Abstract Summer cyanobacteria blooms regularly occur in the Baltic Sea. The phenology of the bloom, however, is mostly unknown. Data of total biomass of the bloom-forming species Nodularia spumigena, Aphanizomenon sp. and Dolichospermum spp., water column variables, nutrients and weather conditions were used to study and define the phenology and optimum environmental window for the occurrence of cyanobacteria blooms in the Gotland Basin during the period 1990–2017. The intra-annual variability of cyanobacteria biomass was modeled using a Weibull function and a partial least squares regression was used to define the variables that explain the timing of the onset, peak and decline stages of the bloom. On average blooms lasted 41 ± 16 days, starting in mid-June, reaching the maximum of observed biomass by mid-July and ending by the end of July with a total biomass in the three stages of 79, 353 and 161 µg L−1, respectively. The timing of the onset of the bloom was driven by sea surface temperature (14 °C), air temperature (14 °C), outgoing long-wave radiation (−68 W m−2), mixed layer depth (26 m), water column stability expressed as Brunt–Vaisala frequency (−0.02 s−2), phosphate concentration (0.1 mmol m−3) and wind speed (5 m s−1). The time of maximum cyanobacteria biomass occurrence was controlled by sensible (41 W m−2) and latent (−3 W m−2) heat flux. The timing of the decline of the bloom was driven by incoming solar radiation (218 W m−2), net heat flux (178 W m−2), sensible heat flux (35 W m−2), latent heat flux (−12 W m−2) and phosphate concentration (0.1 mmol m−3). If the bloom occurs early or lasts longer depends on the overall effect that these explanatory variables have on each stage of the bloom. The results show that the phenology of the bloom depends in part on the heat exchange that takes place between the water surface and the overlying atmosphere, however, heat flux components are rarely included in bloom-related studies. The results also show that the Weibull function and the optimum environmental window can be used as an approach to define the phenology of a bloom and the environmental conditions that favor it.