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 …

Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …

Progress within physical oceanography has been concurrent with the increasing
sophistication of tools available for its study. The incorporation of machine learning (ML) …

The climate research community uses atmospheric reanalysis data sets to understand a
wide range of processes and variability in the atmosphere, yet different reanalyses may give …

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

Abstract The ensemble Kalman filter (EnKF) is a sequential data assimilation method that
has been demonstrated to be effective for history matching reservoir production data and …

The Data Assimilation Research Testbed (DART) is an open-source community facility for
data assimilation education, research, and development. DART's ensemble data …

This article provides a fundamental theoretical basis for understanding EnKF and serves as
a useful text for future users. Data assimilation and parameter-estimation problems are …

Drought is one of the likely consequences of climate change in many regions of the world.
Together with an increased demand for water resources to supply the world's growing …