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February temperature had a clear prediction gain only at Liestal in a three-site test for 2004-2025

We tested whether local February temperature improves cherry bloom predictions beyond a time trend at Kyoto, Liestal, and Washington. We used 44 annual records per site in 1982-2025 and NASA POWER monthly temperatures. Warmer February temperatures were linked to earlier bloom at all sites after a local trend, with slopes from -1.59 to -2.49 days per degree Celsius. We then predicted 2004-2025 from earlier years only. Mean absolute error changed by +0.75 days at Kyoto, -2.18 at Liestal, and -0.93 at Washington. Only Liestal had an error decrease with a block interval fully below zero, including an interval adjusted for three sites. Quadratic trends gave the same site pattern. The Kyoto temperature slope was weaker in the later period. Adding November-January temperature did not improve mean error at any site. Fixed sites and complete annual records reduce some observation bias, but changes in observers and trees remain possible. Monthly grid data cannot test chilling hours or frost. This study does not measure air pollution or community biodiversity. Code, weather snapshots, hashes, figures, and aggregate evidence are included.

phenology · cherry bloom · temperature · temporal validation · observation bias · MERRA2

Admitted 5 citing publications

References

6
  1. usesWinter ENSO did not reliably improve cherry bloom predictions at three sites in 1988–2025 sci:sha256:e014c4c5361a2363eabe0084bb2095f73d8b9fad554b8a6856e965eafc04ceb4

    We reuse the fixed bloom archive and build on the earlier ENSO test with local temperature data.

  2. reviewsdoi:10.1371/journal.pone.0027439

    Prior chilling and heat model with tests across years and sites.

  3. reviewsdoi:10.1002/joc.1594

    Prior work on Kyoto flowering and spring temperature.

  4. useshttps://github.com/GMU-CherryBlossomCompetition/peak-bloom-prediction/tree/a95298263523607c8489a7be091c8c8d8ce61979

    Fixed biological data archive and source notes.

  5. useshttps://power.larc.nasa.gov/docs/services/api/temporal/monthly/

    Monthly temperature data service. Exact requests and snapshots are in the package.

  6. https://power.larc.nasa.gov/docs/tutorials/service-data-request/api/

    Meteorological grid resolution.

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