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Interannual variability of the spring phytoplankton bloom is strongly expressed in estuarine ecosystems such as Chesapeake Bay. Quantifying this variability is essential to resolve ecosystem responses to eutrophication from variability imposed by climate. We developed a 'synoptic climatology' from surface sea-level pressure (SLP) maps to categorize and quantify atmospheric circulation patterns and address climate forcing of phytoplankton dynamics in the Bay. The 10 patterns we identified had unique frequencies-of-occurrence and associated meteorological conditions (i.e. precipitation, temperature, wind speed and direction). Four measures of phytoplankton biomass, surface chlorophyll a (B), euphotic layer chlorophyll a (B eu ), water column chlorophyll a (B wc ), and total biomass (B tot ), were obtained from remotely sensed ocean color data spanning 16 yr (1989 to 2004) combined with concurrent shipboard data. Years with more frequent warm/wet weather patterns had spring blooms that reached peak biomass farther seaward in the estuary, were greater in magnitude, occurred later in the spring, and covered a larger area than years with a predominance of cool/dry weather patterns. Frequencies of winter weather patterns were used to forecast spring B, B eu , B wc , and B tot , explaining between 23 and 89% of the variance in the regional time-series. Residuals from these models did not show time-trends attributable to either accelerating eutrophication or management actions intended to decrease nutrient loadings. These findings extend our understanding of climatic influences on phytoplankton dynamics in the Bay by quantifying the effects of synoptic climate variability on spring bloom intensity, thereby supporting forecasts of seasonal phytoplankton biomass based on sub-continental scale weather patterns in this mid-Atlantic estuary.