Young scientist network on hydrological and meteorological data assimilation (HyMeDAs network)

这项建议的目的是建立一个水文学家和气象学家青年科学家网络，共同研究数据同化和不确定性分析。广义上的数据同化将观测和模型结合起来，目的是减少模型预测的不确定性。这一研究领域在水文学和气象学方面都很成熟，但有不同的重点。该网络希望促进这种专门知识的交流和跨学科合作。此外，它还打算促进为耦合水文气象模型开发统一的数据同化和不确定性分析方法，这对于洪水预警系统和气候变化影响研究等应用将变得非常重要。为实现这些目标，该网络将为研究生组织一个暑期班，题为“通过数据同化减少水文和气象模型不确定性的方法”。同时还提交了一份关于这一暑期学校的提案（代码：“HyMeDAs暑期学校”）。此外，预计该网络与暑期学校的感兴趣的参与者将形成一个可持续的小组，能够启动与网络主题相关的跨学科研究提案。

The purpose of this proposal is to establish a young scientist network of hydrologists and meteorologists with shared research interest in data assimilation and uncertainty analysis. Data assimilation in the broad sense combines observations and models with the goal to reduce the uncertainty of model predictions. This field of research is well established in both hydrology and meteorology, but with different focuses. The network wants to foster the exchange of this know-how and interdisciplinary co-operation. Furthermore, it intends to stimulate the development of unified data assimilation and uncertainty analysis methods for coupled hydro-meteorological models, which will become very important for application like e.g. flood warning systems and climate change impact studies. To reach these goals, the network will organize a summer school for postgraduate students entitled ’Methods for reducing the uncertainty of hydrological and meteorological models through data assimilation’. A proposal for this summer school has been submitted in parallel (Code: “HyMeDAs summer school”). In addition, it is expected that the network together with interested participants of the summer school will form a sustainable group that is able to initiate an interdisciplinary research proposal that is related to the topic of the network.