Singular spectrum analysis for time series with missing data (SSAM) was used to reconstruct components of a 6-yr time series of suspended-sediment concentration (SSC) from San Francisco Bay. Data were collected every 15 min and the time series contained missing values that primarily were due to sensor fouling. SSAM was applied in a sequential manner to calculate reconstructed components with time scales of variability that ranged from tidal to annual. Physical processes that controlled SSC and their contribution to the total variance of SSC were (1) diurnal, semidiurnal, and other higher frequency tidal constituents (24%), (2) semimonthly tidal cycles (21%), (3) monthly tidal cycles (19%), (4) semiannual tidal cycles (12%), and (5) annual pulses of sediment caused by freshwater inflow, deposition, and subsequent wind-wave resuspension (13%). Of the total variance 89% was explained and subtidal variability (65%) was greater than tidal variability (24%). Processes at subtidal time scales accounted for more variance of SSC than processes at tidal time scales because sediment accumulated in the water column and the supply of easily erodible bed sediment increased during periods of increased subtidal energy. This large range of time scales that each contained significant variability of SSC and associated contaminants can confound design of sampling programs and interpretation of resulting data.