Two ensembles of 1-month integrations of a coupled land-atmosphere climate
model that differ only in their treatment of land surface boundary conditio
ns have been generated from initial conditions chosen from the July states
taken from each year of a 17-yr integration from the second Atmospheric Mod
el Intercomparison Project (AMIP2). Both ensembles have specified sea surfa
ce temperature from one randomly chosen year, but one ensemble has the land
surface state variables specified in each member at each time step to be i
dentical to those from a single member of the other ensemble. Comparisons w
ith the 17-yr AMIP2 integration provide an estimate of the role of interann
ually varying SST in affecting climate variability. Comparison between the
two ensembles helps to quantify the role of land surface variability on the
variance of surface fluxes and the climate. In this model system, the impa
cts of suppressed ocean variability on intra-ensemble spread are generally
stronger than for suppressed land surface variability. The impacts of land
surface variability on climate variability are clearer on monthly timescale
s than on synoptic timescales. Absolute measures of the impact of surface v
ariability on the synoptic scale are not strong, but the time evolution of
variability is consistent with expectations that the land surface does exer
t some control on climate variability.