{
  "annotation_id": "78357ace-11d7-41fb-b3ae-3ed7ea1e3c01",
  "date_created": "2026-03-02T18:00:50.481000Z",
  "date_modified": "2026-03-02T18:00:50.481000Z",
  "file_hash": "b7ce8bc2c3b8b81b68c62c663af3290df7ba4248f5a2dd381d7ea0bdfe89d03c",
  "private": false,
  "record": {
    "abstract": "The ECMWF ensemble weather forecasts are generated by perturbing the initial\nconditions of the forecast using a subset of the singular vectors of the\nlinearised propagator. Previous results show that when creating probabilistic\nforecasts from this ensemble better forecasts are obtained if the mean of the\nspread and the variability of the spread are calibrated separately. We show\nresults from a simple linear model that suggest that this may be a generic\nproperty for all singular vector based ensemble forecasting systems based on\nonly a subset of the full set of singular vectors.",
    "arxiv_id": "physics/0402027",
    "authors": [
      "Stephen Jewson",
      "Maarten Ambaum",
      "Christine Ziehmann"
    ],
    "categories": [
      "physics.ao-ph"
    ],
    "title": "Singular vector ensemble forecasting systems and the prediction of flow   dependent uncertainty",
    "url": "https://arxiv.org/abs/physics/0402027"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "530cc6fa-66c4-419e-aad5-ba3d1f589406",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}