The assessment of possible implications of anthropogenic climate change requires the evaluation of results obtained with complex climate models. Here we considered the problem of assessing the impact of climate variability on successional events in a lake (Plußsee) of the temperate region between January and May. We first established a statistical link between large-scale air temperature, at about 1500 m height, and the local temperature, in order to bridge the spatial gap of information obtained from global climate models and local climate which forces processes in the lake. Secondly, the local temperatures were statistically related to biologically induced dynamic features in the lake, derived from Secchi depths readings (as integrated measures). The observed relationships were compared with results from a phyto- and zooplankton population-dynamic model run under different temperature regimes. The local temperatures approximated closely the large-scale temperature. The timing of phyto- and zooplankton maxima (clearwater phase) were negatively related to the temperature. Thus, with a temperature increase both occurred earlier. The intensity of the spring algal maximum was negatively related to its timing, whereas no clear relation between the timing and intensity of the clearwater phase (zooplankton maximum) could be obtained.