2013/07/18 by Alexandru Cioaca, Cioaca, Alexandru, Adrian Sandu +1
Earth and Planetary Sciences · Engineering · Environmental Science · Physics and Astronomy · #Computational Engineering #FOS: Computer and information sciences #Finance #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks #Reservoir Engineering and Simulation Methods #Soil Moisture and Remote Sensing #and Science (cs.CE)
paper · pdf · doi:10.48550/arxiv.1307.5076
openalex publication_date 2013/07/18 · openalex created_date 2022/10/03 · openalex updated_date 2026/07/28
We present an efficient computational framework to quantify the impact of\nindividual observations in four dimensional variational data assimilation. The\nproposed methodology uses first and second order adjoint sensitivity analysis,\ntogether with matrix-free algorithms to obtain low-rank approximations of ob-\nservation impact matrix. We illustrate the application of this methodology to\nimportant applications such as data pruning and the identification of faulty\nsensors for a two dimensional shallow water test system.\n