The ACPI project, element 1: Initializing a coupled climate model from observed conditions

A problem for climate change studies with coupled ocean-atmosphere models has been how to incorporate observed initial conditions into the ocean, which holds most of the 'memory' of anthropogenic forcing effects. The first difficulty is the lack of comprehensive three-dimensional observations of the current ocean temperature ( T) and salinity ( S) fields to initialize to. The second problem is that directly imposing observed T and S fields into the model results in rapid drift back to the model climatology, with the corresponding loss of the observed information. Anthropogenic forcing scenarios therefore typically initialize future runs by starting with pre-industrial conditions. However, if the future climate depends on the details of the present climate, then initializing the model to observations may provide more accurate forecasts. Also, this similar to 130 yr spin up imposes substantial overhead if only a few decades of predictions are desired. A new technique to address these problems is presented. In lieu of observed T and S, assimilated ocean data were used. To reduce model drift, an anomaly coupling scheme was devised. This consists of letting the model's climatological (pre-industrial) oceanic and atmospheric heat contents and transports balance each other, while adding on the ( much smaller) changes in heat content since the pre-industrial era as anomalies. The result is model drift of no more than 0.2 K over 50 years, significantly smaller than the forced response of 1.0 K. An ensemble of runs with these assimilated initial conditions is then compared to a set spun up from pre-industrial conditions. No systematic differences were found, i.e., the model simulation of the ocean temperature structure in the late 1990s is statistically indistinguishable from the assimilated observations. However, a model with a worse representation of the late 20th century climate might show significant differences if initialized in this way.