FCN3

GlobalMRF202580 GBNVIDIAPyTorch

Import path: earth2studio.models.px.FCN3

View source on GitHub View install commands

Documentation

Bases: Module, AutoModelMixin, PrognosticMixin

FourCastNet 3 advances global weather modeling by implementing a scalable, geometric machine learning (ML) approach to probabilistic ensemble forecasting. The approach is designed to respect spherical geometry and to accurately model the spatially correlated probabilistic nature of the problem, resulting in stable spectra and realistic dynamics across multiple scales.

FourCastNet 3 is a global probabilistic prognostic model. It operates on a 0.25 degree lat-lon grid (south-pole excluding) equirectangular grid with 72 variables.

Note

For more information see the following references:

• arxiv.org/abs/2507.12144v2
• arxiv.org/abs/2402.16845
• huggingface.co/nvidia/fourcastnet3
• catalog.ngc.nvidia.com/orgs/nvidia/teams/earth-2/models/fourcastnet3

Parameters:

• core_model (Module) –

  Core PyTorch model with loaded weights

• variables (array, default: array(VARIABLES) ) –

  Variables associated with model, by default 72 variable model.

• seed (int, default: 333 ) –

  Seed of the underlying FCN3 model's random generators, by default 333

__call__

__call__(
    x: Tensor, coords: CoordSystem
) -> tuple[Tensor, CoordSystem]

Runs prognostic model 1 step

Parameters:

• x (Tensor) –

  Input tensor

• coords (CoordSystem) –

  Input coordinate system

Returns:

• tuple[Tensor, CoordSystem] –

  Output tensor and coordinate system

create_iterator

create_iterator(
    x: Tensor, coords: CoordSystem
) -> Iterator[tuple[Tensor, CoordSystem]]

Creates a iterator which can be used to perform time-integration of the prognostic model. Will return the initial condition first (0th step).

Parameters:

• x (Tensor) –

  Input tensor

• coords (CoordSystem) –

  Input coordinate system

Yields:

• Iterator[tuple[Tensor, CoordSystem]] –

  Iterator that generates time-steps of the prognostic model container the output data tensor and coordinate system dictionary.

load_default_package classmethod

load_default_package() -> Package

Load prognostic package

load_model classmethod

load_model(
    package: Package, variables: list = VARIABLES
) -> PrognosticModel

Load prognostic from package

Parameters:

• package (Package) –

  Package to load model from

• variables (list, default: VARIABLES ) –

  Model variable override, by default VARIABLES for FCN3 72 channel

Returns:

• PrognosticModel –

  Prognostic model