ABSTRACT:

The European Union Water JPI (http://www.waterjpi.eu/) has funded the project PROGNOS (Predicting In-Lake Responses to Change Using Near Real Time Models http://prognoswater.org/). PROGNOS developed an integrated approach that couples high frequency (HF) lake monitoring data to dynamic lake water quality models to forecast short-term changes in lake water quality. Here we provide an archive of some of the the data sets that were used by PROGNOS project Partner Aarhus Universtiy to calibrate and verify the performance of the GOTM (https://gotm.net/) and FABM-PCLake models. All data were collected from the Lemming mesocosm B1 tank. The data include temperature and chlorophyll a data.