StormGeo employs highly qualified and experienced scientific staff
StormGeo’s high-resolution, in-house modeling, when combined with global models, provides the foundation to deliver the best possible products in the market.
Since its inception, StormGeo Group has invested 20% of its revenues in research and development with the goal of providing the most accurate weather forecasts and decision support solutions for our customers. Our highly qualified and experienced scientific staff conducts research in meteorology, oceanography and technology in an effort to continually improve our products and set best practices in the industry.
StormGeo focuses on quality, timeliness, and dependable deliverables to our customers. The R&D team comprises one sixth of all StormGeo employees and of these, 20% hold a PhD. Our scientific staff includes over 170 operational meteorologists operating seven, 24/7 forecasting centers worldwide, ensures high quality products and services to our customers.
The driving force of the R&D team is innovation—to continually improve weather forecasts—by providing StormGeo Group “Best Data“ for our customers. StormGeo’s Best Data is based on external and in-house model data combined with advanced post-processing and statistical methods.
To provide the best possible products and services to our customers, StormGeo utilizes the full model suites of the most accurate medium and long-range global numerical weather prediction models, including the European Centre for Medium-Range Weather Forecasts (ECMWF) and Global Forecast System (GFS), as well as high-resolution short-range models, such as the High Resolution Rapid Refresh model. The experienced meteorologists at our forecasting centers understand the strengths and weaknesses of each model, utilize the operational and ensemble model runs as part of the overall forecast process, and this results in the most accurate forecast.
The ECMWF and GFS are considered to be the world's most consistent and accurate global numerical weather prediction models on objective reports measuring several atmospheric variables, such as pressure, wind, temperature and precipitation. Our meteorologists have the tools to evaluate all available information to provide high-quality, customer-specific forecasts.
Both the ECMWF and GFS models have ensemble model runs that are used extensively within the StormGeo product portfolio for probability forecasting and to highlight uncertainties. The ensemble model runs are lower resolution with slight variations to their initial atmospheric boundary conditions. They show a range of possibilities beyond the operational model run. These ensembles provide alternative outcomes to the operational model run and are invaluable in areas of the world where sparse surface and upper air observations are incorporated into the models, or where the assumed initial boundary conditions are incorrect.
Global numerical models do not always have high enough resolution to accurately forecast fine-scale weather phenomena in areas with complex topography or limited weather observations. In order to provide accurate site-specific forecasts and decision guidance for our clients’ sensitive operations, StormGeo provides customized in-house modeling. We run limited area atmospheric and oceanic models for smaller and larger regional domains. The models are:
These models are currently being used to strengthen the quality of the day-to-day weather forecasts with a focus on improving quality over the existing model systems. The WRF model is also used to provide extremely high-resolution wind and energy forecasts. This is done by nesting the global ECMWF down to a resolution of 1km between the grid points where weather is calculated. This gives a considerably better representation of land/sea contrasts and complex topography.
We also run advanced models for oil spill, vessel response and marine operations. They include:
The team of researchers at StormGeo works to continuously improve statistical analyses and can provide a variety of state-of-the-art analyses to the market. This includes: