Methods for Predicting the Likelihood of Safe Fieldwork Conditions in Harsh Environments
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https://hdl.handle.net/10037/18911Date
2020-07-30Type
Journal articleTidsskriftartikkel
Peer reviewed
Author
Leidman, Sasha Z.; Rennermalm, Åsa K.; Broccoli, Anthony J.; van As, Dirk; van den Broeke, Michiel R.; Steffen, Konrad; Hubbard, Alun LloydAbstract
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 MediaCitation
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;8Metadata
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