Pelmorex has officially announced the launch of its latest innovation in Gaia Energy, which happens to be a cutting-edge predictive weather forecasting solution developed for energy traders.
According to certain reports, Gaia Energy arrives on the scene with a vision to revolutionize weather predictions and analysis across the natural gas, electricity, agriculture, and weather derivatives space.
More on the same would reveal how the stated solution is actually based upon Pelmorex’s proprietary Deep Learning Numerical Weather Prediction (DLNWP) model capable of providing advanced predictive modeling, real-time weather insights, historical weather data, and customizable data visualizations. By doing so, the model in question is able to help energy traders make informed and strategic trading decisions at a much faster clip.
Developed in close collaboration with energy industry specialists, Gaia Energy delivers its forecasts 18 times faster, all while boasting greater accuracy than world’s top conventional models. In fact, such is its speed that the solution will let energy traders access weather insights an hour ahead of the market.
“This is a revolution in how weather forecasts are made. Instead of using traditional methods that are based on the laws of physics, our model learns from observed weather data, producing more accurate forecasts and eliminating the consistent errors found in traditional models,” said Chris Scott, Chief Meteorologist at Pelmorex Corp.
We referred to the solution’s accuracy, but what we haven’t mentioned yet is how it provides that as the first ever commercially available AI-based weather forecasting product focused on driving outcomes in energy markets.
Now given the speed and accuracy, Gaia Energy also puts on the offer substantial profit potential, considering the way it can unlock for energy traders a clear competitive edge.
“Our Gaia forecast model is a perfect example of what talented and collaborating teams from meteorology and data science can build together by leveraging new and powerful AI methodologies. While conventional physics based models are impressive with their intricate modeling of atmospheric dynamics, these models also tend to grow forecast error very quickly. What we are seeing with our Gaia DLNWP based model is that this error is more suppressed, leading to more accurate forecasts,” said Mark Gibbas, Managing Director, B2B Enterprise Solutions, Pelmorex Corp.
Another detail worth a mention here is rooted in solution’s pledge to constantly learn using ten million plus gridded forecast data sets that span over four decades to provide long-term predictive power. Complimenting that is Gaia Energy’s intuitive design and user-friendly interface which makes accessing and interpreting complex weather data a seamless experience. By doing so, it ensures that users can leverage the full potential of its capabilities.
Founded in 1989, Pelmorex’s rise up the ranks stems from being an international weather information and data management company. To give you a gist of the company’s stature, we must acknowledge the fact that, at present, it owns popular brands like The Weather Network, MétéoMédia, Eltiempo.es, Clima, Otempo.pt, and Weather Source.
“The process of bringing this project to completion has been a humbling experience. It took a substantial amount of brain power to develop and train this model from scratch, in a distributed environment with an enormous amount of data, while providing operational support,” said Jonathan Weisbaum, Director of Meteorological Engineering at Pelmorex Corp. “We’ve got the best engineers and scientists in the world, and it shows in the model’s forecasting skill and inference speed.”
