全球船舶和浮标观测海表温度数据集及数据特征对比评估  

The global ship and buoy sea surface temperature observation dataset and comparative evaluation of data characteristics

作　　者：宇婧婧 林楚勇 何敏 刘健 YU Jingjing;LIN Chuyong;HE Min;LIU Jian(Ocean Data Center,Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082,China)

机构地区：[1]南方海洋科学与工程广东省实验室(珠海)海洋数据中心,广东珠海519082

出　　处：《大气科学学报》2025年第1期93-105,共13页Transactions of Atmospheric Sciences

基　　金：南方海洋科学与工程广东省实验室(珠海)自主科研项目(SML2021SP102);国家自然科学基金项目(42175026)。

摘　　要：现场观测不仅是最为传统的海表温度测量方式,也是获取海表温度最直接、最准确的方式之一,因此现场观测海表温度资料是所有其他海温数据产品研制的基础与保障。船舶和浮标观测是两类现场观测海表温度的主要手段,本文收集整合了全球多源现场观测海表温度资料,并利用ERA5再分析资料,对数据进行了统一的质量控制加工,分别形成“1900—2023年全球船舶海表温度观测数据集”和“1976—2023年全球浮标海表温度观测数据集”。进一步评估表明:浮标观测数据的正确率较高,其数据质量高于船舶观测数据。20世纪90年代以后,浮标观测记录数远超过船舶观测,主要原因是浮标时间上连续的观测带来庞大的观测记录数,但浮标资料的时空覆盖率远低于船舶观测,对全球或大面积海表温度的代表性差,无法仅利用浮标资料进行全球海表温度趋势变化的研究,但可作为精度较高的数据源订正或评估其他数据。船舶资料相对浮标资料有正的系统偏差。全球的船舶海表温度观测记录数在1961年以后显著上升,70—90年代间达到峰值,90年代以后船舶观测数减少并趋于平稳,船舶资料虽然观测样本数相对浮标较少,但覆盖的时空范围相对较大,在全球海表温度趋势变化研究中具有重要参考意义。Sea surface temperature(SST)is a crucial indicator of heat exchange between the ocean and atmosphere.As one of the most important ocean environmental parameters describing the thermal state of the ocean surface,it is widely used in research and applications such as upper ocean processes,air-sea heat exchange,numerical simulation and forecasting of the ocean-atmosphere system.In-situ observation is one of the most direct and accurate ways to obtain SST,primarily through conventional observation systems such as offshore buoys,coastal stations,and ships.In-situ SST observations serve as the foundation for all other sea temperature data products.Whether it is gridded SST data products,satellite-retrieved SST products,multi-source merged products,or reanalysis data,these SST data products all rely on ship and buoy observation data as the basic support.Therefore,focusing on ships and buoys as the two primary observation methods for SST,this work collected SST observation data from multiple sources such as ICOADS,GTS,CFSR_OBS,GDAS_OBS,and offshore China.Through decoding,extraction,duplicate checking,standardization,and other steps,a relatively complete and long-term sequence of global SST observation dataset was integrated.Besides the traditional quality control techniques for gross errors,the quality control scheme developed for this dataset also includes a technical approach leveraging model analysis fields for observation data quality control.Specifically,using ERA5 reanalysis data,a unified quality control process was applied to the data.The quality control scheme formulated can remove large variations or anomalies in SST.The final products,the“Global Ship-Based SST Observation Dataset from 1900 to 2023”and the“Global Buoy-Based SST Observation Dataset from 1976 to 2023,”can provide fundamental data support for subsequent SST data evaluation,multi-source SST data merging,and global climate change analysis.This paper further evaluates the data characteristic differences,and the main conclusions are as follows

关 键 词：船舶 浮标 海表温度 现场观测 气候研究 

分 类 号：P731.11[天文地球—海洋科学]