How hyper-local forecasts can improve mountain safety | Meteorology


IAt the end of May 2021, 172 runners set off for a 100 km ultramarathon in northwest China. The following day, 21 of the runners were killed by hypothermia after a surprisingly intense storm brought freezing temperatures, high winds and hail to a highland section of the course. The weather forecast had predicted a cold front, but hadn’t captured just how extreme the conditions would be.

There are no weather stations in the area and reports from survivors are subjective, but now a new hyper-local weather model – using topographic data at tens of meters resolution rather than kilometers – indicates that Intense wind and rain caused temperatures to drop by 6.7°. C Taking into account blizzard-like conditions and the effect of wet clothing on body temperature, the study – which is published in the Journal of Geophysical Research: Atmospheres – estimates that runners would have experienced an apparent temperature of -10 °C.

Storms like this are common at high altitudes on mountains like Everest, and although rarer at low altitudes, their sudden arrival makes them particularly dangerous. The researchers suggest that hyper-local weather models can improve the accuracy of predictions for mountain events, where steep mountain slopes generate very localized effects on wind, rain and temperature on a scale too small to capture. by conventional weather forecasts.


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