Warm-Season Annual to Decadal Temperature Variability for Hokkaido, Japan, Inferred from Maximum Latewood Density and Ring Width Data View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2002-01

AUTHORS

Nicole Davi, Rosanne D'Arrigo, Gordon Jacoby, Brendan Buckley, Osamu Kobayashi

ABSTRACT

We present a warm season (April–September) temperature reconstructionfor Asahikawa, north central Hokkaido, Japan for AD 1557–1990. The reconstruction, which accounts for 34% of the temperature variancefrom 1925–1990, is based on maximum latewood density data from Saghalinspruce (Picea glehnii) growing at timberline (1340–1390 m) at MountAsahidake, Hokkaido. We only present a high frequency (prewhitened or white noise) version of the reconstruction because there is an unexplained offset in the mean between the actual and estimated temperature data for an earlier period of overlap from 1891–1924. The coldest summer in the reconstruction is 1718, forwhich the estimated value is 12.89 ° C, nearly four standard deviations (SD) below the mean. A colder-than-average year is reconstructed for 1641 (13.30° C, nearly 3 SD below mean), following the eruption of Komagatake, Hokkaido which began in July, 1640. The Asahikawa density chronology, shows decadal modes of variation with statistically significant spectral peaks prior to around 1850. A tree-ring width chronology for this same site (AD 1532–1990) is in phase with a tree-ring width record from centralKamchatka prior to around 1850, but out of phase since that time. This pattern suggests, as has been hypothesized for temperature-sensitive tree-ring records from the eastern Pacific sector (Alaska and Patagonia), that a decadal mode of climate variation was more dominant in the Pacific sector prior to about 1850, after which a higher frequency (ENSO-type) mode may have become more pronounced, at least until recent decades. Additional data from the northwestern Pacific is needed to compare to these findings. More... »

PAGES

201-217

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1013085624162

DOI

http://dx.doi.org/10.1023/a:1013085624162

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1046663522


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