Articles | Volume 25, issue 1
https://doi.org/10.5194/nhess-25-429-2025
https://doi.org/10.5194/nhess-25-429-2025
Research article
 | 
29 Jan 2025
Research article |  | 29 Jan 2025

Assimilation of temperature and relative humidity observations from personal weather stations in AROME-France

Alan Demortier, Marc Mandement, Vivien Pourret, and Olivier Caumont

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Cited articles

Båserud, L., Lussana, C., Nipen, T. N., Seierstad, I. A., Oram, L., and Aspelien, T.: TITAN automatic spatial quality control of meteorological in-situ observations, Adv. Sci. Res., 17, 153–163, https://doi.org/10.5194/asr-17-153-2020, 2020. a, b, c
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Bell, A., Martinet, P., Caumont, O., Burnet, F., Delanoë, J., Jorquera, S., Seity, Y., and Unger, V.: An optimal estimation algorithm for the retrieval of fog and low cloud thermodynamic and micro-physical properties, Atmos. Meas. Tech., 15, 5415–5438, https://doi.org/10.5194/amt-15-5415-2022, 2022. a
Bell, S., Cornford, D., and Bastin, L.: How good are citizen weather stations? Addressing a biased opinion, Weather, 70, 75–84, https://doi.org/10.1002/wea.2316, 2015. a, b
Brousseau, P., Desroziers, G., Bouttier, F., and Chapnik, B.: A posteriori diagnostics of the impact of observations on the AROME-France convective-scale data assimilation system, Q. J. Roy. Meteor. Soc., 140, 982–994, https://doi.org/10.1002/qj.2179, 2014. a
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Short summary
The use of numerical weather prediction models enables the forecasting of hazardous weather situations. The incorporation of new temperature and relative humidity observations from personal weather stations into the French limited-area model is evaluated in this study. This leads to the improvement of the associated near-surface variables of the model during the first hours of the forecast. Examples are provided for a sea breeze case during a heatwave and a fog episode.
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