PREDICTABILITY OF SST FORCED CLIMATE SIGNALS IN 2 ATMOSPHERIC GENERAL-CIRCULATION MODELS

The predictability of atmospheric responses to global sea surface temp erature (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 va riations but start from different initial land and atmospheric states. Five GEN 1980-1992 and six ECM 1980-1988 realizations are compared wi th observations to distinguish predictable SST forced climate signals from internal variability. To facilitate the study, correlation analys is and significance evaluation techniques are developed on the basis o f time series permutations. It is found that the annual mean global ar ea with realistic signals is variable dependent and ranges from 3 to 2 0% in GEN and 6 to 28% in ECM. More than 95% of these signal areas occ ur between 35 degrees S-35 degrees N. Due to the existence of model bi ases, robust responses, which are independent of initial condition, ar e identified over broader areas. Both GCMs demonstrate that the sensit ivity to initial conditions decreases and the predictability of SST fo rced responses increases, in order, from 850 hPa zonal wind, outgoing longwave radiation, 200 hPa zonal wind, sea-level pressure to 500 hPa height. The predictable signals are concentrated in the tropical and s ubtropical Pacific Ocean and are identified with typical El Nino/ Sout hern Oscillation phenomena that occur in response to SST and diabatic heating anomalies over the equatorial central Pacific. ECM is less sen sitive to initial conditions and better predicts SST forced climate ch anges. This results from (1) a more realistic basic climatology, espec ially of the upper-level wind circulation, that produces more realisti c interactions between the mean flow, stationary waves and tropical fo rcing; (2) a more vigorous hydrologic cycle that amplifies the tropica l forcing signals, which can exceed internal variability and be more e fficiently transported from the forcing region. Differences between th e models and observations are identified. For GEN during El Nino, the convection does not carry energy to a sufficiently high altitude, whil e the spread of the tropospheric warming along the equator is slower a nd the anomaly magnitude smaller than observed. This impacts model abi lity to simulate realistic responses over Eurasia and the Indian Ocean . Similar biases exist in the ECM responses. In addition, the relation ships between upper and lower tropospheric wind responses to SST forci ng are not well reproduced by either model. The identification of thes e model biases leads to the conclusion that improvements in convective heat and momentum transport parametrizations and basic climate simula tions could substantially increase predictive skill.