INTERANNUAL VARIABILITY AND PREDICTABILITY IN AN ENSEMBLE OF AMIP CLIMATE SIMULATIONS CONDUCTED WITH THE CCC GCM2

This study considers an ensemble of six 10-year climate simulations co nducted with the Canadian Climate Centre 2nd generation General Circul ation Model (CCC GCM2). Each simulation was forced according to the At mospheric Model Intercomparison Project (AMIP) experimental protocol u sing monthly mean sea surface temperatures and sea-ice extents based o n observations for January, 1979 to December 1988. One simulation, con ducted on a CRAY computer, was initiated from analysed 1 January 1979 conditions while the remaining 5 simulations, conducted on a NEC compu ter, were initiated from previously simulated model states obtained fr om a long control integration. The interannual variability and potenti al predictability of simulated and observed 500 hPa geopotential, 850 hPa temperature and 300 hPa stream function are examined and inter-com pared using statistical analysis of Variance techniques to partition v ariance into a number of components. The boundary conditions specified by AMIP are found to induce statistically significant amounts of pred ictable variance on the interannual time scale in the tropics and, to a lesser extent, at extratropical latitudes. In addition, local intera ctions between the atmosphere and the land surface apparently induce s ignificant amounts of potentially predictable interannual variance in the tropical lower atmosphere and also at some locations in the temper ate lower atmosphere. No evidence was found that the atmosphere's int ernal dynamics on their own generate potentially predictable variation s on the interannual time scale. The sensitivity of the statistical me thods used is demonstrated by the fact that we are able to detect diff erences between the climates simulated on the two computers used. The causes of these physically insignificant changes are traced. The stati stical procedures are checked by confirming that the choice of initial conditions does not lead to significant intersimulation variation. Th e simulations are also interpreted as an ensemble of climate forecasts that rely only on the specified boundary conditions for their predict ive skill. The forecasts are verified against observations and against themselves. In agreement with other studies it was found that the for ecasts have very high skill in the tropics and moderate skill in the e xtratropics.