Distinguishing between the SST‐forced variability and internal variability in mid latitudes: Analysis of observations and GCM simulations
Authors: Straus David M. , Shukla J. 
Published: September 2010

It is shown that the dominant structure of the seasonal‐mean mid‐latitude circulation (500 hPa height) pattern over the Pacific‐North America (PacNA) region forced by tropical sea surface temerature (SST)‐related diabatic heating, is distinctly different from the seasonal‐mean internal variability pattern that occurs in the absence of El Niño Southern Oscillation (ENSO) related SST anomalies. The separation of these two patterns is accomplished by utilizing ensemble General Circulation Model (GCM) integrations in conjunction with re‐analyses.

Ensemble simulations made with the GCM of the Center for Ocean‐Land‐Atmosphere Studies (COLA) are compared to the re‐analyses of the National Centers for Environmental Prediction (NCEP) for the 16 winters 1981/82–96/97. The GCM ensemble for each winter consists of 9 integrations initialized from analyses, and utilizing the observed time‐varying SST. In addition, a 39‐year simulation with the same GCM using climatological SSTs (with the observed annual cycle) is used.

The hemispheric North Atlantic/Arctic pattern is the leading seasonal‐mean empirical orthogonal function (EOF) for: (i) all GCM seasonal means in the ensemble simulations; (ii) the NCEP re‐analyses; and (iii) the climatological SST integration. This mode is removed from these datasets.

The total seasonal‐mean variance of all GCM ensemble integrations is generally quite realistic in the PacNA region. The variance of GCM seasonal‐mean deviations about the ensemble mean agrees with that in the climatological SST GCM run, but is about 20% weaker than the observed variance for 29 non‐ENSO winters from the NCEP re‐analyses. The ratio of the SST‐forced variance (obtained from the variance of ensemble means but corrected for the finite sample size) to the internal variance (from the deviations about the ensemble mean) exceeds 2.5 in the eastern Pacific and 4.5 over Mexico. It is highly significant (99% confidence level) over most of the PacNA region.

A number of techniques are used to calculate the patterns forced by SST heating and the internal variability patterns. The SST‐forced mid‐latitude circulation pattern is calculated in seven ways, namely: (1) as the leading EOF of the ensemble‐mean GCM height field for the 16 winters; (2) as the leading mode of a singular‐value decomposition (SVD) analysis of height with tropical diabatic heating from the GCM; (3) as the leading EOF (as above) for NCEP re‐analyses for the same 16 winters; (4) as the leading SVD mode (as above) for the NCEP re‐analyses for the same 16 winters; (5) as the leading EOF of height from re‐analyses for the 10 winters having the five strongest warm and five strongest cold tropical SST anomalies in the last 39 years; (6) as the leading SVD mode (as above) from re‐analyses for these same 10 extreme‐SST winters; (7) as a regression of GCM‐simulated height on a tropical SST time series obtained from the first EOF mode of re‐analysis tropical diabatic heating. It is found that the results of all of these techniques agree extremely well with each other, and that the leading modes in the EOF (SVD) analyses explain large amounts of variance (squared covariance), about 50% (90%).

The spread of projections of individual seasonal means on the leading SVD mode of the seasonal‐ensemble means, is less than the variation of the projection of the ensemble means on the SVD mode (90% significance level).

We draw two conclusions: first, that the GCM ensemble means simulate the observed anomalies with high accuracy; and second, that the observed and simulated anomalies are indeed forced by tropical diabatic heating.

The internal variability pattern was calculated in three different ways: (1) as the leading EOF of height of the deviations of each seasonal mean about the corresponding ensemble mean for that winter, (2) as the leading height EOF from the 39‐year GCM integration forced by climatological (but annually varying) SST; and (3) as the leading height EOF from re‐analyses for 29 winters not associated with very warm and cold tropical SSTs. The patterns derived from these analyses have a common structure. It is found that it is this internal variability pattern, and not the SST‐forced pattern described above, that closely resembles the ‘PNA’ pattern of Wallace and Gutzler.

The SST‐forced pattern in the GCM (characterized by the heterogeneous correlation pattern of the leading SVD mode for the ensemble means) is significantly different (95% confidence level) from the internal variability pattern (characterized by the homogeneous correlation pattern of the leading EOF of the GCM deviations about the ensemble mean) over a region in western North America and the adjoining eastern Pacific, a region north‐east of the Great Lakes, and a small region in the Gulf of Alaska.