From the 1 of 6 linked papers with an AI index.
6 papers
Skillful forecasting of offshore winds from satellite scatterometer constellations
Francesco Pinto, Luca Lanzilao, Paco Lopez Dekker +1
The paper introduces WindCastNet, a deep‑learning framework that directly uses irregular satellite scatterometer observations to nowcast offshore wind speed and direction, achievin…
Spatiotemporal downscaling and nowcasting of urban land surface temperatures with deep neural networks
Solomiia Kurchaba, Angela Meyer
Land Surface Temperature (LST) is a key variable for various applications, such as urban climate and ecology studies. Yet, existing satellite-derived LST products provide either hi…
NeuroDDAF: Neural Dynamic Diffusion-Advection Fields with Evidential Fusion for Air Quality Forecasting
Prasanjit Dey, Soumyabrata Dev, Angela Meyer +1
Accurate air quality forecasting is crucial for protecting public health and guiding environmental policy, yet it remains challenging due to nonlinear spatiotemporal dynamics, wind…
Characterization and forecasting of national-scale solar power ramp events
Luca Lanzilao, Angela Meyer
The rapid growth of solar energy is reshaping power system operations and increasing the complexity of grid management. As photovoltaic (PV) capacity expands, short-term fluctuatio…
Intraday spatiotemporal PV power prediction at national scale using satellite-based solar forecast models
Luca Lanzilao, Angela Meyer
We present a novel framework for spatiotemporal photovoltaic (PV) power forecasting and use it to evaluate the reliability, sharpness, and overall performance of seven intraday PV…
Surface solar radiation: AI satellite retrieval can outperform Heliosat and generalizes well to other climate zones
K. R. Schuurman, A. Meyer
Accurate estimates of surface solar irradiance (SSI) are essential for solar resource assessments and solar energy forecasts in grid integration and building control applications.…