Optimally growing initial error for predicting the sudden shift in the Antarctic Circumpolar Current transport and its application to targeted observation

• Published in: Ocean Dynamics
• Main Authors: Zhou, Li, Zhang, Kun, Wang, Qiang, Mu, Mu
• Format: Report
• Language: English
• Published: SPRINGER HEIDELBERG 2022
• Subjects: The Antarctic Circumpolar Current; Initial errors; CNOP; Targeted observation; Ocean prediction; Oceanography; NONLINEAR OPTIMAL PERTURBATION; OCEAN CIRCULATION MODEL; KUROSHIO LARGE MEANDER; DRAKE PASSAGE; ADAPTIVE OBSERVATION; SENSITIVE AREAS; WIND STRESS; SEA; PREDICTABILITY; ADJOINT; Antarctic; Drake Passage; The Antarctic; Antarc*
• Online Access: http://ir.qdio.ac.cn/handle/337002/179958; https://doi.org/10.1007/s10236-022-01531-x

Initial errors critically affect the performance of short-term ocean predictions. To investigate the effects of initial errors on the 30-day prediction of the sudden shift in the Antarctic Circumpolar Current (ACC) transport through the Drake Passage (DP), the optimally growing initial error (OGIE) is explored based on the Conditional Nonlinear Optimal Perturbation (CNOP) approach and an eddy-permitting Regional Ocean Modeling System. In the four selected cases, the OGIEs are primarily located under 2000 m in the middle DP of (57 degrees S-62 degrees S, 73 degrees W-64 degrees W). All OGIEs undergo localized evolutions and cause significant transport prediction errors of approximately 40.0 Sv by exciting anomalous dipolar circulations. The vorticity budget analysis indicates linear advection contributes to error vorticity evolutions, whereas nonlinear advection and ageostrophic divergence show damping effects. Moreover, eastward motions exerted by linear advection and westward motions exerted by nonlinear advection together maintain the localized vorticity evolutions. Finally, targeted observation is applied in the OGIE-determined sensitive areas. Observing system simulation experiments suggest that improving initial condition qualities in the OGIE-determined sensitive areas (especially in the deep layers) can effectively enhance the ACC transport predictions. This study reveals the spatial structures and growth mechanism of the OGIEs related to the short-term ACC transport prediction and provides scientific guidance on designing observing networks in the DP.