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Methods for Predicting the Likelihood of Safe Fieldwork Conditions in Harsh Environments

Permanent link
https://hdl.handle.net/10037/18911
DOI
https://doi.org/10.3389/feart.2020.00260
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Date
2020-07-30
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Leidman, Sasha Z.; Rennermalm, Åsa K.; Broccoli, Anthony J.; van As, Dirk; van den Broeke, Michiel R.; Steffen, Konrad; Hubbard, Alun Lloyd
Abstract
Every 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 environments
Publisher
Frontiers Media
Citation
Leidman, 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;8
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