The impact of the MJO on clusters of wintertime circulation anomalies over the North American region
Recent studies have shown that the Madden–Julian Oscillation (MJO) impacts the leading modes of intraseasonal variability in the northern hemisphere extratropics, providing a possible source of predictive skill over North America at intraseasonal timescales. We find that a k-means cluster analysis of mid-level geopotential height anomalies over the North American region identifies several wintertime cluster patterns whose probabilities are strongly modulated during and after MJO events, particularly during certain phases of the El Niño-Southern Oscillation (ENSO). We use a simple new optimization method for determining the number of clusters, k, and show that it results in a set of clusters which are robust to changes in the domain or time period examined. Several of the resulting cluster patterns resemble linear combinations of the Arctic Oscillation (AO) and the Pacific/North American (PNA) teleconnection pattern, but show even stronger responses to the MJO and ENSO than clusters based on the AO and PNA alone. A cluster resembling the positive (negative) PNA has elevated probabilities approximately 8–14 days following phase 6 (phase 3) of the MJO, while a negative AO-like cluster has elevated probabilities 10–20 days following phase 7 of the MJO. The observed relationships are relatively well reproduced in the 11-year daily reforecast dataset from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). This study statistically links MJO activity in the tropics to common intraseasonal circulation anomalies over the North American sector, establishing a framework that may be useful for improving extended range forecasts over this region.
KeywordsThe Madden–Julian Oscillation (MJO) Tropical–extratropical connections Intraseasonal climate variability Extended range prediction Cluster analysis Model hindcasts The Arctic Oscillation (AO) The Pacific/North America pattern (PNA)
Support for this work was provided by the NOAA Climate Test Bed and the NOAA Student Career Experience Program (SCEP). We would also like to thank Jon Gottschalck and Peitao Peng at the Climate Prediction Center and two anonymous reviews for their very helpful editorial comments on the manuscript.
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