The emergence of clear semantics for causal claims and of a sound logic for causal
reasoning is relatively recent, with the consolidation over the past decades of a coherent …

This paper has two interrelated foci:(i) obtaining stable and efficient data-driven closure
models by using a multivariate time series of partial observations from a large-dimensional …

Prediction of barrier‐island response to hurricane attack is important for assessing the
vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of …

As centralized wind power construction approaches saturation, the demand for
decentralized wind power in cities, enterprises, and village is gradually increasing. Unlike …

Hydrologic extremes often lead to droughts and floods that adversely affect the socio-
economic development. Change in the characteristics and causes of hydrologic extremes …

A new methodology for rigorous Bayesian learning of high-dimensional stochastic
dynamical models is developed. The methodology performs parallelized computation of …

Both governments and the private sector urgently require better estimates of the likely
incidence of extreme weather events, their impacts on food crop production and the potential …

Smoothers are increasingly used in geophysics. Several linear Gaussian algorithms exist,
and the general picture may appear somewhat confusing. This paper attempts to stand back …

Prediction of coastal processes, including waves, currents, and sediment transport, can be
obtained from a variety of detailed geophysical-process models with many simulations …

We describe a new approach that allows for systematic causal attribution of weather and
climate-related events, in near-real time. The method is designed so as to facilitate its …