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dc.contributor.authorPfaffhuber, Andreas Aspmo
dc.contributor.authorLieser, Jan L.
dc.contributor.authorHaas, Christian
dc.date.accessioned2017-08-24T07:26:12Z
dc.date.available2017-08-24T07:26:12Z
dc.date.created2017-08-21T13:41:31Z
dc.date.issued2017
dc.identifier.issn0094-8276
dc.identifier.urihttp://hdl.handle.net/11250/2451679
dc.description.abstractSnow thickness on sea ice is a largely undersampled parameter yet of importance for the sea ice mass balance and for satellite-based sea ice thickness estimates and thus our general understanding of global ice volume change. Traditional direct thickness measurements with meter sticks can provide accurate but only spot information, referred to as “needles” due to their pinpoint focus and information, while airborne and satellite remote sensing snow products, referred to as “the haystack,” have large uncertainties due to their scale. We demonstrate the remarkable accuracy and applicability of ground-penetrating radar (GPR) snow thickness measurements by comparing them with in situ meter stick data from two field campaigns to Antarctica in late winter/early spring. The efficiency and millimeter-to-centimeter accuracy of GPR enables practitioners to acquire extensive, semiregional data with the potential to upscale needles to the haystack and to potentially calibrate satellite remote sensing products that we confirm to derive roughly 30% of the in situ thickness. We find the radar wave propagation velocity in snow to be rather constant (± 6%), encouraging regional snow thickness surveys. Snow thinner than 10 cm is under the detection limit with the off-the-shelf GPR setup utilized in our study.
dc.language.isoeng
dc.subjectAvalanche-RnD
dc.subjectSnøskred-FoU
dc.titleSnow thickness profiling on Antarctic sea ice with GPR—Rapid and accurate measurements with the potential to upscale needles to a haystack
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersion
dc.source.volume44
dc.source.journalGeophysical Research Letters
dc.identifier.doi10.1002/2017GL074202
dc.identifier.cristin1487649
cristin.unitcode7452,7,0,0
cristin.unitnameNGI Perth
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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