Influence of natural variability and the cold start problem on the simulated transient response to increasing CO2
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The Hadley Centre coupled ocean-atmosphere general circulation model (AOGCM) has been used to study the effect of including the historical increase in greenhouse gases from 1860 to 1990 on the response to a subsequent 1% per year increase in CO2. Results from an ensemble of four experiments which include the historical increase, warm start (WS) experiments, are compared with an ensemble of four experiments which do not include the historical increase, cold start (CS) experiments. In the WS experiments, oceanic thermal inertia prevents the model from reaching equilibrium with the historical change in forcing from 1860 to 1990. This implies an unrealised warming at 1990, defined here as the ‘warming commitment’, increasing the subsequent warming in WS relative to that in CS. The difference in response between a WS experiment and a CS experiment is defined as the cold start error. For surface temperature the ensemble-mean cold start error is 20% of the WS response after 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 process. This result supports the use of simple ocean models with constant diffusivity to produce time-dependent scenarios of globally averaged climate change, subject to the caveat that the changes in ocean circulation simulated by the present AOGCM were smaller than in some previous 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 error for surface temperature is smaller than for sea level. By year 50 the global patterns of temperature change in individual integrations are highly correlated in both the WS and CS ensembles, indicating that natural variability is too small to conceal the climate change signal. The simulated regional changes are statistically significant almost everywhere after 30 y. Before year 30, when the signal-to-noise ratio is smaller, ensemble averaging the changes leads to a substantial increase in significance. In contrast to a previous study also based on an ensemble of integrations, significant changes in precipitation and soil moisture are found. For these quantities the area of significant change grows more slowly with time, however ensemble averaging increases the significant area throughout. The characteristic patterns of change in WS and CS are similar, and evident in the simulation of the past record. This suggests that the component of the historical patterns of change, driven by greenhouse gas forcing, is likely to bear significant similarities to the patterns expected in the future. However, significant regional differences do develop between the WS and CS ensembles. The cold start error has a non-uniform pattern which becomes established in the second half of the experiment, and is not a simple amplification or modulation of the CS or WS response pattern. In northern summer the warming and drying over parts of the Northern Hemisphere continents 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 based on warm start experiments in order to obtain the best estimates of future changes; (2) ensemble means give predictions of regional changes which are statistically more robust than predictions from individual integrations. Note, however, that neither the removal of the cold start 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.
KeywordsCold Start Climate Change Signal Cold Start Problem Warm Start Effective Heat Capacity
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