optimal ranking regime analysis of treeflow dendrohydrological reconstructions

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ID: 186421
2015
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Ranked #69 of 96 articles by views in proceedings - 16th ieee/acis international conference on computer and information science, icis 2017

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Abstract
The optimal ranking regime (ORR) method was used to identify 6–100-year time windows containing significant ranking sequences in 55 western US streamflow reconstructions, and reconstructions of the level of the Great Salt Lake and San Francisco Bay salinity during 1500–2007. The method's ability to identify optimally significant and non-overlapping runs of low- and high-rankings allows it to re-express a reconstruction time series as a simplified sequence of regime segments marking intra- to multi-decadal (IMD) periods of low or high streamflow, lake level, and salinity. Those ORR sequences, referred to here as Z-lines, can be plotted to identify consistent regime patterns in the analysis of numerous reconstructions. The Z-lines for the 57 reconstructions evaluated here show a common pattern of IMD cycles of drought and pluvial periods during the late 16th and 17th centuries, a relatively dormant period during the 18th century, and the reappearance of alternating dry and wet IMD periods during the 19th and early 20th centuries. Although this pattern suggests the possibility of similarly active and inactive oceanic modes in the North Pacific and North Atlantic, such centennial-scale patterns are not evident in the ORR analyses of reconstructed Pacific Decadal Oscillation (PDO), El Niño–Southern Oscillation, and North Atlantic sea-surface temperature variation. However, given the inconsistency in the analyses of four PDO reconstructions, the possible role of centennial-scale oceanic mechanisms is uncertain. In future research the ORR method might be applied to climate reconstructions around the Pacific Basin to try to resolve this uncertainty. Given its ability to compare regime patterns in climate reconstructions derived using different methods and proxies, the method may also be used in future research to evaluate long-term regional temperature reconstructions.
Reference Key
mauget2015climateoptimal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;S. A. Mauget
Journal proceedings - 16th ieee/acis international conference on computer and information science, icis 2017
Year 2015
DOI
10.5194/cp-11-1107-2015
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