Atmospheric Science Letters (Jul 2019)

Collecting and utilising crowdsourced data for numerical weather prediction: Propositions from the meeting held in Copenhagen, 4–5 December 2018

  • Kasper S. Hintz,
  • Katharine O'Boyle,
  • Sarah L. Dance,
  • Saja Al‐Ali,
  • Ivar Ansper,
  • Dick Blaauboer,
  • Matthew Clark,
  • Alexander Cress,
  • Mohamed Dahoui,
  • Rónán Darcy,
  • Juhana Hyrkkanen,
  • Lars Isaksen,
  • Eigil Kaas,
  • Ulrik S. Korsholm,
  • Marion Lavanant,
  • Gwenaelle Le Bloa,
  • Emilie Mallet,
  • Callie McNicholas,
  • Jeanette Onvlee‐Hooimeijer,
  • Bent Sass,
  • Valeria Siirand,
  • Henrik Vedel,
  • Joanne A. Waller,
  • Xiaohua Yang

DOI
https://doi.org/10.1002/asl.921
Journal volume & issue
Vol. 20, no. 7
pp. n/a – n/a

Abstract

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Abstract In December 2018, the Danish Meteorological Institute organised an international meeting on the subject of crowdsourced data in numerical weather prediction (NWP) and weather forecasting. The meeting, spanning 2 days, gathered experts on crowdsourced data from both meteorological institutes and universities from Europe and the United States. Scientific presentations highlighted a vast array of possibilities and progress being made globally. Subjects include data from vehicles, smartphones, and private weather stations. Two groups were created to discuss open questions regarding the collection and use of crowdsourced data from different observing platforms. Common challenges were identified and potential solutions were discussed. While most of the work presented was preliminary, the results shared suggested that crowdsourced observations have the potential to enhance NWP. A common platform for sharing expertise, data, and results would help crowdsourced data realise this potential.

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