Articles | Volume 20, issue 1
https://doi.org/10.5194/nhess-20-299-2020
© 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/nhess-20-299-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jan 2020
Research article |
| 24 Jan 2020
| 24 Jan 2020
Contribution of personal weather stations to the observation of deep-convection features near the ground
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Olivier Caumont
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
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- The Impact of a Lack of Government Strategies for Sustainable Water Management and Land Use Planning on the Hydrology of Water Bodies: Lessons Learned from the Disappearance of the Aculeo Lagoon in Central Chile R. Valdés-Pineda et al. 10.3390/su14010413
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- Urban Climate Informatics: An Emerging Research Field A. Middel et al. 10.3389/fenvs.2022.867434
- Exploratory analysis of citizen observations of hourly precipitation over Scandinavia C. Lussana et al. 10.5194/asr-20-35-2023
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- Retrieving Water Vapor From an E‐Band Microwave Link With an Empirical Model Not Requiring In Situ Calibration M. Fencl et al. 10.1029/2021EA001911
- CrowdQC+—A Quality-Control for Crowdsourced Air-Temperature Observations Enabling World-Wide Urban Climate Applications D. Fenner et al. 10.3389/fenvs.2021.720747
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- Thunderstorms and extreme rainfall in south Norfolk, 16 August 2020: meteorological analysis D. Holley et al. 10.1002/wea.4038
- Exploring the relationship between flood insurance claims, crowdsourced rainfall, and tide levels for coastal urban communities: Case study for the mid-Atlantic United States A. Chen et al. 10.1016/j.jhydrol.2023.130123
- Bias Correction, Anonymization, and Analysis of Smartphone Pressure Observations Using Machine Learning and Multiresolution Kriging C. McNicholas & C. Mass 10.1175/WAF-D-20-0222.1
- Refining Citizen Climate Science: Addressing Preferential Sampling for Improved Estimates of Urban Heat Z. Calhoun et al. 10.1021/acs.estlett.4c00296
- A numerical study to investigate the roles of former Hurricane Leslie, orography and evaporative cooling in the 2018 Aude heavy-precipitation event M. Mandement & O. Caumont 10.5194/wcd-2-795-2021
- A Comparison of Mesoscale Pressure Features Observed with Smartphones and Conventional Observations C. McNicholas & C. Mass 10.1175/WAF-D-21-0166.1
- The heavy precipitation event of 14–15 October 2018 in the Aude catchment: a meteorological study based on operational numerical weather prediction systems and standard and personal observations O. Caumont et al. 10.5194/nhess-21-1135-2021
- Towards high-resolution gridded climatology stemming from the combination of official and crowdsourced weather observations using multi-fidelity methods D. van Beekvelt et al. 10.1371/journal.pclm.0000216
- Quantifying Local and Mesoscale Drivers of the Urban Heat Island of Moscow with Reference and Crowdsourced Observations M. Varentsov et al. 10.3389/fenvs.2021.716968
1 citations as recorded by crossref.
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Short summary
The number of connected personal weather stations has dramatically increased in the last years. These weather stations produce a high number of data that need a thorough quality control to unleash their potential. A novel quality-control algorithm now allows us to take full advantage of these data and observe thunderstorms with fine-scale details that cannot be caught by standard networks. These results pave the way for tremendous advances in both understanding and forecasting thunderstorms.
The number of connected personal weather stations has dramatically increased in the last years....
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