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M

M. Kaczmarska

Researcher at Norwegian Polar Institute

Publications -  5
Citations -  1199

M. Kaczmarska is an academic researcher from Norwegian Polar Institute. The author has contributed to research in topics: Ice core & Sea ice. The author has an hindex of 5, co-authored 5 publications receiving 1123 citations.

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One-to-one coupling of glacial climate variability in Greenland and Antarctica.

Carlo Barbante, +88 more
- 09 Nov 2006 - 
TL;DR: In this paper, a glacial climate record derived from an ice core from Dronning Maud Land, Antarctica, which represents South Atlantic climate at a resolution comparable with the Greenland ice core records was presented.
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Tropical Pacific–high latitude south Atlantic teleconnections as seen in δ18O variability in Antarctic coastal ice cores

TL;DR: In this paper, the authors used a network of eight ice cores from coastal Dronning Maud Land (DML), Antarctica, to examine the role of the tropical ENSO (El Nino-Southern Oscillation) in the temporal variability of δ18O in annual accumulation.
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Accumulation variability derived from an ice core from coastal Dronning Maud Land, Antarctica

TL;DR: A 100 m long ice core was retrieved from the coastal area of Dronning Maud Land (DML), Antarctica, in the 2000/01 austral summer as discussed by the authors, which was dated to AD 1737 by identification of volcanic horizons in dielectrical profiling and electrical conductivity measurement records in combination with seasonal layer counting from high-resolution oxygen isotope (d 18 O) data.
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Ice core melt features in relation to Antarctic coastal climate

TL;DR: In this paper, the authors measured light intensity transmission on an ice core S100 from coastal Dronning Maud Land (DML) and recorded as peaks in the light transmittance record.
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Statistical techniques to select detection thresholds for peak signals in ice-core data

TL;DR: In this paper, five statistical techniques to determine peaks in ice-core time series are presented and compared, and the success of identifying peaks with technique V is dependent on the redundancy in the data, i.e. the sampling rate.