{
  "annotation_id": "99c708cf-b370-4143-95f8-2d8496cfc4ab",
  "date_created": "2026-03-02T18:00:59.935000Z",
  "date_modified": "2026-03-02T18:00:59.935000Z",
  "file_hash": "d5b09038a1acd29cbf08027a8c33a1cb4b1acc696ea87f83217ffa41ec8a6dde",
  "private": false,
  "record": {
    "abstract": "We theoretically study long-term trends in the statistics of record-breaking\ndaily temperatures and validate these predictions using Monte Carlo simulations\nand data from the city of Philadelphia, for which 126 years of daily\ntemperature data is available. Using extreme statistics, we derive the number\nand the magnitude of record temperature events, based on the observed Gaussian\ndaily temperatures distribution in Philadelphia, as a function of the number of\nelapsed years from the start of the data. We further consider the case of\nglobal warming, where the mean temperature systematically increases with time.\nWe argue that the current warming rate is insufficient to measurably influence\nthe frequency of record temperature events over the time range of the\nobservations, a conclusion that is supported by numerical simulations and the\nPhiladelphia temperature data.",
    "arxiv_id": "physics/0509088",
    "authors": [
      "S. Redner",
      "Mark R. Petersen"
    ],
    "categories": [
      "physics.data-an",
      "physics.ao-ph"
    ],
    "doi": "10.1103/PhysRevE.74.061114",
    "journal_ref": "Phys. Rev. E 74, 061114 (2006)",
    "title": "On the Role of Global Warming on the Statistics of Record-Breaking   Temperatures",
    "url": "https://arxiv.org/abs/physics/0509088"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "8305af47-f5b6-4382-b1e1-4b0d9cd99917",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}