Power and energy supply drive our economy and way of life. There is a need to procure stable, low-cost energy across the world. Energy markets are governed by a variety of factors including demand, supply, geopolitics, and more. Energy demand is directly correlated with meteorological variables such as temperature and dew point. Thus, accurate forecasting at near to medium-term time scales is critical for accurate estimation of price and purchasing supplies.

With the rise and scale of renewable energy, variables such as wind and solar irradiation have become increasingly important to forecast. Existing forecasts, largely driven by Numerical Weather Prediction (NWP) methods have scope for improvement by using AI driven forecasts. However, they lack accuracy on longer horizons such as sub-seasonal to seasonal time scales. These inaccuracies are further exacerbated by the impacts of climate change which creates more anomalous behavior.