Satellite temporal resolutions are vital for the timely detection of phytoplankton blooms in inland waters using satellite observations due to rapid phytoplankton migration and reproduction. However, the effects of satellite temporal resolutions on the remote derivation of trends in phytoplankton have not yet been assessed. To address this issue, we first used the daily Moderate–resolution Imaging Spectroradiometer (MODIS)–derived phytoplankton blooms in a typical bloom–frequent lake (Lake Taihu, China) between 2001 and 2020 to simulate a series of phytoplankton bloom data sets with temporal resolutions of 2 days to 30 days. We then revealed the differences in the trends of the phytoplankton blooms and their responses to the climatic factors derived from these data sets; we subsequently quantified the relationships between the differences and the temporal resolutions at daily, monthly, and yearly scales. We found that there were significant inconsistencies in the trends in the phytoplankton bloom areas derived from the simulated series data sets with different temporal resolutions; the relations of the MODIS–derived phytoplankton bloom areas to those derived from the simulated series data sets became weaker as the temporal resolutions of the simulated series data sets decreased; the responses of the phytoplankton blooms to the climatic factors quantified by the simulated series data sets were also varied with the temporal resolutions at daily, monthly, and yearly scales. These results from simulated data were also validated by satellite data of Lake Taihu, Lake Chaohu, and Lake Dianchi, three eutrophic lakes in China. In brief, our results cautioned against the use of satellite data with low temporal resolutions to reveal long–term phytoplankton–bloom dynamics.