To improve our mechanistic understanding and predictive capacities with respect to climate change effects on the spring phytoplankton bloom in temperate marine systems, we used a process-driven dynamical model to disentangle the impact of potentially relevant factors which are often correlated in the field. The model was based on comprehensive indoor mesocosm experiments run at four temperature and three light regimes. It was driven by time-series of water temperature and irradiance, considered edible and less edible phytoplankton separately, and accounted for density-dependent grazing losses. It successfully reproduced the observed dynamics of well edible phytoplankton in the different temperature and light treatments. Four major factors influenced spring phytoplankton dynamics: temperature, light (cloudiness), grazing, and the success of overwintering phyto- and zooplankton providing the starting biomasses for spring growth. Our study predicts that increasing cloudiness as anticipated for warmer winters for the Baltic Sea region will retard phytoplankton net growth and reduce peak heights. Light had a strong direct effect in contrast to temperature. However, edible phytoplankton was indirectly strongly temperature-sensitive via grazing which was already important in early spring at moderately high algal biomasses and counter-intuitively provoked lower and later algal peaks at higher temperatures. Initial phyto- and zooplankton composition and biomass also had a strong effect on spring algal dynamics indicating a memory effect via the broadly under-sampled overwintering plankton community. Unexpectedly, increased initial phytoplankton biomass did not necessarily lead to earlier or higher spring blooms since the effect was counteracted by subsequently enhanced grazing. Increasing temperature will likely exhibit complex indirect effects via changes in overwintering phytoplankton and grazer biomasses and current grazing pressure. Additionally, effects on the phytoplankton composition due to the species-specific susceptibility to grazing are expected. Hence, we need to consider not only direct but also indirect effects, e.g. biotic interactions, when addressing climate change impacts.