A Model Study Of Non-stationary Relations Between Teleconnections In The Climate System | 18647
Journal of Earth Science & Climatic Change
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The influence of prominent patterns of climate variability on the regional and global climate and their potential connections
are examined by using the millennium simulations of the Max Planck Institute for Meteorology Earth System Model
(MPI-ESM). Specifically, the North Atlantic Oscillation (NAO), the El Ni?o-Southern Oscillation (ENSO), the Pacific decadal
oscillation (PDO) and the Pacific North American pattern (PNA) are considered. Firstly, the performance of the model in
simulating the observed features of these climate modes was examined. Secondly, it was considered whether there are possible
links between these patterns and how they might be connected over annual to centennial time scales. The results demonstrate
the prominent skill of MPI-ESM in simulating dominant climate patterns. The results from both reanalysis and modelled data
show that NAO and ENSO strongly influence the global climate system, including surface circulation, surface temperature,
regional precipitation and circulation at troposphere level. Besides, the model results support the idea that NAO and ENSO
show low correlation in winter with several short periods of strong correlation. Moreover, the PNA may play a considerable
role in the link between NAO and ENSO. Furthermore, if there is a connection between NAO and ENSO via the troposphere
of the North Pacific and North Atlantic, it is suggested that the NAO events are forced by the ENSO rather than vice versa.
The influence of North Atlantic sea surface temperature anomalies (SSTNA index) on NAO variability in the North Atlantic
sector and the relationship between ENSO and PDO in the Pacific region is confirmed to be significant and stationary in
different periods of the past millennium. However, these teleconnections are stronger at seasonal to annual time scales than at
decadal time scale. These results suggest that model information is potentially useful in seasonal to annual forecasting based
on analyses of prominent climate modes.
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