In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short‐term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well‐developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short‐ and long‐term. We summarize the current understanding of storm‐induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions. Our understanding of ecosystem‐scale responses to storm events is fragmented, and terminological variability in defining a “storm” hinders resolution of generalizable impacts. We provide a comprehensive synthesis of the interactions between physical properties and biological responses in lakes that demonstrates the context‐dependency of storm impacts; lake/watershed attributes and their antecedent conditions mediate the extent to which storms impact lake ecosystems. We develop a framework which conceptualizes how abrupt, storm‐induced changes in the lake environment influence phytoplankton community dynamics through functional traits, identifies current limitations, and highlights several avenues of research to narrow knowledge gaps in synthetic and interdisciplinary ways.