Interpreting airborne ice penetrating radar data by ice core based numerical forward modeling

Edit Item Edit Item

General Information:

Eisen, O. , Wilhelms, F. , Steinhage, D. , Nixdorf, U. and Miller, H. (2003): Interpreting airborne ice penetrating radar data by ice core based numerical forward modeling , Seventh International Symposium on Antarctic Glaciology (ISAG-7), Milano, Italy, 25-29.8.2003. .
Cite this page as:
Contact Email:
Supplementary Information:


Interpretation of deep ice cores for paleoclimatic studies requires detailed knowledge of the glacial surrounding of the drilling location.Ice penetrating radar is the only means that allows detailed mapping of the internal structure of the ice body over its whole depth, providing the basis for reconstruction of ice dynamic history.Unfortunately, physical-chemical interpretation of radar data is ambiguous, as several reflection mechanismsmight contribute to the received signal.This lack of information can partly be overcome by numerical forward modeling of radar data utilising dielectric profiling (DEP) data of ice cores.Based on the complex-valued DEP data from the EPICA deep ice core in Dronning Maud Land (EDML), Antarctica,currently spanning 1500 m and approximately 50 ka of climatic history, we model a synthetic radar trace.Validation of the modeled trace is performed by comparison with surveyed airborne radar data retrieved nearthe drill site.The origin of corresponding prominent reflections is investigated by sensitivity studies with altered DEP data.Emphasis is put on the interaction between ice core properties and thepropagating magnetic wave, but the results can also be directly applied to the new radar profile connectingthe EDML and Dome Fuji drilling locations, making it possible to extrapolate ice core properties along continuous radar reflections along the profile.In addition to the presentation of results we also discuss problems and shortcomings of the combination of the different measuring and modeling methods.

Further Details:

read more
OAI 2.0:
ePIC is powered by:
EPrints 3