Supported Weather Models

Statistically post-processed blend that calibrates many guidance sources into one reliable forecast. This entry is the CONUS core grid. Strong baseline for threshold decisions in energy, emergency management and public works.

NBM core grid for Alaska. Same calibrated blend as CONUS, exposed as a separate dataset code with its own native grid.

NBM core grid for Hawaii. Ideal for island-scale forecasts without reprojecting CONUS output or clipping global grids.

NBM core grid for Puerto Rico. Use for tropical weather monitoring, energy load forecasting, and high-resolution island extraction.

NBM core grid for Guam. Great for tropical cyclone season workflows and high-resolution local extraction in the western Pacific.

NBM oceanic core grid with coarse resolution optimized for marine and wide-area workflows. Exposed as a separate dataset with its own native grid.

Quantile-mapped deterministic branch of the operational CONUS NBM. Useful when a workflow needs calibrated deterministic fields alongside the NBM core and probabilistic products.

Experimental public parallel feed for NBM v5 on the CONUS core grid. Only the last 5 days are retained for side-by-side validation against operational NBM.

Experimental Alaska core grid for the public NBM v5 parallel feed, with only the last 5 days retained for comparison workflows.

Experimental Hawaii core grid for the public NBM v5 parallel feed, with only the last 5 days retained for comparison against operational Hawaii guidance.

Experimental Puerto Rico core grid for the public NBM v5 parallel feed, with only the last 5 days retained for tropical and coastal validation against operations.

Experimental Guam core grid for the public NBM v5 parallel feed, with only the last 5 days retained for western Pacific comparison work.

Experimental Oceanic core grid for the public NBM v5 parallel feed, with only the last 5 days retained for marine validation against operational NBM Oceanic.

Experimental parallel QMD feed for NBM v5, with only the last 5 days retained for CONUS-side comparison against the operational QMD product.

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.

15-minute cadence near-real-time surface analysis on the 2.5 km CONUS NDFD grid. Designed for intrahour monitoring, ramp detection, operational QA, and high-frequency verification where hourly actuals are too coarse.

Climatologically calibrated one-hour precipitation analysis on the CONUS NDGD 2.5 km grid. Useful for QPF verification, hydrology, event reconstruction, and precipitation truth fields.

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.

Global data-assimilation analysis that underpins the GFS initial conditions. Useful for near-real-time “what happened” fields, verification, and short lead-time baselines. Complements GFS by focusing on the analysis cycle.

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.

NOAA aviation turbulence diagnostics for CONUS, including eddy dissipation, clear-air turbulence, mountain-wave turbulence, and convectively induced turbulence guidance on a 3 km grid.

CONUS in-flight icing probability, severity, and supercooled large droplet potential guidance for route-aware aviation weather applications.

Alaska in-flight icing probability, severity, and supercooled large droplet potential guidance on a 3 km polar stereographic grid.

One-hour thunderstorm probability guidance from SPC post-processed HREF output. Built for short-fuse lightning-aware operations, event safety, utilities, and aviation ground workflows.

Four-hour thunderstorm probability layer for planning windows where convective risk matters more than exact minute-by-minute initiation timing.

Lightning-density probability guidance for outdoor safety, venue operations, aviation ramps, and utility workflows where nearby lightning is the trigger.

Calibrated hail probability guidance for severe-weather dashboards, agriculture, insurance exposure, rooftop solar, and fleet protection workflows.

Calibrated tornado probability field for severe-weather situational awareness, emergency-management triage, and risk scoring ahead of warnings.

Calibrated damaging convective-wind probability guidance for utilities, transportation, event safety, emergency management, and logistics workflows.

Taiwan Central Weather Administration regional WRF guidance over East Asia and the western Pacific. A useful regional companion to global models for typhoon-region, maritime, aviation, energy, and logistics applications.

12 km North American Mesoscale (NAM) CONUS guidance covering the gap between global flow and storm-scale refresh models. Useful when GFS is too coarse and HRRR is too local or too short, especially for regional temperature, wind, moisture, and precipitation structure.

12 km North American Mesoscale (NAM) CONUS slice on the same native grid as namawphys, but with a much richer surface, soil, column, radiative, and canopy diagnostic set. Best companion when you want more than the upper-air focused awphys stream.

3 km convection-allowing North American Mesoscale (NAM) nest for CONUS. This is the highest-resolution fixed-domain NAM stream and the closest physics-based counterpart to HRRR when you want a longer mesoscale horizon out to 60 hours.

GOES-like simulated brightness temperatures on the 12 km North American Mesoscale (NAM) CONUS grid. Specialized, but useful for cloud-top, moisture plume, and satellite-analogue workflows without leaving the NAM family.

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.

High-frequency HRRR surface output at 15-minute valid times. Built for intraday ramps: wind and solar power, aviation winds/ceilings, and fast-evolving convection signals in the next few hours.

CONUS RRFS pressure-level fields for storm-scale upper-air analysis: temperature, wind, humidity, geopotential height, vertical motion, vorticity, and related isobaric-level forecast variables.

CONUS RRFS 2D fields for surface weather, near-surface wind and temperature, precipitation, clouds, radiation, soil state, fire-weather signals, and severe-storm diagnostics.

RRFS ensemble guidance for storm-scale uncertainty, probability thresholds, severe-weather risk, aviation hazards, heavy precipitation, winter weather, and ML-ready ensemble features.

Operational NOAA/NCEP GraphCast-based surface forecast fields available from the NOAA EAGLE AWS Open Data bucket. Covers 10 m wind, 2 m temperature, mean sea-level pressure, and precipitation on a 0.25 degree global grid.

Operational NOAA/NCEP GraphCast-based pressure-level fields available from the NOAA EAGLE AWS Open Data bucket. Provides height, temperature, humidity, wind, and vertical velocity at standard pressure levels.

NOAA/NCEP 31-member GraphCast-based AI ensemble surface fields from the NOAA EAGLE AWS Open Data bucket. Provides member-level wind, temperature, humidity, pressure, and precipitation.

NOAA/NCEP 31-member GraphCast-based AI ensemble pressure-level fields from the NOAA EAGLE AWS Open Data bucket. Provides member-level height, temperature, humidity, wind, and vertical velocity.

Historical GraphCastGFS archive for AI-vs-physics comparison and backtesting. GribStream currently offers this experimental NOAA/Google feed through the 2026-05-05 00 UTC run; use AIGFS or AIGEFS for current NOAA AI guidance.

Historical FourCastNetGFS archive for AI-model comparison and backtesting. GribStream currently offers this experimental NOAA/NVIDIA feed through the 2026-03-01 12 UTC run; use AIGFS or AIGEFS for current NOAA AI guidance.

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.

Global ultraviolet exposure guidance for public-health, recreation, tourism, outdoor labor, school sports, and solar-exposure analytics.

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.

Climate-oriented global assimilation fields on a 1° grid. Useful for retrospective baselines, anomaly studies and large-scale machine-learning inputs. Complements CFS by providing analysis-first context.

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.