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

Hintz, K. S., O'Boyle, K., Dance, S. L., Al-Ali, S., Ansper, I., Blaauboer, D., Clark, M., Cress, A., Dahoui, M., Darcy, R., Hyrkkanen, J., Isaksen, L., Kaas, E., Korsholm, U. S., Lavanant, M., Le Bloa, G., Mallet, E., McNicholas, C., Onvlee-Hooimeijer, J., Sass, B. , Siirand, V., Vedel, H., Waller, J. A. and Yang, X. (2019) Collecting and utilising crowdsourced data for numerical weather prediction: propositions from the meeting held in Copenhagen, 4–December 5, 2018. Atmospheric Science Letters. ISSN 1530-261X

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To link to this item DOI: 10.1002/asl.921

Abstract/Summary

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.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:84048
Publisher:John Wiley & Sons

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