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

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 PWS temperature and 4200 PWS relative humidity 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 three-dimensional ensemble variational (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 of forecasts. 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 PWS temperature and relative humidity observations can be highly dependent on the DA schemes and settings employed.