Crowd‐sourced observations for short‐range numerical weather prediction: Report from EWGLAM / SRNWP Meeting 2019-Reference-Cited by-同舟云学术

Crowd‐sourced observations for short‐range numerical weather prediction: Report from EWGLAM / SRNWP Meeting 2019

Published:2021-02-25 Issue:6 Volume:22 Page:
ISSN:1530-261X
Container-title:Atmospheric Science Letters
language:en
Short-container-title:Atmos Sci Lett

Author:

Hintz Kasper S.¹^ORCID,McNicholas Callie²,Randriamampianina Roger³,Williams Hywel T. P.⁴⁵,Macpherson Bruce⁶,Mittermaier Marion⁶,Onvlee‐Hooimeijer Jeanette⁷,Szintai Balázs⁸^ORCID

Affiliation:

1. Danish Meteorological Institute (DMI) Copenhagen Denmark

2. University of Washington Seattle Washington USA

3. Norwegian Meteorological Institute (MET Norway) Oslo Norway

4. University of Exeter Exeter UK

5. Alan Turing Institute London UK

6. Met Office Exeter UK

7. Royal Netherlands Meteorological Institute (KNMI) Utrecht Netherlands

8. Hungarian Meteorological Service Budapest Hungary

Funder

Natural Environment Research Council

Innovationsfonden

Publisher

Wiley

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/asl.1031

Reference22 articles.

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3. Boulton C.A. Shotton H.andWilliams H.T.(2016)Using social media to detect and locate wildfires. Proc. 1st International Workshop on Social Web for Environmental and Ecological Monitoring (SWEEM) at International Conference on Web and Social Media (ICWSM 2016) Cologne Germany (AAAI).

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

5. @choo: Tracking Pollen and Hayfever in the UK Using Social Media

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