{
  "annotation_id": "bd84f2fa-074c-4019-a0bd-5fd6e5b23844",
  "date_created": "2026-03-02T18:00:39.778000Z",
  "date_modified": "2026-03-02T18:00:39.778000Z",
  "file_hash": "5613f772a4625600b38b6eced650e08062f6751bb222399e343dfeb0cb549f31",
  "private": false,
  "record": {
    "abstract": "We consider Aerosol Index (AI) time-series extracted from TOMS archive for an\narea covering Italy $(7-18^o E ; 36-47^o N)$. The missing of convergence in\nestimating the embedding dimension of the system and the inability of the\nIndependent Component Analysis (ICA) in separating the fluctuations from\ndeterministic component of the signals are evidences of an intrinsic link\nbetween the periodic behavior of AI and its fluctuations. We prove that these\ntime series are well described by a stochastic dynamical model. Moreover, the\nprincipal peak in the power spectrum of these signals can be explained whereby\na stochastic resonance, linking variable external factors, such as Sun-Earth\nradiation budget and local insolation, and fluctuations on smaller spatial and\ntemporal scale due to internal weather and antrophic components.",
    "arxiv_id": "physics/0202008",
    "authors": [
      "S. De Martino",
      "M. Falanga",
      "L. Mona"
    ],
    "categories": [
      "physics.ao-ph",
      "physics.data-an"
    ],
    "doi": "10.1103/PhysRevLett.89.128501",
    "title": "The stochastic resonance mechanism in the Aerosol Index dynamics",
    "url": "https://arxiv.org/abs/physics/0202008"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "ac7c64f0-47f3-4905-b7a8-89964fd8792f",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}