Pith Number

pith:3HX7Q54S

pith:2026:3HX7Q54SCJUVYHKY6VESK3CYVK

not attested not anchored not stored refs resolved

McCast: Memory-Guided Latent Drift Correction for Long-Horizon Precipitation Nowcasting

Lintao Wang, Mengwei He, Patrick Filippi, Penghui Wen, Thomas Francis Bishop, Yu Luo, Zhiyong Wang

McCast corrects latent drift in autoregressive precipitation models using a memory bank to produce coherent long-horizon forecasts.

arxiv:2605.13197 v1 · 2026-05-13 · cs.LG · cs.AI

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{3HX7Q54SCJUVYHKY6VESK3CYVK}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

By explicitly correcting latent evolution, instead of improving step-wise prediction accuracy only, McCast produces more temporally coherent and reliable long-horizon forecasts.

C2weakest assumption

That a temporally organized memory bank can reliably estimate and apply drift corrections to latent states without introducing new inconsistencies or requiring domain-specific tuning that is not captured in the abstract description.

C3one line summary

McCast uses a Drift-Corrective Memory Bank to actively correct latent drift in autoregressive precipitation nowcasting for more coherent long-horizon forecasts.

References

37 extracted · 37 resolved · 1 Pith anchors

[1] Skilful pre- cipitation nowcasting using deep generative models of radar.Nature, 597(7878):672–677, 2021 2021

[2] Skilful nowcasting of extreme precipitation with nowcastnet.Nature, 619 (7970):526–532, 2023 2023

[3] Diffcast: A unified framework via residual diffusion for precipitation nowcasting 2024

[4] AlphaPre: Amplitude-phase disentanglement model for precipitation nowcasting 2025

[5] CasCast: Skillful high-resolution precipitation nowcasting via cascaded modelling 2024

Cited by

1 paper in Pith

PhenoYieldNet: Learning Crop-Aware Phenological Responses for Multi-Crop Yield Prediction

Receipt and verification

First computed	2026-05-18T03:08:48.710655Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d9eff8779212695c1d58f549256c58aa8a9fa506aea241d13c1fccce9976bea8

Aliases

arxiv: 2605.13197 · arxiv_version: 2605.13197v1 · doi: 10.48550/arxiv.2605.13197 · pith_short_12: 3HX7Q54SCJUV · pith_short_16: 3HX7Q54SCJUVYHKY · pith_short_8: 3HX7Q54S

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/3HX7Q54SCJUVYHKY6VESK3CYVK \
  | 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: d9eff8779212695c1d58f549256c58aa8a9fa506aea241d13c1fccce9976bea8

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e6aafeb8e75b21198796d7f45088af5442361d0180302fa9fba0b9502b3a2502",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-13T08:51:24Z",
    "title_canon_sha256": "8228a6864765d70c3d63aec7cb10f686e9e2a296bb02e940815d8edec0a0f4e8"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13197",
    "kind": "arxiv",
    "version": 1
  }
}