INFLUENCE OF NATURAL VARIABILITY AND THE COLD START PROBLEM ON THE SIMULATED TRANSIENT-RESPONSE TO INCREASING CO2

The Hadley Centre coupled ocean-atmosphere general circulation model ( AOGCM) has been used to study the effect of including the historical i ncrease in greenhouse gases from 1860 to 1990 on the response to a sub sequent 1% per year increase in CO2. Results from an ensemble of four experiments which include the historical increase, warm start (WS) exp eriments, are compared with an ensemble of four experiments which do n ot include the historical increase, cold start (CS) experiments. In th e WS experiments, oceanic thermal inertia prevents the model from reac hing equilibrium with the historical change in forcing from 1860 to 19 90. This implies an unrealised warming at 1990, defined here as the 'w arming commitment', increasing the subsequent warming in WS relative t o that in CS. The difference in response between a WS experiment and a CS experiment is defined as the cold start error. For surface tempera ture the ensemble-mean cold start error is 20% of the WS response afte r year 30 and 10% at the time of doubling CO2 (year 70). For sea level the reduction in the CS response is more pronounced, amounting to 60% at year 30 and 40% at the time of doubling. The vertical transfer of heat in the ocean is found to correspond to an equivalent diffusion pr ocess. This result supports the use of simple ocean models with consta nt diffusivity to produce time-dependent scenarios of globally average d climate change, subject to the caveat that the changes in ocean circ ulation simulated by the present AOGCM were smaller than in some previ ous cases. In the WS integrations the vertical temperature gradient is larger than in CS due to the historical forcing influence, leading to more efficient heat loss from the base of the mixed layer and hence a larger effective heat capacity. This explains why the cold start erro r for surface temperature is smaller than for sea level. By year 50 th e global patterns of temperature change in individual integrations are highly correlated in both the WS and CS ensembles, indicating that na tural variability is too small to conceal the climate change signal. T he simulated regional changes are statistically significant almost eve rywhere after 30 y. Before year 30, when the signal-to-noise ratio is smaller, ensemble averaging the changes leads to a substantial increas e in significance. In contrast to a previous study also based on an en semble of integrations, significant changes in precipitation and soil moisture are found. For these quantities the area of significant chang e grows more slowly with time, however ensemble averaging increases th e significant area throughout. The characteristic patterns of change i n WS and CS are similar, and evident in the simulation of the past rec ord. This suggests that the component of the historical patterns of ch ange, driven by greenhouse gas forcing, is likely to bear significant similarities to the patterns expected in the future. However, signific ant regional differences do develop between the WS and CS ensembles. T he cold start error has a non-uniform pattern which becomes establishe d in the second half of the experiment, and is not a simple amplificat ion or modulation of the CS or WS response pattern. In northern summer the warming and drying over parts of the Northern Hemisphere continen ts is larger in CS than in WS, due to a smaller net moisture flux from sea to land. The conclusions are: (1) climate predictions should be b ased on warm start experiments in order to obtain the best estimates o f future changes; (2) ensemble means give predictions of regional chan ges which are statistically more robust than predictions from individu al integrations. Note, however, that neither the removal of the cold s tart error nor the use of ensemble averaging can reduce uncertainties in the regional changes arising from model deficiencies, which remain considerable at the present stage of development.