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

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

Published:2019-06-10 Issue:7 Volume:20 Page:
ISSN:1530-261X
Container-title:Atmospheric Science Letters
language:en
Short-container-title:Atmos Sci Lett

Author:

Hintz Kasper S.¹^ORCID,O'Boyle Katharine²,Dance Sarah L.³,Al‐Ali Saja⁴,Ansper Ivar⁵,Blaauboer Dick⁶,Clark Matthew²,Cress Alexander⁷,Dahoui Mohamed⁸,Darcy Rónán⁹,Hyrkkanen Juhana¹⁰,Isaksen Lars⁸,Kaas Eigil¹¹,Korsholm Ulrik S.¹,Lavanant Marion⁴,Le Bloa Gwenaelle⁴,Mallet Emilie⁴,McNicholas Callie¹²,Onvlee‐Hooimeijer Jeanette⁶,Sass Bent¹,Siirand Valeria⁵,Vedel Henrik¹,Waller Joanne A.³,Yang Xiaohua¹

Affiliation:

1. Danish Meteorological Institute Copenhagen Denmark

2. Met Office Exeter UK

3. University of Reading Reading UK

4. Météo‐France Paris France

5. Estonian Environment Agency Tallinn Estonia

6. Royal Netherlands Meteorological Institute De Bilt the Netherlands

7. Deutsche Wetterdienst Offenbach Germany

8. European Centre for Medium‐Range Weather Forecasts Reading UK

9. Met Èireann Dublin Ireland

10. Finnish Meteorological Institute Helsinki Finland

11. University of Copenhagen Niels Bohr Institute Copenhagen Denmark

12. Department of Atmospheric Sciences University of Washington Seattle Washington

Funder

Innovationsfonden

Publisher

Wiley

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/asl.921

Reference27 articles.

1. Quality of Mobile Air Temperature and Atmospheric Pressure Observations from the 2010 Development Test Environment Experiment

2. The state of automated amateur weather observations

3. How good are citizen weather stations? Addressing a biased opinion

4. Investigating the impacts of assimilating surface observations on high‐resolution forecasts of the may 15, 2013 tornado event;Carlaw L.B.;Electronic Journal of Severe Storms,2015

5. Fine-scale analysis of a severe hailstorm using crowd-sourced and conventional observations

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