Data assimilation (DA) and uncertainty quantification (UQ) are extensively used in analysing
and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical …

The outstanding breakthroughs of deep learning in computer vision and natural language
processing have been the horn of plenty for many recent developments in the climate …

This report provides a summary of the main outcomes of the 3rd edition of the workshop on
Machine Learning (ML) for Earth System Observation and Prediction (ESOP/ML4ESOP) co …

Satellite altimetry offers a unique approach for direct sea surface current observation, but it is
limited to measuring the surface‐constrained geostrophic component. Ageostrophic …

Deep learning is widely used to predict complex dynamical systems in many scientific and
engineering areas. However, the black-box nature of these deep learning models presents …

A new knowledge-based and machine learning hybrid modeling approach, called
conditional Gaussian neural stochastic differential equation (CGNSDE), is developed to …

Data Assimilation is the process in which we improve the representation of the state of a
physical system by combining information coming from a numerical model, real-world …