Going to Extremes: Installing the World’s Highest Weather Stations on Mount Everest

• Published in: Bulletin of the American Meteorological Society 2020-11, Vol.101 (11), p.E1870-E1890
• Main Authors: Matthews, T., Perry, L. B., Koch, I., Aryal, D., Khadka, A., Shrestha, D., Abernathy, K., Elmore, A. C., Seimon, A., Tait, A., Elvin, S., Tuladhar, S., Baidya, S. K., Potocki, M., Birkel, S. D., Kang, S., Sherpa, T. C., Gajurel, A., Mayewski, P. A.
• Format: Article
• Language: English
• Subjects: Air temperature; Altitude; Atmospheric models; Automatic weather stations; Climate change; Climbing; Data collection; Design specifications; Economic forecasting; Elevation; Empirical analysis; Error reduction; Extreme environments; Fluxes; Freezing; Glacier melting; Glaciers; Ice; Mathematical models; Mountains; Precipitation; Statistical analysis; Statistical methods; Surface energy; Surface properties; Tracking; Upper atmosphere; Water towers; Weather forecasting; Wind; Winds
• ISSN: 0003-0007; 1520-0477
• DOI: 10.1175/BAMS-D-19-0198.1

As the highest mountain on Earth, Mount Everest is an iconic peak that offers an unrivalled natural platform for measuring ongoing climate change across the full elevation range of Asia’s water towers. However, Everest’s extreme environment challenges data collection, particularly on the mountain’s upper slopes, where glaciers accumulate mass and mountaineers are most exposed. Weather stations have operated on Everest before, including the world’s previous highest, but coverage has been sparse in space and time. Here we describe the installation of a network of five automatic weather stations (AWSs), including the two highest stations on Earth (8,430 and 7,945 m MSL) which greatly improves monitoring of this iconic mountain. We highlight sample applications of the new data, including an initial assessment of surface energy fluxes at Camp II (6,464 m MSL) and the South Col (7,945 m MSL), which suggest melt occurs at both sites, despite persistently below-freezing air temperatures. This analysis indicates that melt may even be possible at the 8,850 m MSL summit, and prompts a reevaluation of empirical temperature index models used to simulate glacier melt in the Himalayas that focus only on air temperature. We also provide the first evaluation of numerical weather forecasts at almost 8,000 m MSL and use of model output statistics to reduce forecast error, showcasing an important opportunity to improve climber safety on Everest. Looking forward, we emphasize the considerable potential of these freely available data for understanding weather and climate in the Himalayas and beyond, including tracking the behavior of upper-atmosphere winds, which the AWS network is uniquely positioned to monitor.