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

这项建议的目的是建立一个青年科学家网络，由对数据同化和不确定性分析有共同研究兴趣的水文学家和气象学家组成。广义的数据同化将观测和模式结合起来，目的是减少模式预报的不确定性。这一领域的研究在水文学和气象学方面都很成熟，但侧重点不同。该网络希望促进这种专有技术的交流和跨学科合作。此外，它还打算促进水文-气象耦合模式的统一数据同化和不确定性分析方法的发展，这将对洪水预警系统和气候变化影响研究等应用变得非常重要。为实现这些目标，该网络将为研究生组织一次暑期培训班，题为“通过数据同化减少水文和气象模型不确定性的方法”。该暑期班的建议书已同时提交(代码：“HyMeDas暑期班”)。此外，预计该网络将与暑期班的感兴趣的参与者一起组成一个可持续的小组，能够发起与该网络专题有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.