In recent years, interest has grown in modeling spatio-temporal data generated from
monitoring networks, satellite imaging, and climate models. Under Gaussianity, the …

Reasonable assessment of structural resistance degradation and reliability is the premise of
formulating targeted maintenance strategy of aging structures. In this paper, a Gamma …

The unprecedented scale and sophistication of wind turbine technologies call for wind
forecasts of high spatial resolution, ie turbine-tailored forecasts, to inform several operational …

Multivariate spatially oriented data sets are prevalent in the environmental and physical
sciences. Scientists seek to jointly model multiple variables, each indexed by a spatial …

The reliable integration of wind energy into modern-day electricity systems heavily relies on
accurate short-term wind forecasts. We propose a spatio-temporal model called AIRU-WRF …

Accurate short-term wind forecasts are instrumental to the optimal operation and
management of offshore wind farms. While there have been significant advancements in …

When analyzing the spatio-temporal dependence in most environmental and earth sciences
variables such as pollutant concentrations at different levels of the atmosphere, a special …

Joint modeling of spatially oriented dependent variables is commonplace in the
environmental sciences, where scientists seek to estimate the relationships among a set of …

Modelling multivariate spatio-temporal data with complex dependency structures is a
challenging task but can be simplified by assuming that the original variables are generated …

Understanding and predicting environmental phenomena often requires the construction of
spatio-temporal statistical models, which are typically Gaussian processes. A common …