지구시스템모형에 기반한 해양생태계 예측과 기후 예측에 생물-광학 피드백이 미치는 영향 = ESM-based marine ecosystem prediction and impacts of bio-optical feedback on climate prediction

다국어 초록 (Multilingual Abstract)

The extension of seasonal to interannual prediction of physical climate systems to that of marine ecosystem has a great potential to inform marine resource management strategies. A recent study showed that a global Earth system model (ESM) can skillfully predict marine biogeochemical variables averaged over large ocean basins, demonstrating the feasibility and application of ESM-based biogeochemical forecast systems. This study show that successful chlorophyll prediction skill against satellite observations is possible in large coastal areas. By focusing on the Agulhas and Somali Coastal LME (Large Marine Ecosystem) regions, ESM used in here confirm the significant prediction skill almost up to 2-year lead time. The underlying mechanisms involved in this chlorophyll prediction skill are associated with the westward‐propagating oceanic Rossby wave. This wave as the key mechanism related with chlorophyll prediction skill is initially excited by El Niño/Southern Oscillation (ENSO)-Indian Ocean teleconnections.

This present study also explain that the advantages of ESM are not stalled to biochemical field predictions, but that ESM can help improve the prediction of physical variables through feedback between physical and biological systems. The assessment of feedback impacts on climate prediction is conducted after sea surface temperature (SST) anomaly prediction with bio-optical feedback in Equatorial Pacific Ocean. As a result, bio-optical feedback involving chlorophyll, shortwave heating and SST relationship improves the Nino3.4 index toward observation between summer to winter season for 1 year.

목차 (Table of Contents)

• List of Figures ii
• Abstract iv
• 1. Introduction 1
• 2. Methods 4
• 2.1. Global marine biogeochemical prediction system 4
• 2.2. Retrospective forecast experiment and skill assessment 6
• 2.3. Twin experiment design and skill metrics 7
• 3. Results 9
• 3.1. Biogeochemical prediction assesssment 9
• 3.1.1. Chlorophyll prediction skill in coastal large marine ecosystems 9
• 3.1.2. Mechanisms of chlorophyll prediction skill 11
• 3.1.3. Rossby wave initiated by ENSO-Indian Ocean teleconnection 13
• 3.2. Impact of bio-optical feedback on climate prediction 15
• 3.2.1. ENSO prediction modified by marine phytoplankton 15
• 3.2.2. Mechanism of bio-optical feedback 17
• 3.2.3. Quantitative impacts of bio-optical feedback on climate prediction 18
• 4. Conclusion and discussion 20
• Figures 22
• References 46
• 국문 초록 52