Abstract
We use a new method based on point correlation maps and self-organising maps (SOMs) to identify teleconnection patterns in 60 yr of National Centres for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) sea level pressure (SLP) re-analysis data. The most prevalent patterns are the El Nino Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO) and the Southern Annular Mode (SAM). Asymmetries are found between base points in opposite centres of action of the NAO and the Pacific North America pattern (PNA). The SOM-based method is a powerful tool that allows us to efficiently assess how realistically teleconnections are reproduced in any climate model. The degree of agreement between modelled and re-analysis-based teleconnections (or between different models) can be summarised in a single plot. Here, we illustrate this by assessing the skill of the medium complexity climate model FORTE (Fast Ocean Rapid Troposphere Experiment). FORTE reproduces some realistic teleconnections, such as the Arctic Oscillation (AO), the NAO, the PNA, the SAM, the African Monsoon and ENSO, along with several other teleconnections, which resemble to varying degrees the corresponding NCEP patterns. However, FORTE tends to underestimate the strength of the correlation patterns and the patterns tend to be slightly too zonal. The accuracy of frequency of occurrence is variable between patterns. The Indian Ocean is a region where FORTE performs poorly, as it does not reproduce the teleconnection patterns linked to the Indian Monsoon. In contrast, the North and equatorial Pacific and North Atlantic are reasonably well reproduced.
Highlights
Teleconnections span the timeframe between weather and climate, modulating average weather patterns on seasonal to decadal timescales
To address some of the shortcomings of current methods for investigating teleconnections and provide an alternative technique for approaching gridded datasets, this paper describes a method for identifying teleconnections that combines point correlation maps with self-organising map (SOM)
Using NCEPÁ NCAR re-analysis sea level pressure (SLP) we have demonstrated that the method can identify well-known teleconnection patterns, such as El Nino Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), the PNA and the Indian Monsoon, and associate each pattern with a frequency of occurrence
Summary
Teleconnections span the timeframe between weather and climate, modulating average weather patterns on seasonal to decadal timescales. It is a method that has similar benefits to EOF analysis, in that it can identify spatial patterns and be used to trace the evolution of patterns over time It is much less rigid in its results and provides a compact way to summarise a large amount of information about teleconnections on one figure. We suggest that the point correlation maps can be used as an intermediate step between the raw data and the SOM to identify the relationships within the data, before allowing the SOM to summarise and organise the correlation maps to reveal the teleconnections This method will be used to examine teleconnections in National Centres for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data, which are used as a benchmark to test the realism of teleconnections simulated by the medium complexity climate model FORTE (Fast Ocean Rapid Troposphere Experiment). Appendix C contains a glossary of definitions for the acronyms and terminology used throughout the paper
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