Precision weather forecasting to reduce energy forecast errors.

15-minute temporal resolution. 1-km spatial resolution. 48-hour lead time.
Reduce energy prediction errors, minimise imbalance costs, and optimise performance with high-resolution forecasting technology designed for renewable energy traders, producers, and grid operators.

Precision weather forecasting at 1 km and 200-meter resolution, anywhere on Earth.

Configure

Define the geographical domain for your simulation and choose from spatial resolutions of 9 km, 1 km, or 200 meters to match the level of details required for your solar or wind power model.

Peer-reviewed, authoritative models.

global scale

ECMWF

The ECMWF (European Centre for Medium-Range Weather Forecasts) provides large-scale boundary condition inputs, which are necessary for establishing the initial and boundary conditions for the Meso-NH model. This integration helps ensure that our simulations reflect real-world data, leading to more accurate modeling of regional weather phenomena.

synoptic scale

Meso-NH

Meso-NH [1] is the research-focused limited-area model designed to simulate small-scale meteorological phenomena, including turbulence, convection, microphysics, cloud formation, radiation, wildfire propagation, and dust aerosols.

fine scale

Weatherwise

We offer on-demand weather simulations that accurately resolve processes at the kilometer scale, down to a 200-meter resolution globally. Our approach allows for the configuration, execution, and scaling of the model to simulation local atmospheric processes and small-scale hazards with high fidelity.

Using an operational model physics.

Peer-reviewed

Meso-NH's [1] physics module is integrated into the French operational weather model AROME, demonstrating effective performance in operational conditions, and has been cited in over 1,000 publications.

High-performance

Our automated processing chain enables the execution of multiple simulations in parallel, allowing for the generation of a full year's worth of data in under a week.

On-demand

Our user-friendly interface simplifies the simulation setup process, making it easier for practitioners to navigate. It allows for clear domain selection, horizontal spatial resolution, and time period selection.

Supporting the renewable energy and AI industries

Energy forecasting

We deliver high-resolution weather data enabling 15–30 minute interval forecasts for renewable energy output. By combining weather inputs with site-specific parameters—such as panel specs and inverter efficiency—clients generate kWh forecasts with lower error margins.

Financial impact

Renewable prediction errors of 10–20% often result in avoidable costs. We aim to reduce this to less than 10%, helping energy producers improve planning and reduce financial exposure.

Grid integration

More accurate forecasts support better grid coordination and operational decisions. This helps reduce imbalance costs and improves alignment between production and demand.