Multidecadal CO2uptake variability of the North Atlantic

Predictability of North Atlantic Multidecadal Climate Variability

Atmospheric weather systems become unpredictable beyond a few weeks, but climate variations can be predictable over much longer periods because of the coupling of the ocean and atmosphere. With the use of a global coupled ocean-atmosphere model, it is shown that the North Atlantic may have climatic predictability on the order of a decade or longer. These results suggest that variations of the d...

A predictability study of simulated North Atlantic multidecadal variability

The North Atlantic is one of the few places on the globe where the atmosphere is linked to the deep ocean through air—sea interaction. While the internal variability of the atmosphere by itself is only predictable over a period of one to two weeks, climate variations are potentially predictable for much longer periods of months or even years because of coupling with the ocean. This work present...

On Multidecadal and Quasi-Decadal North Atlantic Variability

Observed sea surface temperatures (SSTs) in the North Atlantic from 1958 through 2000, as well as data from an ocean model simulation driven with the atmospheric variability observed during the same period, are examined using multichannel singular spectrum analysis. The two leading oscillatory modes are associated with a multidecadal and a quasi-decadal period. The former is connected to a basi...

North Atlantic Multidecadal SST Oscillation: External forcing versus internal variability

Evolution of the Atlantic Multidecadal Variability in a Model with an Improved North Atlantic Current

This article investigates the dynamics and temporal evolution of the Atlantic multidecadal variability (AMV) in a coupled climate model. The model contains a correction to the North Atlantic flow field to improve the path of the North Atlantic Current, thereby alleviating the surface cold bias, a common problem with climate models, and offering a unique opportunity to study the AMV in a model. ...