164 citations · 236 across the 6 of their papers we have counts for
6 papers
The rise of data-driven weather forecasting
Zied Ben-Bouallegue, Mariana C A Clare, Linus Magnusson +14
Data-driven modeling based on machine learning (ML) is showing enormous potential for weather forecasting. Rapid progress has been made with impressive results for some application…
Accelerated wind farm yaw and layout optimisation with multi-fidelity deep transfer learning wake models
Sokratis Anagnostopoulos, Jens Bauer, Mariana C. A. Clare +1
Wind farm modelling has been an area of rapidly increasing interest with numerous analytical as well as computational-based approaches developed to extend the margins of wind farm…
Improving medium-range ensemble weather forecasts with hierarchical ensemble transformers
Zied Ben-Bouallegue, Jonathan A Weyn, Mariana C A Clare +3
Statistical post-processing of global ensemble weather forecasts is revisited by leveraging recent developments in machine learning. Verification of past forecasts is exploited to…
An unsupervised learning approach for predicting wind farm power and downstream wakes using weather patterns
Mariana C A Clare, Simon C Warder, Robert Neal +2
Wind energy resource assessment typically requires numerical models, but such models are too computationally intensive to consider multi-year timescales. Increasingly, unsupervised…
Bayesian neural networks for the probabilistic forecasting of wind direction and speed using ocean data
Mariana C A Clare, Matthew D Piggott
Neural networks are increasingly being used in a variety of settings to predict wind direction and speed, two of the most important factors for estimating the potential power outpu…
Combining distribution-based neural networks to predict weather forecast probabilities
Mariana Clare, Omar Jamil, Cyril Morcrette
The success of deep learning techniques over the last decades has opened up a new avenue of research for weather forecasting. Here, we take the novel approach of using a neural net…