🌍 Weather Model Comparison

AIFS Single v2 (ECMWF) · WeatherNext 2 (Google DeepMind) · ERA5 climatology baseline

📋 Session Status

  • AIFS: ⬜ not run yet
  • WeatherNext2: ⬜ not run yet
  • Climatology (ERA5 baseline): ⬜ not run yet

⚙️ Run a Forecast

Model
AIFS runs on GPU (ZeroGPU); WeatherNext2 runs on CPU (~96s/step — needs ~50GB RAM/first-load, more than this Space's default GPU allocation); Climatology is a zero-skill baseline for comparison, not a real model.
Number of steps (6h each)
Initial conditions (AIFS only)
Historical dates pull from ECMWF's deeper S3 archive (from 2023-01-18) instead of the live feed.
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🗺️ Visualize

Model
Step
Field

📂 Saved Runs

Forecasts saved above persist in the weather-forecast-archive dataset — load one back here to plot/compare it without re-running the model.

Saved run

📊 Compare Two Models

Pick any two model runs (including two steps of the same model) and a field — shows both maps, their difference, and a skill metric (RMSE, MAE, bias, correlation). AIFS's irregular grid is compared by sampling the other model onto AIFS's own points; WeatherNext2 and the climatology baseline share an identical grid, so no resampling is needed between them.

Model A
Step A
Model B
Step B
Field

Notes

  • AIFS: no flash-attn required (PyTorch SDPA — works on CPU, MPS, CUDA). First run downloads its ~2GB checkpoint.
  • WeatherNext2: runs via an unmerged transformers fork; CPU-only here, ~96s/step once loaded.
  • Climatology baseline: pure ERA5 climatological mean per step — zero model skill by construction, a reference point for judging whether AIFS/WeatherNext2 add value.
  • Data: ECMWF Open Data (forecasts) and EarthMover's public ERA5 archive (climatology).