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Data-Model Fusion Approach in Global Change Research: Recent Development and Future Challenges

It is increasingly recognized that global change research requires methods and strategies for combing process models and data in systematic ways. This is leading to research towards the application of model-data fusion approach. The model-data fusion is a new quantitative approach to model analysis and data assimilation that provides a high level of empirical constraint over model predictions based on observations. Applications of model-data fusion require (a) a model that describes the underlying physical, chemical and biological processes, (b) experimental observations and (c) an optimization tool. The optimization tool is used to find optimal estimates of model parameters or states ...
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