The quality control(QC) of ocean observational data, essential to establish a high-quality global ocean database, is one of the basic data pre-processing steps in oceanography research, marine monitoring, and forecast...The quality control(QC) of ocean observational data, essential to establish a high-quality global ocean database, is one of the basic data pre-processing steps in oceanography research, marine monitoring, and forecasting. With the introduction of various advanced instruments in recent decades, oceanographic surveys have expanded from coastal regions to open oceans.However, as ocean in-situ observations are obtained using different instruments that offer heterogeneous data qualities, it is paramount that bad data could be accurately and efficiently identified via QC to provide a reliable global ocean database. In this review, we briefly summarize the latest progress of QC for oceanic in-situ observations, and mainly focus on temperature and salinity data. The similarities and differences between QC schemes developed by various ocean organizations are introduced. We also discuss the performances of the various QC schemes and identify the key challenges. Based on the discussions, several recommendations are proposed for future improvements in the QC for ocean observations.展开更多
基金This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB42040402)the Open Fund of State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,MNR(Grant No.QNHX2133)+2 种基金the National Key R&D Program of China(Grant No.2017YFA0603202)the Key Deployment Project of Centre for Ocean Mega-Research of Science,CAS(Grant No.COMS2019Q01)the National Natural Science Foundation of China(Grant No.42076202).
文摘The quality control(QC) of ocean observational data, essential to establish a high-quality global ocean database, is one of the basic data pre-processing steps in oceanography research, marine monitoring, and forecasting. With the introduction of various advanced instruments in recent decades, oceanographic surveys have expanded from coastal regions to open oceans.However, as ocean in-situ observations are obtained using different instruments that offer heterogeneous data qualities, it is paramount that bad data could be accurately and efficiently identified via QC to provide a reliable global ocean database. In this review, we briefly summarize the latest progress of QC for oceanic in-situ observations, and mainly focus on temperature and salinity data. The similarities and differences between QC schemes developed by various ocean organizations are introduced. We also discuss the performances of the various QC schemes and identify the key challenges. Based on the discussions, several recommendations are proposed for future improvements in the QC for ocean observations.
