Pith Number

pith:5HUPYUGZ

pith:2026:5HUPYUGZEQO62FBAJXDWXRIEF7

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SwAIther-Precip: Lead-Time-Aware Bias Correction Enables Kilometer-Scale Downscaling of Global AI Precipitation Forecasts over Switzerland

Dan Assouline, Daniele Nerini, Erwan Koch, Federico Amato, Filippo Quarenghi, Kyle van de Langemheen, Thibaut Loiseau, Tom Beucler

A lead-time-conditioned U-Net bias correction enables a diffusion model to produce kilometer-scale probabilistic precipitation forecasts from global AI outputs with 48% lower CRPS over Switzerland.

arxiv:2605.16163 v1 · 2026-05-15 · physics.ao-ph · cs.LG

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Claims

C1strongest claim

SwAIther-Precip reduces CRPS by 48% relative to raw AIFS forecasts and reproduces observed spatial variability with spectral fidelity above 0.85 at large scales and 0.88 at small scales, corresponding to an effective resolution of approximately 4 km on a 1 km grid for lead times up to 5 days.

C2weakest assumption

That a deterministic U-Net bias correction conditioned on lead time at coarse resolution is sufficient to allow a subsequent generative super-resolution model to be trained directly on observations without needing the full atmospheric state.

C3one line summary

SwAIther-Precip uses lead-time-conditioned U-Net bias correction followed by diffusion-based super-resolution to downscale AIFS forecasts, achieving 48% CRPS reduction and ~4 km effective resolution up to 5 days lead time.

References

67 extracted · 67 resolved · 2 Pith anchors

[1] Communications Earth & Environment , volume= 2025

[2] Proceedings of the AAAI conference on artificial intelligence , volume=

[3] Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

[4] arXiv preprint arXiv:2410.07472 , year=

[5] Atmospheric Science Letters , volume= 2025

Receipt and verification

First computed	2026-05-20T00:01:55.669513Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

e9e8fc50d9241ded14204dc76bc5042fd07fd4dc5e0260363d32e7a2916b87c3

Aliases

arxiv: 2605.16163 · arxiv_version: 2605.16163v1 · doi: 10.48550/arxiv.2605.16163 · pith_short_12: 5HUPYUGZEQO6 · pith_short_16: 5HUPYUGZEQO62FBA · pith_short_8: 5HUPYUGZ

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/5HUPYUGZEQO62FBAJXDWXRIEF7 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: e9e8fc50d9241ded14204dc76bc5042fd07fd4dc5e0260363d32e7a2916b87c3

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "edea1da40f7b0e9af8035bbf66959f94171fd9e38f3a7d7ed7c3a85a39d45de7",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "physics.ao-ph",
    "submitted_at": "2026-05-15T16:42:45Z",
    "title_canon_sha256": "335f05fb3b1fb4efaf928f03ef71964d252550f65a52465c6592ca90c7cf4522"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.16163",
    "kind": "arxiv",
    "version": 1
  }
}