Constraining climate predictions using Argo data

For decadal timescales or longer, most of the uncertainty in climate predictions results from the spread of different models' simulated responses to anthropogenic climate forcings (Hawkins and Sutton, 2009). Argo measurements of the sub-surface ocean have great potential to reduce uncertainties in climate predictions, by providing an observational constraint on the rate of ocean heat uptake. There is some evidence to suggest that climate models have overestimated how rapidly heat has penetrated below the ocean’s mixed layer (Forest and Stott, 2007). Continuing sub-surface temperature data will better constrain to what extent climate models could be under-estimating the near-surface temperature response by exporting too much heat to the deep ocean.

Further, sub-surface salinity observations made by Argo will aid an improved quantification of observed changes in the strength of the hydrological cycle. Observed precipitation trends over land demonstrate that the predicted signal of climate change of reductions in the sub-tropics and increases at high latitudes has begun to emerge, although there are also some indications that climate models could underestimate the observed rates of change (Zhang et al., 2007). Ocean salinity acts as an integrator of differences between precipitation and evaporation at the ocean surface and continued data from Argo as the climate signal strengthens will provide important information of changes in the hydrological cycle over the poorly-observed ocean.