Predictability of Anomalous Storm Tracks from Seasonal to Decadal ScalesGil Compo
This paper is concerned with estimating the predictable variation of extratropical daily weather statistics ("stormtracks") associated with sea surface temperature (SST) changes on interannual to interdecadal scales, and its magnitude relative to the unpredictable noise. The SST-forced stormtrack signal in each winter in 1950-99 is defined as the mean stormtrack anomaly obtained in an ensemble of atmospheric general circulation model (GCM) integrations with prescribed observed SSTs. Two sets of relatively small (9- to 13-member) ensembles available from two modeling centers (NCAR and NCEP), with anomalous SSTs prescribed either globally or in the tropics alone, are used. Since the stormtrack signals cannot be derived directly from the archived GCM output, they are diagnosed from the SST-forced winter-mean 200 mb height signals using an empirical linear stormtrack model (STM). For two particular winters (the El Nino of JFM 1987 and the La Nina of JFM 1989), the stormtrack signals and noise are estimated directly, and more accurately, from additional large (60-member) ensemble runs of the NCEP GCM. The linear STM is shown to be remarkably successful at capturing the GCM's stormtrack signal in these two winters, and is thus suitable for estimating the signal in other winters.
The principal conclusions from this analysis are as follows. A predictable SST-forced stormtrack signal exists in many winters, but its strength and pattern can change substantially from winter to winter. The correlation of the SST-forced and observed stormtrack anomalies is high enough in the Pacific-North American (PNA) sector to be of practical use. Most of the SST-forced signal is associated with tropical Pacific SST forcing; the central Pacific (Nino-4) is somewhat more important than the eastern Pacific (Nino-3) in this regard. Variations of the pattern correlation of the SST-forced and observed stormtrack anomaly fields from winter to winter, and among 5- winter averages, are generally consistent with variations of the signal strength, and to that extent are identifiable a priori. Larger pattern correlations for the 5-winter averages in the second half of the 50-yr record, and also the 50-yr stormtrack trend, are consistent with the stronger ENSO SST forcing in the second half. None of these conclusions, however, apply in the Euro-Atlantic sector, where the correlations of the SST-forced and observed stormtrack anomalies are found to be much smaller. Given also that they are inconsistent with the estimated signal to noise ratios, substantial GCM error in representing the response in this region to tropical SST forcing, rather than intrinsically low Euro-Atlantic stormtrack predictability, is argued to be behind these lower correlations.
2 PM/ DSRC 1D 403