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CR 20:141-151 (2002)
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Abstract
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Construction of consistent ice core accumulation time series from large-scale meteorological data: development and description of a regression model for one North Greenland ice core
Traute Crüger1,*, Hans von Storch2
1Institute of Meteorology, University of Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany
2GKSS Research Centre, Max-Planck-Strasse, 21502 Geesthacht, Germany
*E-mail: crueger@dkrz.de
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ABSTRACT: An empirical downscaling relationship is constructed which consistently estimates annual ice accumulation from large-scale meteorological data. The method by which the relationship was developed and the application of the method to one ice core
are described. The statistical technique is based on a stepwise multiple linear regression using yearly accumulation as the predictand and the principle components (PCs) of seasonally averaged large-scale atmospheric fields as predictors. In order to
separate the accumulation variations related to circulation and thermodynamics, the first step involves the stream-function field as the predictor. In the second step, temperature PCs are related to the residuals between real ice accumulation and
accumulation described by stream-function PCs. One model is fitted for a North Greenland ice core. The atmospheric data are monthly NCEP Reanalysis data from 1948 to 1992. A statistical relationship is found which reproduces about 71.5% of local ice
accumulation variability. The relationship involves 3 physically plausible stream-function patterns, representing a seasonal mean (May to August) over Greenland, the North Atlantic and North Europe, which describes 64% of variance. In the second step, an
additional contribution of the temperature field to the explained variance of 7.5% is achieved. The temperature PCs represent the annual mean 700 hPa pattern covering the area from east Canada to east Greenland.
KEY WORDS: Ice core accumulation · Downscaling · NCEP-Reanalysis data
Full text in pdf format
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Published in CR Vol.
20, No. 2
(2002) on February 21
Print ISSN: 0936-577X; Online ISSN: 1616-1572.
Copyright © Inter-Research, Oldendorf/Luhe, 2002
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