Weather Forecasting
GeoRetina AI provides access to cutting-edge weather forecasting capabilities using Google DeepMind's WeatherNext Graph dataset, the most advanced AI-based weather forecasting technology available. WeatherNext Graph generates global medium-range weather forecasts using DeepMind's graphical neural network weather model, providing superior accuracy and comprehensive atmospheric data.
What is WeatherNext Graph?
WeatherNext Graph is Google DeepMind's experimental global weather forecasting dataset produced by an operational version of their graphical neural network weather model (formerly known as GraphCast). Unlike traditional physics-based models, WeatherNext Graph uses advanced machine learning to generate accurate global medium-range weather forecasts with comprehensive atmospheric and surface variables.
Key Technical Specifications
• Spatial resolution: 0.25° global (~27.75 km) • Temporal resolution: 6‑hour steps (init + lead times) • Lead time: up to 10 days • Update frequency: 4×/day (00z, 06z, 12z, 18z UTC) • Coverage: global with comprehensive atmospheric levels • Availability: 2020‑01‑01 → present (real‑time + historical)
Why WeatherNext Graph is Superior
Why It’s Better (in 6 bullets)
- AI speed & reliability: faster than physics‑based models with better skill.
- 69+ variables: surface + 13 atmospheric levels (50–1000 hPa).
- Multi‑level analysis: temp, humidity, wind, geopotential, vertical velocity.
- Surface conditions: 2m temperature, 10m wind, precipitation, MSLP.
- 6‑hour steps: detailed evolution out to 10 days.
- Uniform 0.25° grid: consistent global coverage.
Forecast Capabilities and Performance
Capabilities & Performance (at a glance)
• Comprehensive modeling: surface + 13 pressure levels (50–1000 hPa) • 6‑hour resolution across the full 10‑day horizon • Uniform 0.25° grid globally (~27.75 km pixels) • Handles regional and global‑scale patterns
Using WeatherNext Graph in GRAI
Simple Query Interface
Show me the 10-day weather forecast for this region
Analyze precipitation patterns for the next week in this area
Provide atmospheric pressure analysis for weather system tracking
Show wind patterns at different atmospheric levels
Atmospheric Analysis
• Multi‑level analysis: temperature, humidity, wind at 13 levels • Surface conditions: precipitation and sea‑level pressure • Vertical profiles: surface → 50 hPa • System tracking: movement and evolution
Workflow at a Glance
Example Use Cases
Show cyclone formation and tracking analysis for the next 10 days
Assess flood risk probability from precipitation forecasts
Show precipitation forecasts and atmospheric conditions for harvest planning
Provide temperature forecasts at multiple levels for frost risk assessment
Forecast wind power generation potential using multi‑level wind data
Provide comprehensive aviation weather forecasts
Other Use Cases
- Energy: wind/solar planning, demand forecasting, storm risk to infrastructure.
- Logistics: routing and delay avoidance for shipping, aviation, and ports.
- Climate Risk: infrastructure planning and insurance modeling with medium‑range trends.
Understanding WeatherNext Graph Forecasts
How to read the forecasts
• Surface + 13 pressure levels (1000 → 50 hPa) describe the full atmosphere • Updates every 6 hours across a 10‑day horizon • Uniform 0.25° grid = consistent global coverage • AI model outperforms traditional physics‑based models
Integration and Access
- Real‑time forecasts within ~48 hours (Real‑Time Experimental).
- Historical archive back to 2020 (Historic Experimental).
- Direct access via Google Earth Engine.
- Updated 4× daily (00z, 06z, 12z, 18z).
Getting Started
- Define your location (ROI or region).
- Ask for forecasts in natural language.
- Review multi‑level outputs (surface + aloft).
- Make decisions using the 10‑day outlook.
Example Queries
Start with these natural language requests:
Show me the 10-day weather forecast for this region using WeatherNext Graph data
Analyze atmospheric conditions for severe weather potential
Provide multi-level wind analysis for this coastal area
Show temperature and precipitation patterns for agricultural planning
GRAI integrates WeatherNext Graph seamlessly with other geospatial analyses, enabling comprehensive environmental assessments that combine Google DeepMind's advanced weather forecasting with satellite imagery, land cover analysis, and other earth observation data.