Identification of coherent links between interannual sedimentary structures and daily meteorological observations in Arctic proglacial lacustrine varves: potentials and limitations
Proglacial lacustrine sediments from High Arctic Lake R (76°17.9′N, 90°59.3′W, unofficial name) are shown to be annually laminated (varved) and contain a variety of subannual structures. The formation of the subannual structures (and overall varve) was controlled by a combination of meteorologic (te...
| Published in: | Canadian Journal of Earth Sciences |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Canadian Science Publishing
2008
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1139/e07-070 http://www.nrcresearchpress.com/doi/pdf/10.1139/e07-070 |
| Summary: | Proglacial lacustrine sediments from High Arctic Lake R (76°17.9′N, 90°59.3′W, unofficial name) are shown to be annually laminated (varved) and contain a variety of subannual structures. The formation of the subannual structures (and overall varve) was controlled by a combination of meteorologic (temperature and rainfall) and geomorphic factors. Using a training set of the ten thickest varves in the 38-year sedimentary record, a heuristic model was developed to link subannual structures with regional meteorological conditions. Within the training set, significant correlations were shown between subannual structure thickness and the magnitude of the corresponding melt event, defined as a period of continuously positive temperature. However, these correlations deteriorated as the varves progressively thinned, and several varves exhibited no relationship between their subannual structures and respective meteorological conditions. Grain size analyses showed that the thin varves were significantly finer than the thick varves and are inferred to reflect changed sediment inflow patterns that altered deposition and reduced the fidelity of the model. Despite these complexities, this study identified the potential to produce long-term, subannual reconstructions of weather conditions. Model results revealed the limitations of simple varve–meteorology relationships, as well as identified necessary environmental and sampling conditions required to produce a more robust model for future applications. |
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