Collecting and utilising crowdsourced data for numerical weather prediction: Propositions from the meeting held in Copenhagen, 4–5 December 2018. (10th June 2019)

• Record Type: Journal Article
• Authors: Hintz, Kasper S.; O'Boyle, Katharine; Dance, Sarah L.; Al‐Ali, Saja; Ansper, Ivar; Blaauboer, Dick; Clark, Matthew; Cress, Alexander; Dahoui, Mohamed; Darcy, Rónán; Hyrkkanen, Juhana; Isaksen, Lars; Kaas, Eigil; Korsholm, Ulrik S.; Lavanant, Marion; Le Bloa, Gwenaelle; Mallet, Emilie; McNicholas, Conor; Onvlee‐Hooimeijer, Jeanette; Sass, Bent; Siirand, Valeria; Vedel, Henrik; Waller, Joanne A.; Yang, Xiaohua
• Is Part Of: Atmospheric science letters. Volume 20:Number 7(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-06-10
• Subjects: citizen science -- crowdsourcing -- data collection -- opportunistic data -- quality control -- third‐party data; Atmospheric physics -- Periodicals; 551
• DOI: 10.1002/asl.921
• Languages: English
• ISSNs: 1530-261X

Abstract

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. 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. It was concluded that crowdsourced observations are likely to be useful for NWP. Finally, it is recommended that a platform for sharing thoughts, data and results is worked upon moving forward.