Perspectives on the intertwinedness of scientific, technological, socioeconomic, and geopolitical bottlenecks on progress towards realising a sustainable future for oceans

Summary:

• Focus: modeling global oceans and their interactions with the climate

  • The future of the oceans is the Blue Economy

  • Will combine 

    • Harvesting+Aquaculture (fish, vegetation)

    • Marine CO2 removal

    • Deep sea mining

    • Energy harvesting

    • Tourism

  • Does not yet exist in a meaningful way

  • Massive-scale ocean operations requires 

    • Cooperation

    • Governance

    • Cost-benefit analysis: How do we value the various resources in the ocean?

• Oceans keep a large portion of the Earth’s heat and carbon budget

  • 91% of global heat stored in ocean water, slow exchange with atmosphere and land

  • 2x more CO2 in ocean than atmosphere

  • Complex chemistry as carbon spreads from atmosphere to surface ocean (water, phytoplankton, etc.) and then deep ocean (water, sediment, etc.)

  • These processes, fluxes and amounts are very uncertain

  • Limited ability to sense ocean processes (chemistry, currents): leads to huge error bars in our models

  • We have sensor technology to constrain it but we have not invested in deploying them on a sufficient scale

• Changing polar climates

  • Both poles are being heated by climate change

  • Heating of the North Atlantic is being taken by the ocean south to Antarctica

  • Massive ice loss will cause major disaster events

  • Study of flow of heat via ocean to Antarctica

    • Upwelling of heat from deep ocean up to the Antarctic coast

    • GLODAP ship measurements: https://glodap.info

    • Argo float measurements: https://argo.ucsd.edu (go between surface and 2km depth)

  • Using all available data to infer the state of the ocean via

    • Southern Ocean High-Resolution (SOhi) Model: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023GL106377

    • Melt from ice shelves on land into the ocean

    • ML critical for this data fusion and model inference

  • Arctic modeling is similar

    • Ice melts from floating ice on the water surface

    • Sea ice protects against heating from warmer ocean and from sun; losing it will make the ocean warming worse

    • Geoengineering has been explored for slowing the impact of heating on ice (very controversial)

    • Climate variability in Arctic links up to equatorial weather patterns (e.g. Monsoon)

    • Hard to collect data in cold Arctic regions

    • Also, melting of ice opens ocean routes, so has geopolitical implications

    • Also motivates calls for global cooperation

• Looking at histories of climate in both poles

  • The poles are generally unsynchronized

  • One gets warmer, while the other cools and then the effects propagate to switch the dynamic

    • The dynamic takes is ~100-~1000 years 

    • We are now warming both poles, so dynamic may change

  • Incorporating these dynamics into ocean models is challenging because data sources are highly inferential and limited in accuracy

  • Interactions between ocean and ice sheets change at the 100k year time frames.

    • Antarctic ice sheets also depress the continent, affecting its tectonics

• Biogeochemistry couples tightly with the evolution of the ocean

  • Organisms and their interaction with ocean chemistry

  • Nutrient cycling between deep ocean and surface

  • Observation: changing the level of background mixing in a state-of-the-art ocean simulation has a 100% impact on CO2 flux in the first year and 60% over 6 years

  • Examining the concentration of iron on the ocean surface

    • There are proposals to do carbon storage by changing iron concentration

    • Impact is very sensitive to the ocean mixing level and whether the iron will be taken up by organisms

• We have diverse available data

  • Enables coherent ocean state estimates

  • But still lots of missing knowledge and insight

• DICE model https://en.wikipedia.org/wiki/DICE_model

  • Integrated assessment model that combines economics and climate

  • Indicates that climate change is done most economically if removals are combined with reductions

• Critical to create a financial framework that makes it possible to connect research and knowledge gathering to commercial value

  • Balancing IP and academic freedom

  • Change in perspective about how to best impact the world positively

  • We have significantly more tech for sensors and modeling, need to connect to governance and finance

• MRV for ocean intervention

  • Sinking wood or improving mangroves can be tracked

  • But changing ocean geochemistry is much harder/more expensive to track

  • Local interventions that affect local ecosystems are easier to finance because the beneficiaries are more clear