SNOW-WEB: a new technology for Antarctic meteorological monitoring

Abstract This study describes SNOW-WEB, a distributed system of atmospheric sensors, which is cost-effective and can be efficiently deployed in Antarctica. The system supports traditional atmospheric sensors and has built-in redundancy as many units can be deployed in a relatively small area for a s...

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Bibliographic Details
Published in:Antarctic Science
Main Authors: Coggins, J.H.J., Mcdonald, A.J., Plank, G., Pannell, M., Jolly, B., Parsons, S., Delany, T.
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2013
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Online Access:http://dx.doi.org/10.1017/s0954102013000011
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0954102013000011
Description
Summary:Abstract This study describes SNOW-WEB, a distributed system of atmospheric sensors, which is cost-effective and can be efficiently deployed in Antarctica. The system supports traditional atmospheric sensors and has built-in redundancy as many units can be deployed in a relatively small area for a similar cost to one conventional weather station. Furthermore, each unit is equipped with wireless mesh-networking capabilities and so is able to share information with those units in its direct vicinity. This allows for the ferrying of collected information to a manned observation station and hence the ability to monitor data in real-time. GPS hardware installed on each unit also allows for high-resolution glacier or ice shelf tracking. As a testing study, eighteen such weather stations were deployed in the vicinity of Scott Base, Ross Island, Antarctica over the 2011/12 summer season. This paper reports on the successful development and deployment of the system, results from the testing period and challenges encountered during the experiment. Collected data is validated against automatic weather stations already operating in the region and an intercomparison is performed between SNOW-WEB data and forecast output from the Antarctic Mesoscale Prediction System. A high degree of agreement is found between data sources. We conclude that SNOW-WEB data is suitable for use in studies of mesoscale meteorology.