwest Indian Ocean |
| 投稿时间：2015-10-26 修订日期：2016-01-27 |
| DOI：10.1007/s13131-016-0847-4 |
| 中文关键词: 船载观测 海表面温度 西北印度洋 热带降雨测量任务微波成像仪 业务化海表面温度和海冰分析 |
| 英文关键词:shipboard survey sea surface temperature Northwest Indian Ocean Tropical Rainfall Measuring Mission Microwave Imager Operational Sea Surface Temperature and Sea Ice Analysis |
| 基金项目: |
| 作者 | 单位 | E-mail | | 杨广 | 浙江大学海洋学院, 舟山, 316021
卫星海洋环境动力学国家重点实验室, 国家海洋局第二海洋研究所, 杭州, 310012 | | | 何海伦 | 卫星海洋环境动力学国家重点实验室, 国家海洋局第二海洋研究所, 杭州, 310012 | hehailun@sio.org.cn | | 王渊 | 卫星海洋环境动力学国家重点实验室, 国家海洋局第二海洋研究所, 杭州, 310012 | | | 韩喜球 | 海底科学重点实验室, 国家海洋局第二海洋研究所, 杭州, 310012 | | | 王叶剑 | 海底科学重点实验室, 国家海洋局第二海洋研究所, 杭州, 310012 | |
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| 中文摘要: |
| 本文描述了一次西北印度洋夏季进行的船载气象观测。我们使用船载数据评估卫星海表面温度，并发现影响海表面温度误差的主要因素。本文考虑两种卫星数据，一种是微波遥感产品——热带降雨测量任务微波成像仪TMI数据，另一种是融合了微波、红外线和漂流浮标数据的融合数据——业务化海表面温度和海冰分析OSTIA数据。结果表明，融合数据的日平均海表面温度平均误差和均方根误差都小于微波遥感数据。这一结果证实了融合红外线和漂流浮标数据以提高微波遥感海表面温度数据质量的必要性。进一步，本文分析海表面温度误差对于气象参数的依赖性，这些气象参数包括风速、气温、相对湿度、气压和能见度。结果表明，风速与TMI海表面温度误差的相关系数最大；气温是影响OSTIA海表面温度误差最重要的因素，同时，相对湿度与OSTIA海表面温度误差的相关系数也较高。 |
| 英文摘要: |
| A summer-time shipboard meteorological survey is described in the Northwest Indian Ocean. Shipboard observations are used to evaluate a satellite-based sea surface temperature (SST), and then find the main factors that are highly correlated with errors. Two satellite data, the first is remote sensing product of a microwave, which is a Tropical Rainfall Measuring Mission Microwave Imager (TMI), and the second is merged data from the microwave and infrared satellite as well as drifter observations, which is Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). The results reveal that the daily mean SST of merged data has much lower bias and root mean square error as compared with that from microwave products. Therefore the results support the necessary of the merging infrared and drifter SST with a microwave satellite for improving the quality of the SST. Furthermore, the correlation coefficient between an SST error and meteorological parameters, which include a wind speed, an air temperature, a relative humidity, an air pressure, and a visibility. The results show that the wind speed has the largest correlation coefficient with the TMI SST error. However, the air temperature is the most important factor to the OSTIA SST error. Meanwhile, the relative humidity shows the high correlation with the SST error for the OSTIA product. |
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