An ensemble reconstruction of ocean temperature, salinity, and the Atlantic Meridional Overturning Circulation 1960-2021

Ocean reanalyses covering many decades, including those with few observations, are needed to understand climate variability and to initialize and assess interannual to decadal climate predictions. The Met Office Statistical Ocean Re-Analysis (MOSORA) exploits long-range covariances to generate full-depth reanalyses of monthly ocean temperature and salinity even from sparse observations. We extend MOSORA by generating an ensemble that samples uncertainties in long-range covariances. Initial covariances are taken from model runs and these are improved with observations using an iterative process. We demonstrate that covariances are improved by iteration, and that this procedure, using very sparse observations typical of the 1960s, captures many features of analyses benefiting from modern observation density. We investigate the ensemble spread and find that salinity trends in the covariances from model runs can introduce unexpected changes in the reanalyses. We nudge the reanalyses into an ensemble of coupled climate models to produce estimates of the Atlantic Meridional Overturning Circulation (AMOC). At 26 degrees N, the AMOC shows decadal variability consistent with observations at this latitude and shows signs of strengthening in recent years. The ensemble spread in AMOC reconstructions increases with time as more observations interact with uncertain covariances. At 45 degrees N, the amount of decadal variability in the AMOC varies between members, but on shorter timescales the variability is similar across the ensemble. At 45 degrees N, the AMOC can be constrained better with more observations on the western boundary, but longer continuous observations are needed to improve covariances and reduce uncertainties in the AMOC.