Articles | Volume 3, issue 2
https://doi.org/10.5194/gc-3-191-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gc-3-191-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| Highlight paper
| 
13 Aug 2020
Review article | Highlight paper |
| 13 Aug 2020
| 13 Aug 2020
Open weather and climate science in the digital era
Martine G. de Vos
CORRESPONDING AUTHOR
Netherlands eScience center, Amsterdam, the Netherlands
Information and Technology Services, Utrecht University, Utrecht, the Netherlands
Wilco Hazeleger
Netherlands eScience center, Amsterdam, the Netherlands
Geosciences, Utrecht University, Utrecht, the Netherlands
Driss Bari
CNRMSI/SMN, Direction de la Meteorologie Nationale Casablanca, Morocco
Jörg Behrens
German Climate Computing Centre (DKRZ), Hamburg, Germany
Sofiane Bendoukha
German Climate Computing Centre (DKRZ), Hamburg, Germany
Irene Garcia-Marti
Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Ronald van Haren
Netherlands eScience center, Amsterdam, the Netherlands
Sue Ellen Haupt
Research Applications Laboratory, National Center for Atmopsheric Research, Boulder, USA
Water Resources Management, Delft University of Technology, Delft, the Netherlands
Fredrik Jansson
Centrum Wiskunde & Informatica, Amsterdam, the Netherlands
Andreas Mueller
Numerical methods, European Centre for Medium-Range Weather Forecasts, Reading, UK
Peter Neilley
The Weather Company/IBM, Boston, MA, USA
Gijs van den Oord
Netherlands eScience center, Amsterdam, the Netherlands
Inti Pelupessy
Netherlands eScience center, Amsterdam, the Netherlands
Paolo Ruti
World Weather Research Division, World Meteorological Organization, Geneva, Switzerland
Martin G. Schultz
Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany
Jeremy Walton
Hadley Centre for Climate Science, Met Office, Exeter, UK
Viewed
Total article views: 4,636 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 29 Oct 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,797 | 736 | 103 | 4,636 | 112 | 114 |
- HTML: 3,797
- PDF: 736
- XML: 103
- Total: 4,636
- BibTeX: 112
- EndNote: 114
Total article views: 3,787 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 13 Aug 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,223 | 510 | 54 | 3,787 | 60 | 60 |
- HTML: 3,223
- PDF: 510
- XML: 54
- Total: 3,787
- BibTeX: 60
- EndNote: 60
Total article views: 849 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 29 Oct 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 574 | 226 | 49 | 849 | 52 | 54 |
- HTML: 574
- PDF: 226
- XML: 49
- Total: 849
- BibTeX: 52
- EndNote: 54
Viewed (geographical distribution)
Total article views: 4,636 (including HTML, PDF, and XML)
Thereof 3,893 with geography defined
and 743 with unknown origin.
Total article views: 3,787 (including HTML, PDF, and XML)
Thereof 3,157 with geography defined
and 630 with unknown origin.
Total article views: 849 (including HTML, PDF, and XML)
Thereof 736 with geography defined
and 113 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
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Cited
7 citations as recorded by crossref.
- Intelligent IoT Wind Emulation System Based on Real-Time Data Fetching Approach R. Singh et al. 10.1109/ACCESS.2022.3193774
- When geoscience meets generative AI and large language models: Foundations, trends, and future challenges A. Hadid et al. 10.1111/exsy.13654
- Beach and Weather: A Mobile Crowdsensing platform to report beach conditions J. Peña-Abreu & F. Terroso-Saenz 10.1016/j.simpa.2023.100472
- A hydrologist's guide to open science C. Hall et al. 10.5194/hess-26-647-2022
- HOTRUNZ: an open-access 1 km resolution monthly 1910–2019 time series of interpolated temperature and rainfall grids with associated uncertainty for New Zealand T. Etherington et al. 10.5194/essd-14-2817-2022
- From proof‐of‐concept to proof‐of‐value: Approaching third‐party data to operational workflows of national meteorological services I. Garcia‐Marti et al. 10.1002/joc.7757
- The MÉRA Data Extraction toolkit L. Görgü et al. 10.1002/met.2111
7 citations as recorded by crossref.
- Intelligent IoT Wind Emulation System Based on Real-Time Data Fetching Approach R. Singh et al. 10.1109/ACCESS.2022.3193774
- When geoscience meets generative AI and large language models: Foundations, trends, and future challenges A. Hadid et al. 10.1111/exsy.13654
- Beach and Weather: A Mobile Crowdsensing platform to report beach conditions J. Peña-Abreu & F. Terroso-Saenz 10.1016/j.simpa.2023.100472
- A hydrologist's guide to open science C. Hall et al. 10.5194/hess-26-647-2022
- HOTRUNZ: an open-access 1 km resolution monthly 1910–2019 time series of interpolated temperature and rainfall grids with associated uncertainty for New Zealand T. Etherington et al. 10.5194/essd-14-2817-2022
- From proof‐of‐concept to proof‐of‐value: Approaching third‐party data to operational workflows of national meteorological services I. Garcia‐Marti et al. 10.1002/joc.7757
- The MÉRA Data Extraction toolkit L. Görgü et al. 10.1002/met.2111
Latest update: 26 Jul 2024
Short summary
At the 14th IEEE International eScience Conference domain specialists and data and computer scientists discussed the road towards open weather and climate science. Open science offers manifold opportunities but goes beyond sharing code and data. Besides domain-specific technical challenges, we observed that the main challenges are non-technical and impact the system of science as a whole.
At the 14th IEEE International eScience Conference domain specialists and data and computer...
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