[A-CG40] Earth System Observation Impacts on Climate and Ocean Predictions

[ACG40-01] Impact of the Argo data quality control on ocean reanalyses demonstrated by coordinated observing system experiments

*Yosuke Fujii^1,2, Ichiro Ishikawa¹, Eric de Boisseson³, Yiguo Wang⁴, Hao Zuo³ (1.Meteorological Research Institute, Japan Meteorological Agency, 2.The Institute of Statistical Mathematics, 3.European Centre for Medium-Range Weather Forecasts, 4.Nansen Environmental and Remote Sensing Center)

Keywords:Argo, Ocean Data Assimilation, Observing System Experiment, SynObs, UN Ocean Decade

“Synergistic Observing Network for Ocean Prediction” (SynObs) is the United Nations Ocean Decade Project that seeks the way to extract maximum benefit from combining various observation platforms’ measurements, typically satellite and in situ observation data, for ocean predictions. SynObs aims to optimize the ocean observing network through evaluatiion of ocean observation impacts on ocean predictions, and encourages the development of data assimilation schemes which enable us to use observation data more effectively.

Under the framework of SynObs, internationally coordinated observing system experiments (OSEs) were conducted in order to evaluate the effects of Argo data quality control (QC), by using the three global ocean data assimilation systems developed in different prediction centers. During the experimental period between 2015 and 2020, some Argo floats are affected by the abrupt salinity drifts, which caused spurious increasing trend of the global mean salinity in the ocean reanalyses using the observations with only real-time QC applied. The spurious trend is mitigated by applying the gray list provided by the Argo Global Data Assembly Centres (GDAC), and further reduced by assimilating the delayed-mode Argo data of the Argo GDAC instead of the real-time Argo data. These impacts of the Argo QC are generally consistent among the three ocean data assimilation systems. Further investigations in the JMA’s system show that errors in the analyzed salinity with respect to the delayed-mode Argo data are smaller in the OSE with more rigorous QC, and the spatiotemporal variations in the sea-surface dynamic height are reproduced better.