|
ENSO Diversity in the NCAR-CCSM4 Model
Antonietta Capotondi
(1) CIRES (2) NOAA ESRL PSD1
El Niño-Southern Oscillation (ENSO) is a fundamental component of the climate system due to its profound impact upon the global climate. Over the last few years extensive literature has developed to describe a type of El Niño in which the maximum sea surface temperature (SST) anomalies are located in the central equatorial Pacific rather than in the eastern Pacific, as in the canonical event. This central equatorial Pacific warming has been referred to as “Central Pacific El Niño” (CP- El Niño), “warm-pool El Niño”, “dateline El Niño”, and “El Niño Modoki” in an attempt to distinguish it from the classical Eastern Pacific (EP) El Niño. However, it is not clear whether there is a clear dichotomy between eastern vs. central Pacific warming events, or whether the location of maximum warming ranges over a continuum of longitudes resulting in events that could be defined as “central”, “central-eastern” or “eastern”.
Different locations of maximum warming can lead to different patterns of extra-tropical teleconnections. In particular, the dominance of CP- vs. EP- El Niño over decadal long periods seems to produce a decadal modulation of the influence of ENSO upon temperature and precipitation over the United States. Central Pacific warming appears also to influence North Atlantic tropical cyclones, and may be linked to Antarctic warming.
In this study we use the recently-released NCAR-CCSM4, a state-of-the-art climate model whose representation of ENSO has a large degree of realism, to characterize ENSO diversity, dynamical processes associated with different ENSO “flavors”, and the dependency of the teleconnection patterns upon the longitude of maximum warming. We first validate some aspects of ENSO diversity in the model against the Simple Ocean Data Assimilation (SODA) product, as well as other SST data sets. We then use 500 years of model output to examine the teleconnection patterns associated with different ENSO flavors. The much longer duration of the model time series, relative to the observational record, allows a characterization of ENSO diversity with a higher degree of statistical significance.
|
|
