A.T.J. de Laat (Jos) has alerted us to a new paper
Dunstone, N. J., and D. M. Smith (2010), Impact of atmosphere and sub-surface ocean data on decadal climate prediction, Geophys. Res. Lett., 37, L02709, doi:10.1029/2009GL041609.
The abstract reads
“We present a set of idealised model experiments that investigate the impact of assimilating different amounts of ocean and atmosphere data on decadal climate prediction skill. Assimilating monthly average sub‐surface temperature
and salinity data successfully initialises the meridional overturning circulation and produces skillful predictions of global ocean heat content. However, when sea surface temperature data is assimilated alone the predictions have much less skill, particularly in the extra‐tropics. The upper 2000m temperature and salinity observations currently provided by the Argo array of floats are therefore potentially well suited to initialising decadal climate predictions. We note however that we do not attempt to simulate the actual distribution of Argo floats. Assimilating data beneath 2000m always reduces the RMSE, with the most significant improvements in the Southern Ocean. Furthermore, assimilating six hourly atmospheric observations significantly improves the forecast skill within the first year, but has little impact thereafter.”
Excerpts from the paper are
“Decadal climate prediction aims to predict natural internal variability in addition to the response of the climate system to anthropogenic forcing. In order to achieve this it is necessary to start from the current state of the climate system.”
“At all forecast lead times, assimilating SST alone has significantly lower skill than the experiments that assimilated sub‐surface temperature and salinity. In particular the SST experiments appear to introduce systematic errors in the North Atlantic with the result that they never achieved skill significantly above that of a persistence forecast. We find a similar situation initially in the Southern Ocean, although performance is better in the Pacific Ocean.”
There are two conclusions from this study that have direct relevance to the IPCC multi-year global climate predictions. First, climate is an initial value problem as I wrote on in the paper
Pielke, R.A., 1998: Climate prediction as an initial value problem. Bull. Amer. Meteor. Soc., 79, 2743-2746.
Secondly, the climate models drift from reality unless real world data is continually assimilated (i.e. inserted) into the model equations. The multi-decadal global climate models have no such real world constraint. There is no way to determine how far they drift from reality, but this study (although with a single idealized model) suggests that they deviate significantly with respect to what the real world will actually be decades from now.