Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction.

Area of Science:

• Oceanography
• Data Assimilation
• Climate Science
• Observing Systems

Background:

• Ocean observing system technologies and data assimilation (DA) methods are interdependent.
• New observation types drive DA advancements, and coupled DA can enhance existing observations' value.
• Ocean reanalyses are crucial for climate analysis and initializing long-range prediction models.

Purpose of the Study:

• To highlight the symbiotic relationship between ocean observing systems and data assimilation.
• To encourage better utilization of existing ocean observations through advanced DA techniques.
• To identify challenges and propose solutions for improving ocean reanalyses and prediction systems.

Main Methods:

• Exploration of coupled data assimilation (DA) techniques for integrated ocean and atmosphere analysis.
• Review of current challenges in ocean reanalyses, including system biases and model limitations.
• Discussion on the need for improved communication and protocols between DA and observation communities.

Main Results:

• Strongly coupled DA allows ocean observations to improve atmospheric analyses and vice versa.
• Significant challenges remain in ocean reanalyses due to historical data biases and model assumptions.
• Rapid communication protocols for ocean-observing data are essential for numerical weather prediction (NWP).

Conclusions:

• Enhanced collaboration and support are needed between ocean observing and DA communities.
• New observation types offer potential for enhancing prediction capabilities across multiple timescales.
• Improved communication can guide the design of sustained, adaptive ocean observing networks.