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The subpolar North Atlantic is the only extensive region of the world ocean where the sea surface temperature (SST) has cooled since 1900 (IPCC 2013). This cooling occurs in the context of strong multi-decadal variability in SST. The causes of these features of the subpolar North Atlantic are currently debated, and include external forcing as well as externally forced and internally generated variability in the atmosphere and ocean circulation. Understanding the causes of past changes is critical for predicting how the ocean will evolve in the near-term future, as well as in long-term projections.
Here we will address the causes of the cooling trend (the so-called ‘warming hole’) in the context of a highly variable subpolar North Atlantic. As a first step, we will dive into the causes of the trend itself, and evaluate a previously untested mechanism: that the cooling is the ocean response to a northward shifted North Atlantic jet. We will employ a climate model hierarchy that includes: a fully coupled model, a slab ocean model, a slab ocean with Ekman included, as well as forced ocean experiments. The mechanisms revealed in this hierarchy will also be tested in CMIP5/6 model experiments and observations. As a second step, we will examine fluctuations about this trend, and how the forced component can impact internally driven ocean and atmosphere variability. To do this we will develop a new framework that can applied across models for evaluating the time-evolving ocean conditions that can lead to predictability. We will also use a large-archive of CESM and CMIP5/6 simulations to evaluate the relationship between the ensemble-mean forced signal and the spread due to internally-generated variability.
Our proposed work responds to the NOAA Climate Program Office’s “CVP – Decadal Climate Variability and Predictability” competition. In particular, we address the priority area of ‘Investigation of mechanisms that govern variability of the coupled climate system and its predictability on the interannual to multi-decadal timescales within longterm observation data and/or model data (such as, CMIP6), with a focus on either the Atlantic or Pacific Ocean region.’ By using a combination of the CESM model hierarchy, CMIP5/6 data, and observations, we will gain a process-level understanding of the ocean and atmosphere on the interannual to multi-decadal timescales, which will lead to greater confidence in our ability to predict future changes in the North Atlantic and their impacts.

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