Supported Weather Models

Statistically post-processed blend that calibrates many guidance sources into one reliable forecast. Uses bias correction and quantile mapping to produce site-ready probabilities. Strong baseline for threshold decisions in energy, emergency management and public works.

Objective analysis that fuses dense surface observations with short-range guidance to create a best-estimate grid. Designed as analysis of record for verification and ML training. Ideal truth set for bias correction and backfilling missing data.

Near real-time surface analysis built with variational data assimilation. Ingests METAR networks and other sensors to map current conditions at high cadence. Best suited for monitoring, rapid QA and initializing very short-range systems.

Global numerical weather prediction using the FV3 dynamical core and modern physics suites. Serves as the backbone for synoptic guidance and boundary conditions. Widely used for aviation planning, long-range scenarios and downstream ensembles.

Hourly cycling short-range model tuned for mesoscale detail. Assimilates radar, aircraft and surface data to capture evolving boundaries and jets. A go-to for aviation operations and fast-changing weather in the next few hours.

Storm-resolving, convection-allowing configuration with hourly radar-informed cycling. Captures squall lines, outflow boundaries and sharp wind ramps. Favored for severe timing, road weather and renewable ramp forecasting.

Unified Forecast System at storm scale using the FV3 core with frequent cycling. Designed to succeed RAP and HRRR in a single modern system. Built for real-time hazard awareness, power operations and transportation planning.

Ensemble built on RRFS to express uncertainty at convective scales. Produces neighborhood probabilities for heavy rain and severe ingredients. Useful for risk communication and threshold-based triggers.

Graph neural network that advances the atmospheric state via message passing on a spherical mesh. Delivers medium-range skill with very low inference cost. Great for rapid ensembles and research workflows that need speed.

Fourier Neural Operator surrogate trained to emulate GFS fields. Produces forecasts in seconds while preserving large-scale flow patterns. Suited for large ensembles, sensitivity work and AI-assisted research.

Couples meteorology with aerosol composition to simulate dust, smoke and other species. Uses emissions and chemistry modules to predict transport and deposition. Supports visibility planning, health risk and dispersion studies.

Probabilistic wave guidance derived from an ensemble of wave simulations. Provides exceedance chances for heights and periods along routes and coasts. Used for offshore safety windows and marine risk management.

Ensemble mean that filters member noise to reveal persistent signals. Highlights pattern shifts and teleconnections for planning. A practical starting point before drilling into percentiles or clusters.

Set of perturbed atmospheric members that express forecast spread. Uses stochastic physics and initial-state perturbations to sample uncertainty. Essential for percentiles, clusters and scenario risk analysis.

Seasonal shortwave and longwave flux fields from a coupled ocean-atmosphere system. Useful for energy budget studies, agriculture and hydrology at multi-month horizons. Connects surface budgets to ENSO and MJO variability.

Seasonal pressure-level fields from the atmospheric component of CFS. Good for anomaly composites, stratospheric diagnostics and teleconnection studies. Supports aviation climatologies and hemispheric pattern analysis.

Fields on isentropic surfaces suited to transport and potential vorticity analyses. Reveals cross-tropopause exchange and jet dynamics on seasonal scales. Valuable for research, education and specialty diagnostics.

Ocean component of CFS providing temperature, currents and heat content. Captures basin-scale variability and subsurface structure. Applied to ENSO tracking and seasonal marine planning.

Deterministic forecast from ECMWF with advanced 4D-Var data assimilation. High skill on synoptic and planetary scales supports many industries. Often used as the anchor run in multi-model decision workflows.

Deterministic wave model tightly coupled to the atmosphere. Resolves swell propagation and locally forced seas for ports and offshore assets. Supports routing, safety windows and coastal hazard outlooks.

ECMWF ensemble prediction system for the medium range. Perturbs initial conditions and model tendencies to sample uncertainty. Trusted for probabilities, percentiles and cluster analysis.

Wave ensemble paired with the atmospheric EPS to quantify marine uncertainty. Delivers probabilities for crossing safe limits along routes and coasts. Used for risk envelopes, port logistics and offshore planning.

ECMWF’s AI forecast trained to reproduce IFS behavior at a fraction of the cost. Enables rapid cycles and wider what-if exploration without heavy compute. Complements physics models for medium-range tasks and decision support.

Ensemble of AIFS runs that provides fast probabilistic guidance. Good for low-cost spread estimates and sensitivity testing. Pairs well with traditional ensembles in hybrid workflows.