Articles | Volume 14, issue 10
https://doi.org/10.5194/essd-14-4681-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4681-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
21 Oct 2022
Data description paper |
| 21 Oct 2022
| 21 Oct 2022
Quality control and correction method for air temperature data from a citizen science weather station network in Leuven, Belgium
Division Forest, Nature and Landscape, University of Leuven (KU
Leuven), Celestijnenlaan 200E-2411, 3001 Leuven, Belgium
Maarten Reyniers
Royal Meteorological Institute of Belgium, Ringlaan 3, 1180
Brussels, Belgium
Raf Aerts
Risk and Health Impact Assessment, Sciensano (Belgian Institute of
Health), Juliette Wytsmanstraat 14,1050 Brussels, Belgium
Division Ecology, Evolution and Biodiversity Conservation, University
of Leuven (KU Leuven), Kasteelpark Arenberg 31-2435, 3001 Leuven, Belgium
Ben Somers
Division Forest, Nature and Landscape, University of Leuven (KU
Leuven), Celestijnenlaan 200E-2411, 3001 Leuven, Belgium
KU Leuven Urban Studies Institute, University of Leuven (KU Leuven),
Parkstraat 45-3609, 3000 Leuven, Belgium
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Short summary
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The Amazon forest is important for carbon storage, but climate change might push parts of it towards a tipping point into a degraded state. By studying satellite trends and tree diversity across different spatial scales, we found a larger tipping risk at smaller spatial scales than for the whole region. We also found that higher tree diversity makes the forest more stable and thus less likely to tip, although the effect is relatively weak, highlighting the importance of protecting biodiversity.
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Short summary
This paper presents crowdsourced data from the Leuven.cool network, a citizen science network of around 100 low-cost weather stations distributed across Leuven, Belgium. The temperature data have undergone a quality control (QC) and correction procedure. The procedure consists of three levels that remove implausible measurements while also correcting for between-station and station-specific temperature biases.
This paper presents crowdsourced data from the Leuven.cool network, a citizen science network of...
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