1 citations · 3 across the 5 of their papers we have counts for
5 papers
Learning Accurate Storm-Scale Evolution from Observations
Jaideep Pathak, Mohammad Shoaib Abbas, Peter Harrington +10
Accurate short-term prediction of clouds and precipitation is critical for severe weather warnings, aviation safety, and renewable energy operations. Forecasts at this timescale ar…
Data-driven solar forecasting enables near-optimal economic decisions
Zhixiang Dai, Minghao Yin, Xuanhong Chen +27
Solar energy adoption is critical to achieving net-zero emissions. However, it remains difficult for many industrial and commercial actors to decide on whether they should adopt di…
Data-driven Surface Solar Irradiance Estimation using Neural Operators at Global Scale
Alberto Carpentieri, Jussi Leinonen, Jeff Adie +3
Accurate surface solar irradiance (SSI) forecasting is essential for optimizing renewable energy systems, particularly in the context of long-term energy planning on a global scale…
Modulated Adaptive Fourier Neural Operators for Temporal Interpolation of Weather Forecasts
Jussi Leinonen, Boris Bonev, Thorsten Kurth +1
Weather and climate data are often available at limited temporal resolution, either due to storage limitations, or in the case of weather forecast models based on deep learning, th…
Extending intraday solar forecast horizons with deep generative models
Alberto Carpentieri, Doris Folini, Jussi Leinonen +1
Surface solar irradiance (SSI) plays a crucial role in tackling climate change - as an abundant, non-fossil energy source, exploited primarily via photovoltaic (PV) energy producti…