Danish Lemming experimental facility high-frequency data

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.

欧洲联盟水资源联合计划倡议（http://www.waterjpi.eu/）资助了PROGNOS项目（通过近实时模型预测湖泊对变化的响应，http://prognoswater.org/）。PROGNOS项目研发了一种综合方法，该方法将高频（HF）湖泊监测数据与动态湖泊水质模型相结合，以预测湖泊水质短期变化。在此，我们提供了一些数据集的存档，这些数据集由合作伙伴奥尔胡斯大学在PROGNOS项目中用于校准和验证GOTM（https://gotm.net/）和FABM-PCLake模型的性能。所有数据均收集自勒明特生境B1罐。数据包括温度和叶绿素a数据。