Decadal prediction skill in the GEOS-5 forecast system Yoo-Geun Ham, Michele M Rienecker, Max J Suarez, Yury Vikhliaev, Bin Zhao, Jelena Marshak, Guillaume Vernieres, Siegfried D Schubert Abstract: A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office’s (GMAO’s) GEOS-5 Atmosphere–Ocean general circulation model. The hind casts are initialized every December 1st from 1959 to 2010, following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multi-variate ensemble optimal interpolation ocean and sea-ice reanalysis, and from GMAO’s atmospheric reanalysis, the modern-era retrospective analysis for research and applications. The mean forecast skill of a three-member-ensemble is compared to that of an experiment without initialization but also forced with observed greenhouse gases. The results show that initialization increases the forecast skill of North Atlantic sea surface temperature compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. On the other hand, the initialization reduces the skill in predicting the warming trend over some regions outside the Atlantic. The annual-mean atlantic meridional overturning circulation index, which is defined here as the maximum of the zonally-integrated overturning stream function at mid-latitude, is predictable up to a 4-year lead time, consistent with the predictable signal in upper ocean heat content over the North Atlantic. While the 6- to 9-year forecast skill measured by mean squared skill score shows 50 % improvement in the upper ocean heat content over the subtropical and mid-latitude Atlantic, prediction skill is relatively low in the subpolar gyre. This low skill is due in part to features in the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region that differ from observations. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts. PDF: P2014_1