earth2studio

Quick start

Running AI weather prediction can be done with just a few lines of code.

• For detailed installation steps, including model-specific installations, see the [install guide][e2studio_install_url].
• See the [examples][e2studio_examples_url] gallery providing different inference workflow samples.
• Swap out [data sources][e2studio_data_api] or [models][e2studio_px_api] depending on your use case!

Tutorial

Agent-assisted setup

Automate setup with your preferred coding agent using NVIDIA Earth2Studio skills. Install the Earth2Studio skill set, then ask your favorite agent (Claude, Codex, OpenCode, etc) to recommend a model, configure an environment, or run a first deterministic forecast. Find more Earth2Studio skills in the NVIDIA Skills catalog.

npx skills add NVIDIA/skills --skill earth2studio-install
npx skills add NVIDIA/skills --skill earth2studio-discover
npx skills add NVIDIA/skills --skill earth2studio-data-fetch
npx skills add NVIDIA/skills --skill earth2studio-deterministic-forecast

Example agent prompts:

Use the Earth2Studio discover skill to recommend a starter forecast workflow.
Use the Earth2Studio install skill to set up my environment for FourCastNet3 inference.
Create a script to fetch ERA5 surface winds data for March 2024.
Create a deterministic forecast workflow with GFS, FourCastNet3, and a Zarr output store.

NVIDIA FourCastNet3

from earth2studio.models.px import FCN3
from earth2studio.data import GFS
from earth2studio.io import ZarrBackend
from earth2studio.run import deterministic as run

model = FCN3.load_model(FCN3.load_default_package())
data = GFS()
io = ZarrBackend("outputs/fcn3_forecast.zarr")
run(["2025-01-01T00:00:00"], 10, model, data, io)

ECMWF AIFS

from earth2studio.models.px import AIFS
from earth2studio.data import IFS
from earth2studio.io import ZarrBackend
from earth2studio.run import deterministic as run

model = AIFS.load_model(AIFS.load_default_package())
data = IFS()
io = ZarrBackend("outputs/aifs_forecast.zarr")
run(["2025-01-01T00:00:00"], 10, model, data, io)

Google Graphcast

from earth2studio.models.px import GraphCastOperational
from earth2studio.data import GFS
from earth2studio.io import ZarrBackend
from earth2studio.run import deterministic as run

package = GraphCastOperational.load_default_package()
model = GraphCastOperational.load_model(package)
data = GFS()
io = ZarrBackend("outputs/graphcast_operational_forecast.zarr")
run(["2025-01-01T00:00:00"], 4, model, data, io)

[!IMPORTANT] Earth2Studio is an interface to third‑party models, checkpoints, and datasets. Licenses for these assets are owned by their providers. Ensure you have the rights to download, use, and (if applicable) redistribute each model and dataset. Links to the original license and source are often provided in the API docs for each model/data source.

Latest News

[!NOTE] As of version 0.14.0, Earth2Studio TOML default installs now target CUDA 13.