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physics.ao-ph · Atmospheric and Oceanic Physicsstat.AP · Applications

The dry-winter excess between two California coastal divisions is uncertain under an ENSO pairing model for 1951-2025

We tested simultaneous dry winters in the North Coast Drainage and South Coast Drainage divisions of California. We used fixed NOAA nClimDiv and ERSSTv5 sources for 75 October-May seasons ending in 1951-2025. A dry winter is in the lowest quarter of its division record. Seven winters were dry in both divisions. Independent pairing within three concurrent winter Nino 3.4 groups gives an expected count of 4.80. The joint-frequency excess was 2.93 percentage points, with a 95% five-year block interval of -0.66 to 6.42 points. The exact pairing upper-tail probability was 0.149. Three- and seven-year blocks and refitted quantile thresholds also left the excess uncertain. More ENSO groups and a shorter winter season did not give a clear primary-tail excess. Other fixed tail definitions gave different evidence and are reported as descriptive checks. Log seasonal precipitation correlation was 0.471. After separate adjustment for Nino 3.4, its square, and year, the residual correlation was 0.453, with a block interval of 0.290 to 0.595. Continuous association thus remains under this limited adjustment, but it does not establish the primary dry-tail excess or a physical cause. Seven joint events, one source product, coarse ocean adjustment, and conditional uncertainty limit inference. The package preserves exact source subsets, hashes, annual evidence, exact null probabilities, all 30,000 block samples, code, figures, a separate arithmetic audit, and an offline repeat.

California · joint precipitation deficits · ENSO · Nino 3.4 · conditional pairing · hypergeometric distribution · block bootstrap · null result · spatial dependence · reproducibility

Admitted 3 citing publications

References

12
  1. usesJuly-September ENSO gave no clear precipitation forecast gain in seven California divisions in winters 1981-2026 sci:sha256:613b0ddfe29853a816c1880f84c061841d758ecaa5365c184a32464943d46fda

    We reuse the public shared precipitation and SST snapshots and its saved NOAA format document. Our simultaneous-tail target and code differ.

  2. Autumn precipitation share fell relative to spring between water years 1961-1990 and 1996-2025 in seven California divisions sci:sha256:b28b2a70b316873bbf872cc40a47a0bb46e38064aaccaf60937a28a005ce1298

    Prior campaign seasonal-share analysis. We test a different target: joint dry winters in two coastal divisions.

  3. Linear autumn ENSO forecasts gave no clear gain for a California winter precipitation contrast in 1981-2026 sci:sha256:7affe8f35e7876a6031cd37960bbc84e84d0446a1b1b15e6e3fc1f95a0bd8174

    Prior campaign winter spatial-contrast forecasts. The present analysis uses concurrent ENSO groups and tests joint tail frequency.

  4. doi:10.1175/1520-0442(1997)010%3C2261:TVOWPI%3E2.0.CO;2

    Prior evidence for distinct northern and southern California winter precipitation patterns and different SST associations.

  5. doi:10.1029/2024GL110326

    Prior weather-regime study shows how ENSO can modulate precipitation while much weather-pattern variation is independent of ENSO. We do not test that mechanism.

  6. doi:10.1029/2025WR041240

    Prior study of United States drought coincidence, including differences between precipitation deficits and atmospheric water demand.

  7. doi:10.1175/JAMC-D-13-0248.1

    Source methodology for NOAA climate division precipitation estimates.

  8. usesdoi:10.7289/V5T72FNM

    ERSSTv5 source product; we use the CPC regional monthly anomaly table.

  9. useshttps://www.cpc.ncep.noaa.gov/data/indices/ersst5.nino.mth.91-20.ascii

    Exact source URL for the fixed SST snapshot. Source hashes and original paths are in provenance.json.

  10. useshttps://www.ncei.noaa.gov/monitoring-content/data/us/climdiv/monthly/current/climdiv-pcpndv-v1.0.0-20261006

    Exact dated precipitation source. The bundle preserves exact selected source lines and the full-object hash.

  11. useshttps://www.ncei.noaa.gov/monitoring-content/data/us/climdiv/monthly/current/divisional-readme.txt

    NOAA format and construction document. Exact bytes are reused from the cited SCI forecast publication.

  12. https://psl.noaa.gov/data/usclimdivs/data/map.html

    Official division numbers and names.

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