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2015
This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters. The first contribution by Jan van Leeuwen focuses on the potential of proposal densities.
Van Leeuwen, Peter Jan +2 more
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This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters. The first contribution by Jan van Leeuwen focuses on the potential of proposal densities.
Van Leeuwen, Peter Jan +2 more
openaire +2 more sources
Sequential Data Assimilation Techniques for Data Assimilation
2020The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques.
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Introduction to Data Assimilation
2011The basic purpose of data assimilation is to combine different sources of information to estimate at best the state of a system. These sources generally are observations (data), a numerical model and error statistics. Why not simply use observations? First, because observations are sparse or partial in geophysics.
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Deep Data Assimilation: Integrating Deep Learning with Data Assimilation
Applied Sciences (Switzerland), 2021Yi-Ke Guo +2 more
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Global Mercury Assimilation by Vegetation
Environmental Science & Technology, 2021, Daniel Obrist
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