A new study supported by the Climate Program Office’s Climate Variability & Predictability (CVP) Program describes how Earth System Models represent ocean convection in the Labrador Sea, a crucial site for understanding climate variability. CVP-funded researchers Takamitsu Ito and Annalisa Bracco worked with a team from the Georgia Institute of Technology, to pinpoint biases in both oceanic and atmospheric model components affecting climate. The results, published in Climate Dynamics, showed that improving ocean stratification is vital for accurate climate change projections, as current models struggle to simulate deep convection in the Labrador Sea. While increasing ocean model resolution helps, it’s not enough to overcome biases in water mass transport, highlighting the complex interplay between ocean and atmospheric dynamics. The authors recommend machine learning techniques to correct biases in ocean stratification and improve climate change projections urgently. CVP supported this project to understand the drivers and impacts of uncertainties involved in modeling the Labrador Sea, as it relates to decadal variability. It is crucial to improve our understanding of deep convection here because of its role in greater carbon cycling and global climate.
For more information, contact Clara Deck.
Image credit: Pixabay
