We commonly refer to state estimation theory in geosciences as data assimilation (DA). This
term encompasses the entire sequence of operations that, starting from the observations of a …

Variational and ensemble methods have been developed separately by various research
and development groups and each brings its own benefits to data assimilation. In the last …

This open-access textbook's significant contribution is the unified derivation of data-
assimilation techniques from a common fundamental and optimal starting point, namely …

Climate projections continue to be marred by large uncertainties, which originate in
processes that need to be parameterized, such as clouds, convection, and ecosystems. But …

A 6-year-long high-resolution Chinese air quality reanalysis (CAQRA) dataset is presented
in this study obtained from the assimilation of surface observations from the China National …

A central research challenge for the mathematical sciences in the twenty-first century is the
development of principled methodologies for the seamless integration of (often vast) data …

The subject of inverse problems in differential equations is of enormous practical
importance, and has also generated substantial mathematical and computational …

This book places data assimilation (DA) into the broader context of inverse problems and the
theory, methods, and algorithms that are used for their solution. It strives to provide a …

Reservoir computing systems, a class of recurrent neural networks, have recently been
exploited for model-free, data-based prediction of the state evolution of a variety of chaotic …

Data Assimilation comprehensively covers data assimilation and inverse methods, including
both traditional state estimation and parameter estimation. This text and reference focuses …