Preprints
https://doi.org/10.5194/egusphere-2024-1673
https://doi.org/10.5194/egusphere-2024-1673
08 Jul 2024
 | 08 Jul 2024
Status: this preprint is open for discussion.

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

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

Abstract. Personal weather station (PWS) networks owned by citizens now provide near-surface observations at a spatial density unattainable with standard weather stations (SWSs) deployed by national meteorological services. This article aims to assess the benefits of assimilating PWS observations of screen-level temperature and relative humidity in the AROME-France model, in the same framework of experiments carried out to assimilate PWS observations of surface pressure in a previous work. Several methods for pre-processing these observations, in addition to the usual data assimilation (DA) screening, are evaluated and selected. After pre-processing, nearly 4700 temperature and 4200 relative humidity PWS observations are assimilated per hour, representing 3 and 6 times more than SWS observations, respectively. Separate assimilation of each variable in the atmosphere with the 3DEnVar DA scheme significantly reduces the root-mean-square deviation between SWS observations and forecasts of the assimilated variable at 2 m height above ground level up to 3 h range. Improvements to the near-surface temperature and relative humidity fields analysed are shown for a sea breeze case during a heatwave and a fog episode. However, degradation of short-range forecasts are found when PWS observations are assimilated with the current operational 3DVar DA scheme in the atmosphere or jointly in the atmosphere and at the surface with 3DEnVar and Optimal interpolation DA schemes. These results demonstrate that the benefit of assimilating temperature and relative humidity PWS observations can be highly dependent on the DA schemes and settings employed.

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

Status: open (until 23 Aug 2024)

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

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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.