Train your AI weather models with physics-based data.

Weatherwise specializes in high-resolution regional weather simulations, down to 400-meter resolution. Our team of meteorologists and engineers creates weather data products designed to enhance the training of your AI models with realistic weather scenarios.

Configure and run weather simulation at 400-meter resolution globally.

Define the geographical domain for your simulation and choose from spatial resolutions of 10 km, 2 km, or 400 meters to match the level of details required for your AI weather model.

Our goal is to help you access physics-model output in a few hours. Most of our efforts are dedicated to optimise how our weather model runs on parallel computing resources without any downtime.

Track computing status in real-time on a dedicated dashboard. Once the simulation is done running, you can visualise its outputs online and download NetCDF data archive.

The leading physics-based data product for training AI weather models.

global scale

GFS

The Global Forecast System (GFS) 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 400-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.

A focus on performance andexperience.

Peer-reviewed model

Meso-NH [1] is the research model we use to simulate meteorological events. It has been cited in over 1,000 publications, supporting its importance in the meteorological community.

Its physics module is integrated into the French operational weather model, demonstrating effective performance in operational conditions.

High-performance

A 24-hour simulation at 400-meter resolution over a 120 km x 120 km domain takes approximately 3 hours to complete.

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.

Additionally, the ability to specify 2D and 3D output enhances the effectiveness of training for your AI models.