Liang95b Liang, X.-Z., K. Sperber, W.-C. Wang and A. Samel, 1995: Predictability of SST forced climate signals in two atmospheric general circulation models. Monthly Weather Review (submitted). 
The predictability of atmospheric responses to global sea surface temperature (SST) anomalies is evaluated using ensemble simulations of two general circulation models (GCMs): the GENESIS version 1.5 (GEN) and the ECMWF cycle 36 (ECM). The integrations incorporate observed SST variations but start from different initial land and atmospheric states. Five GEN 1980-1992 and six ECM 1980-1988 realizations are compared with observations to distinguish predictable SST forced climate signals from internal variability. To facilitate the study, correlation analysis and significance evaluation techniques are developed on the basis of time series permutations.

It is found that the annual mean global area with realistic signals is variable dependent and ranges from 3 to 20% in GEN and 6 to 28% in ECM. Due to the existence of model biases, robust responses, which are independent of initial conditions, occur over broader areas. Both GCMs demonstrate that the sensitivity to initial conditions increases and the predictability of SST forced responses decreases from 500 hPa height, sea-level pressure, 200 hPa zonal wind, outgoing longwave radiation to 850 hPa zonal wind. The predictable signals are concentrated in the tropical and subtropical Pacific Ocean and are identified with typical E1 Nino/Southern Oscillation phenomena that occur in response to SST and diabatic heating anomalies over the equatorial central Pacific. ECM is less sensitive to initial conditions and better predicts SST forced climate changes. This is because ECM has a more realistic basic climatology, especially of the wind circulation, and a more vigorous hydrologic cycle.

Differences between the models and observations are identified. For GEN during E1 Nino, the convection does not carry the energy to a sufficiently high altitude, while the spread of the tropospheric warming along the equator is slower and the anomaly magnitude smaller than observed. This impacts model ability to simulate realistic responses over Eurasia and the Indian Ocean. Similar biases exist in the ECM response. In addition, the relationships between upper and lower tropospheric wind responses to SST forcing are not well reproduced by either model.