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Titel |
Just the right age: well-clustered exposure ages from a global glacial 10Be compilation |
VerfasserIn |
Jakob Heyman, Martin Margold |
Konferenz |
EGU General Assembly 2017
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Medientyp |
Artikel
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Sprache |
en
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 19 (2017) |
Datensatznummer |
250152054
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Publikation (Nr.) |
EGU/EGU2017-16843.pdf |
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Zusammenfassung |
Cosmogenic exposure dating has been used extensively for defining glacial chronologies,
both in ice sheet and alpine settings, and the global set of published ages today reaches well
beyond 10,000 samples. Over the last few years, a number of important developments have
improved the measurements (with well-defined AMS standards) and exposure age
calculations (with updated data and methods for calculating production rates), in the best case
enabling high precision dating of past glacial events. A remaining problem, however, is the
fact that a large portion of all dated samples have been affected by prior and/or incomplete
exposure, yielding erroneous exposure ages under the standard assumptions. One way to
address this issue is to only use exposure ages that can be confidently considered as
unaffected by prior/incomplete exposure, such as groups of samples with statistically
identical ages.
Here we use objective statistical criteria to identify groups of well-clustered exposure ages
from the global glacial “expage” 10Be compilation. Out of ∼1700 groups with at least 3
individual samples ∼30% are well-clustered, increasing to ∼45% if allowing outlier rejection
of a maximum of 1/3 of the samples (still requiring a minimum of 3 well-clustered ages). The
dataset of well-clustered ages is heavily dominated by ages <30 ka, showing that well-defined
cosmogenic chronologies primarily exist for the last glaciation. We observe a large-scale
global synchronicity in the timing of the last deglaciation from ∼20 to 10 ka. There is also a
general correlation between the timing of deglaciation and latitude (or size of the
individual ice mass), with earlier deglaciation in lower latitudes and later deglaciation
towards the poles. Grouping the data into regions and comparing with available
paleoclimate data we can start to untangle regional differences in the last deglaciation
and the climate events controlling the ice mass loss. The extensive dataset and the
statistical analysis enables an unprecedented global view on the last deglaciation. |
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