Pith Number

pith:URPUUL6T

pith:2025:URPUUL6TKYAEVM7WI35UYUSNEN

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Leveraging Teleconnections with Physics-Informed Graph Attention Networks for Long-Range Extreme Rainfall Forecasting in Thailand

Jirawan Kamma, Kanoksri Sarinnapakorn, Kiattikun Chobtham, Kritanai Torsri, Prattana Deeprasertkul

Physics-informed graph attention networks with teleconnections and orographic physics improve long-range extreme rainfall forecasts at Thai gauge stations.

arxiv:2510.12328 v6 · 2025-10-14 · cs.LG

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Claims

C1strongest claim

Experiments demonstrate that our method outperforms well-established baselines across most regions, including areas prone to extremes, and remains strongly competitive with the state of the art. Compared with the operational forecasting system SEAS5, our real-world application improves extreme-event prediction and offers a practical enhancement to produce high-resolution maps that support decision-making in long-term water management.

C2weakest assumption

That deriving initial edge features from a simple orographic-precipitation physics formulation together with preprocessed climate teleconnection indices will capture the dominant spatiotemporal drivers of extreme rainfall sufficiently for the attention-LSTM and season-aware GPD to generalize reliably beyond the training gauges.

C3one line summary

A physics-informed graph attention LSTM with teleconnection inputs and a novel spatial season-aware GPD improves long-range extreme rainfall forecasts for Thailand over baselines and the SEAS5 operational system.

Receipt and verification

First computed	2026-05-25T02:01:08.253280Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

a45f4a2fd356004ab3f646fb4c524d23582f041e36fb66602c937bbc4b7023a1

Aliases

arxiv: 2510.12328 · arxiv_version: 2510.12328v6 · doi: 10.48550/arxiv.2510.12328 · pith_short_12: URPUUL6TKYAE · pith_short_16: URPUUL6TKYAEVM7W · pith_short_8: URPUUL6T

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/URPUUL6TKYAEVM7WI35UYUSNEN \
  | 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: a45f4a2fd356004ab3f646fb4c524d23582f041e36fb66602c937bbc4b7023a1

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "308dafe410cbafb4c85758729f8557def2abd2060105715fefc1785a87b196da",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2025-10-14T09:34:14Z",
    "title_canon_sha256": "950357f020bdfebc2ecbdd8b61a3a90eb31221080df6670636a103dcdebda614"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2510.12328",
    "kind": "arxiv",
    "version": 6
  }
}