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      • Toward Earth system prediction

        박종연,Charles A. Stock,John P. Dunne,Xiaosong Yang,Anthony Rosati 한국기상학회 2019 한국기상학회 학술대회 논문집 Vol.2019 No.10

      • SCISCIESCOPUS

        Seasonal to multiannual marine ecosystem prediction with a global Earth system model

        Park, Jong-Yeon,Stock, Charles A.,Dunne, John P.,Yang, Xiaosong,Rosati, Anthony American Association for the Advancement of Scienc 2019 Science Vol.365 No.6450

        <P><B>Predicting marine futures</B></P><P>The ability to predict how climate variations will affect marine ecosystems would allow better economic and ecosystem planning and management. Park <I>et al.</I> found that a global Earth system model skillfully predicted seasonal to multiannual ocean chlorophyll fluctuations in many regions. This could allow annual fish catches in some regions to be forecast 2 to 3 years in advance.</P><P><I>Science</I>, this issue p. 284</P><P>Climate variations have a profound impact on marine ecosystems and the communities that depend upon them. Anticipating ecosystem shifts using global Earth system models (ESMs) could enable communities to adapt to climate fluctuations and contribute to long-term ecosystem resilience. We show that newly developed ESM-based marine biogeochemical predictions can skillfully predict satellite-derived seasonal to multiannual chlorophyll fluctuations in many regions. Prediction skill arises primarily from successfully simulating the chlorophyll response to the El Niño–Southern Oscillation and capturing the winter reemergence of subsurface nutrient anomalies in the extratropics, which subsequently affect spring and summer chlorophyll concentrations. Further investigations suggest that interannual fish-catch variations in selected large marine ecosystems can be anticipated from predicted chlorophyll and sea surface temperature anomalies. This result, together with high predictability for other marine-resource–relevant biogeochemical properties (e.g., oxygen, primary production), suggests a role for ESM-based marine biogeochemical predictions in dynamic marine resource management efforts.</P>

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