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dc.contributor.authorLeidman, Sasha Z.
dc.contributor.authorRennermalm, Åsa K.
dc.contributor.authorBroccoli, Anthony J.
dc.contributor.authorvan As, Dirk
dc.contributor.authorvan den Broeke, Michiel R.
dc.contributor.authorSteffen, Konrad
dc.contributor.authorHubbard, Alun Lloyd
dc.date.accessioned2020-08-04T08:24:27Z
dc.date.available2020-08-04T08:24:27Z
dc.date.issued2020-07-30
dc.description.abstractEvery year, numerous field teams travel to remote field locations on the Greenland ice sheet to carry out polar research, geologic exploration, and other commercial, military, strategic, and recreational activities. In this region, extreme weather can lead to decreased productivity, equipment failure, increased stress, unexpected logistical challenges, and, in the worst cases, a risk of physical injury and loss of life. Here we describe methods for calculating the probability of a “scienceable” day defined as a day when wind, temperature, snowfall, and sunlight conditions are conducive to sustained outdoor activity. Scienceable days have been calculated for six sites on the ice sheet of southern Greenland using meteorological station data between 1996-2016, and compared with indices of large scale atmospheric circulation patterns: the Greenland Blocking Index (GBI) and the North Atlantic Oscillation (NAO). Our findings show that the probability of a scienceable day between 2010 and 2016 in the Greenland Ice Sheet.’s accumulation zone was 46 ± 17% in March-May and 86 ± 11% in July-August on average. Decreases in scienceability due to lower temperatures at higher elevations are made up for by weaker katabatic winds, especially in the shoulder seasons. We also find a strong correlation between the probability of a scienceable day and GBI (R = 0.88, p < 0.001) resulting in a significant decrease in April scienceability since 1996. The methodology presented can help inform expedition planning, the setting of realistic field goals and managing expectations, and aid with accurate risk assessment in Greenland and other harsh, remote environmentsen_US
dc.identifier.citationLeidman, Rennermalm ÅK, Broccoli, van As D, van den Broeke MR, Steffen K, Hubbard AL. Methods for Predicting the Likelihood of Safe Fieldwork Conditions in Harsh Environments. Frontiers in Earth Science. 2020;8en_US
dc.identifier.cristinIDFRIDAID 1821284
dc.identifier.doi10.3389/feart.2020.00260
dc.identifier.issn2296-6463
dc.identifier.urihttps://hdl.handle.net/10037/18911
dc.language.isoengen_US
dc.publisherFrontiers Mediaen_US
dc.relation.journalFrontiers in Earth Science
dc.relation.projectIDNorges forskningsråd: 223259en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/SFF/223259/Norway/Centre for Arctic Gas Hydrate, Environment and Climate/CAGE/en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2020 The Author(s)en_US
dc.subjectVDP::Mathematics and natural science: 400::Geosciences: 450en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Geofag: 450en_US
dc.titleMethods for Predicting the Likelihood of Safe Fieldwork Conditions in Harsh Environmentsen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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