Data assimilation plays a dual role in advancing the “scientific” understanding and serving
as an “engineering tool” for the Earth system sciences. Land data assimilation (LDA) has …

Operational numerical weather prediction systems consist of three fundamental
components: the global observing system for data collection, data assimilation for …

The forecasting skill of numerical weather prediction (NWP) models critically depends on the
accurate initial conditions, also known as analysis, provided by data assimilation (DA) …

Data assimilation (DA) is a powerful technique for improving the forecast accuracy of
dynamic systems by optimally integrating model forecasts with observations. Traditional DA …

Fitting nonlinear dynamical models to sparse and noisy observations is fundamentally
challenging. Identifying dynamics requires data assimilation (DA) to estimate system states …

Significant Wave Height (SWH) is a crucial parameter in oceanographic research, essential
for understanding various marine and atmospheric processes. Traditional methods for …

Recent advancements in Artificial Intelligence (AI) have led to the development of several
Large Weather Models (LWMs) that rival State-Of-The-Art (SOTA) Numerical Weather …

In the field of numerical weather prediction, fine-grained precipitation fields play a crucial
role in forecasting and analyzing the spatial distribution and intensity of the precipitation …

Weather forecasting traditionally relies on numerical weather prediction (NWP) systems that
integrates global observational systems, data assimilation (DA), and forecasting models …

Advances in data assimilation (DA) methods have greatly improved the accuracy of Earth
system predictions. To fuse multi-source data and reconstruct the nonlinear evolution …