WeatherNext models

WeatherNext is a family of global, medium-range atmospheric models developed by Google DeepMind and Google Research, leveraging machine learning to significantly improve forecast accuracy and efficiency.

We have released two generations of WeatherNext models:

WeatherNext 2:Our state-of-the-art weather model that improves upon WeatherNext 1 with improved temporal resolution and better accuracy.
WeatherNext 1:Represents our original Graph and Gen models, which have been shown to be more skillful than ECMWF's HRES and ENS models.

We recommend starting with WeatherNext 2 for all new projects. It is our state-of-the-art model; WeatherNext 2 surpasses WeatherNext Gen on 99.9% of variables (e.g. temperature, wind, humidity) and lead times (0-15 days). The WeatherNext 1 models are considered legacy but remain available as a valuable reference and for users who need to compare results against our original published research.

You can learn more about core WeatherNext use cases on the Use Cases page .

WeatherNext 1

WeatherNext 2

WeatherNext Graph

WeatherNext Gen

Historical Data Coverage

2020 - present

2022 - present

Architecture

Graph Neural Network (GNN) implemented as a "encoder-processor-decoder" system

Conditional Diffusion model incorporating GNN coupled with graph transformer

Functional Generative Network (FGN) uses a graph transformer framework optimized with noisy weights

Spatial Resolution

0.25° (~30km at the equator)

0.25°

Temporal Resolution

6 hours

12 hours

6 hours
See Vertex AI for access to 1hr timestep experimental capabilities

Forecast Initialization Frequency Times (UTC)

Every 6 hours (00, 06, 12, 18 UTC)

Lead Times (Forecast Horizon)

10 days

15 days

Locations

Global

Training data

ERA5 /HRES-fc0

Initialization Inputs for Generating Forecasts

HRES-fc0

Forecast Type

Deterministic forecast

Ensemble forecast (50)

Ensemble forecast (64)

Variables

Atmospheric:

Geopotential
Specific humidity
Temperature
U component of wind
V component of wind
Vertical velocity
Each at pressure levels: 50, 100, 150, 200, 250, 300, 400, 500, 600, 700, 850, 925, 1000 hPa

Surface:

2 metre temperature
10 metre u wind component
10 metre v wind component
Mean sea level pressure
Total precipitation

Atmospheric:

Geopotential
Specific humidity
Temperature
U component of wind
V component of wind
Vertical velocity
Each at pressure levels: 50, 100, 150, 200, 250, 300, 400, 500, 600, 700, 850, 925, 1000 hPa

Surface:

2 metre temperature
10 metre u wind component
10 metre v wind component
100 metre u wind component
100 metre v wind component
Mean sea level pressure
Total precipitation
Sea surface temperature

Atmospheric:

Geopotential
Specific humidity
Temperature
U component of wind
V component of wind
Vertical velocity
Each at pressure levels: 50, 100, 150, 200, 250, 300, 400, 500, 600, 700, 850, 925, 1000 hPa

Surface:

2 metre temperature
10 metre u wind component
10 metre v wind component
100 metre u wind component
100 metre v wind component
Mean sea level pressure
Total precipitation
Sea surface temperature

See Glossary for more information on terms.

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WeatherNext models