Pith Number

pith:A6263754

pith:2026:A62637546VBGORUXFBD5MX2B32

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VMU-Diff: A Coarse-to-fine Multi-source Data Fusion Framework for Precipitation Nowcasting

Boyu Liu, Chunlei Shi, Dan Niu, Hao Li, Hongbin Wang, Yanlan Yang, Yongchao Feng, Yufeng Zhu, Zengliang Zang

A two-stage model fuses radar and satellite data to first capture broad precipitation motion then add fine details via diffusion.

arxiv:2605.14597 v1 · 2026-05-14 · cs.CV · cs.CE · cs.MM

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Claims

C1strongest claim

Experiments on Jiangsu SWAN datasets demonstrate the improvements of our method over state-of-the-art methods, particularly in short-term forecasts.

C2weakest assumption

That the coarse-stage multi-source Vision Mamba prediction accurately captures global precipitation dynamics so the residual diffusion stage can reliably add fine details without introducing new artifacts.

C3one line summary

VMU-Diff improves precipitation nowcasting via coarse multi-source Vision Mamba fusion followed by residual conditional diffusion refinement.

References

76 extracted · 76 resolved · 5 Pith anchors

[1] Tilmann, G. and Adrian, E. R. Weather forecasting with ensemble methods. Science

[2] Machine learning tapped to improve climate forecasts

[3] Juanzhen, S. and Ming, X. and James, W. W. and Zawadzki, I. and Ballard, S. P. and Onvlee-Hooimeyer, J. and Pinto, J. Use of NWP for nowcasting convective precipitation: Recent progress and challenges

[4] Tolstykh, M. A. and Frolov, A. V. Some current problems in numerical weather prediction. Izvestiya Atmospheric and Oceanic Physics

[5] Wang-chun, W. and Wai-kin, W. Operational application of optical flow techniques to radar-based rainfall nowcasting. Atmosphere

Formal links

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Receipt and verification

First computed	2026-05-17T23:39:04.294462Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

07b5edffbcf5426746972847d65f41deaeefc7e312cde4667a2555a7969ac1bf

Aliases

arxiv: 2605.14597 · arxiv_version: 2605.14597v1 · doi: 10.48550/arxiv.2605.14597 · pith_short_12: A62637546VBG · pith_short_16: A62637546VBGORUX · pith_short_8: A6263754

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/A62637546VBGORUXFBD5MX2B32 \
  | 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: 07b5edffbcf5426746972847d65f41deaeefc7e312cde4667a2555a7969ac1bf

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6ffe7d3af9d72957ed6746869adcf4aa552fddfbd474d278f39aeb12422f2891",
    "cross_cats_sorted": [
      "cs.CE",
      "cs.MM"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-14T09:05:30Z",
    "title_canon_sha256": "ab04eaf81b84d8c50d075c683e3ac29468b8c43b75c40bb3ac199bdfa1dc0a68"
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  "source": {
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    "kind": "arxiv",
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}