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Abstract:

There is increasing demand for robust, reliable and actionable climate information for the next 1 to 50 years. This is challenging for the scientific community as the longest initialized predictions are limited to 10 years (decadal predictions). Thus, to provide seamless information for the upcoming 50 years, information from decadal predictions and uninitialized projections need to be merged. In this study, the ability to obtain valuable climate information beyond decadal time-scales by constraining uninitialized projections using decadal predictions is assessed. The application of this framework to surface temperatures over the North Atlantic Subpolar Gyre region, shows that the constrained uninitialized sub-ensemble has higher skill compared to the overall projection ensemble also beyond ten years when information from decadal predictions is no longer available. Though showing the potential of such a constraining approach to obtain climate information for the near-term future, its utility depends on the added value of initialization.

Abstract:

Recent studies have found evidence of multidecadal variability in northern hemisphere wintertime seasonal forecast skill. Here we assess the robustness of this finding by extending the analysis to analysing a diverse set of ensemble atmospheric model simulations. These simulations differ in either numerical model or type of initialisation and include atmospheric model experiments initialised with reanalysis data and free‐running atmospheric model ensembles. All ensembles are forced with observed SST and seaice boundary conditions. Analysis of large‐scale Northern Hemisphere circulation indicesover the Northern Hemisphere (namely the North Atlantic Oscillation, Pacific North American pattern and the Arctic Oscillation) reveals that in all ensembles there is larger correlation skill in the late century periods than during periods in the mid‐century. Similar multidecadal variability in skill is found in a measure of total skill integrated over the whole of the extratropics. Most of the differences in large‐scale circulation skill between the skillful late period (as well as early period) and the less skillful mid‐century period seem to be due to a reduction in skill over the North Pacific and a disappearance in skill over North America and the North Atlantic. The results are robust across different models and different types of initialisation, indicating that the multidecadal variability in Northern Hemisphere winter skill is a robust feature of 20th century climate variability. Multidecadal variability in skill therefore arises from the evolution of the observed SSTs, likely related to a weakened influence of ENSO on the predictable extratropical circulation signal during the middle of the 20th century, and is evident in the signal‐to‐noise ratio of the different ensembles, particularly the larger ensembles.

Abstract:

Atmospheric circulation is often clustered in so‐called circulation regimes, which are persistent and recurrent patterns. For the Euro‐Atlantic sector in winter, most studies identify four regimes: the Atlantic Ridge, Scandinavian Blocking and the two phases of the North Atlantic Oscillation. These results are obtained by applying k‐means clustering to the first several empirical orthogonal functions (EOFs) of geopotential height data. 51�������ing the observed circulation in reanalysis data, it is found that when the full field data are used for the k‐means cluster analysis instead of the EOFs, the optimal number of clusters is no longer four but six. The two extra regimes that are found are the opposites of the Atlantic Ridge and Scandinavian Blocking, meaning they have a low‐pressure area roughly where the original regimes have a high‐pressure area. This introduces an appealing symmetry in the clustering result. Incorporating a weak persistence constraint in the clustering procedure is found to lead to a longer duration of regimes, extending beyond the synoptic time‐scale, without changing their occurrence rates. This is in contrast to the commonly used application of a time‐filter to the data before the clustering is executed, which, while increasing the persistence, changes the occurrence rates of the regimes. We conclude that applying a persistence constraint within the clustering procedure is a better way of stabilizing the clustering results than low‐pass filtering the data.