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Using a very cheap Data Assimilation (DA) method, I show an alternativeapproach to classical DA for numerical climate models which produce a largeamount of "big data". The problematic features of state-of-the-art highresolution Regional Climate Models are highlighted. One of the shortcomings isthe sensitivity of such models to the slightly different initial and boundaryconditions which could be corrected by assimilating scattered observationaldata. This method might help to reduce the bias of numerical models based onavailable observations within the model domain, especially for thetime-averaged observations and the long-term simulations.

A cheap data assimilation approach for expensive numerical simulations