10Be measured on Akademii Nauk ice core, Russian Arctic, for the period 1590-1950 CE

Global variations of the radionuclide 10Be that are almost simultaneous provide a powerful tool to synchronize 10Be records from different locations. We compared the 10Be record of the Akademii Nauk (AN) ice core (Russian Arctic) for the time period CE 1590-1950 to the 10Be records of two well-dated...

Full description

Bibliographic Details
Main Author: Fritzsche, Diedrich
Format: Dataset
Language:English
Published: PANGAEA 2017
Subjects:
Accelerator mass spectrometry (AMS)
Age
Akademii Nauk
Severnaya Zemlya
Russian Arctic
AN
AWI Arctic Land Expedition
Beryllium-10
standard deviation
water
Correction
Depth
bottom/max
ice/snow
top/min
ICEDRILL
Ice drill
RU-Land_1999/2001_SevernayaZemly
SZ_1999/2001
Arctic
Greenland
Greenland ice cores
ice core
Journal of Glaciology
NGRIP
Online Access:https://doi.pangaea.de/10.1594/PANGAEA.869948
https://doi.org/10.1594/PANGAEA.869948
Description
Summary:Global variations of the radionuclide 10Be that are almost simultaneous provide a powerful tool to synchronize 10Be records from different locations. We compared the 10Be record of the Akademii Nauk (AN) ice core (Russian Arctic) for the time period CE 1590-1950 to the 10Be records of two well-dated Greenland ice cores (Dye3 and NGRIP). A high correlation (r=0.60) was found between the AN and Dye3 records, which increases up to 0.78 in certain intervals, whereas the correlation to NGRIP was distinctly lower. Sources of deviations may include local fluctuations in the deposition of 10Be due to changes in the precipitation patterns, artefacts due to the core-sampling strategy and a general bias in the age model. In general, the existing age model was validated confirming the AN ice core to be a unique and well-dated source of palaeoclimate parameters for the Russian Arctic. Because of a possible minor bias in the earliest part of the studied ice-core section, the influence of the core-sampling strategy was studied, based on a numerical model that simulates sampling in a discrete and continuous mode with varying sample lengths. Based on the results of the model to sample continuously with individual samples lengths covering a time span of 4-8 years we developed a new sample strategy for the deeper layers.

Similar Items