Delivering accurate weather forecasts to drive better business decisions
Belgingur has developed a versatile forecasting framework which can be optimized for even the most demanding conditions. Combining ensemble 3D/4D-variational and observation nudging data assimilation methods, along with novel machine learning methods for data post-processing, we can offer forecast solutions tailored to the varied needs of our customers.
Our solutions
For over two decades Belgingur has been dedicated to research in meteorology with special emphasis on numerical simulations of the effects of orography on atmospheric flow.
Operational weather forecasts
Belgingur has created a novel weather forecasting framework, called Weather On Demand – WOD, that is deployable in the cloud and on in-house hardware and which can be customized for any location world-wide at a very short notice.
Re-analysis of past weather
Atmospheric models can not only be used to create weather forecasts but also to give us a better understanding of past weather patterns. This can be achieved by a method called dynamical downscaling.
Weather On Demand
Belgingur has created a novel weather forecasting framework, called Weather On Demand – WOD, that is deployable in the cloud and on in-house hardware and which can be customized for any location world-wide at a very short notice.
Latest stories
Comparisons of observed and simulated weather
GenCast – AI meets ensemble forecasting
Recently released GenCast model has made its way into traditional media. While it's not the first successful AI model to emerge in the recent years, it stands out for its extraordinary accuracy and its innovative approach to ensemble ...
