A new ensemble-based targeted observational method and its application in the TPOS 2020.

Area of Science:

• Oceanography
• Climate Science
• Data Assimilation

Background:

• Ensemble Kalman filter (EnKF) methods are crucial for optimal oceanic buoy deployment.
• Targeted observation strategies aim to minimize initial forecast uncertainties.
• Understanding El Niño-Southern Oscillation (ENSO) variability is vital for climate prediction.

Purpose of the Study:

• To develop a novel 'cross-region and cross-variable' targeted observation algorithm.
• To optimize the observational array design for the Tropical Pacific Observation System (TPOS) 2020.
• To improve the prediction of ENSO events in the tropical western Pacific.

Main Methods:

• Introduction of a projection operator into the EnKF optimization process.
• Application of targeted observational analysis for ENSO events.
• Identification of optimal observational sites and vertical levels.

Main Results:

• The first 10 optimal observational sites reduced initial uncertainties by 70%.
• The optimal observational array was located in regions dominated by Rossby wave signals.
• Observations near the thermocline provided the most significant vertical contribution.

Conclusions:

• The proposed algorithm offers a practical approach for designing optimal mooring arrays.
• The findings provide valuable insights into ENSO-related variability.
• This study serves as scientific guidance for enhancing the TPOS observation network.