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. This paper investigates the potential benefit of ground-based microwave radiometers (MWRs) to improve the initial state (analysis)of current numerical weather prediction (NWP) systems during fogconditions. To this end, temperature, humidity and liquid water path(LWP) retrievals have been performed by directly assimilatingbrightness temperatures using a one-dimensional variational technique(1D-Var). This study focuses on a fog-dedicated field-experimentperformed over winter 2016–2017 in France. In situ measurements froma 120 m tower and radiosoundings are used to assess theimprovement brought by the 1D-Var analysis to the background. Asensitivity study demonstrates the importance of thecross-correlations between temperature and specific humidity in thebackground-error-covariance matrix as well as the bias correctionapplied on MWR raw measurements. With the optimal 1D-Varconfiguration, root-mean-square errors smaller than 1.5 K(respectively 0.8 K) for temperature and 1 g kg−1(respectively 0.5 g kg−1) for humidity are obtained up to6 km altitude (respectively within the fog layer up to250 m). A thin radiative fog case study has shown that theassimilation of MWR observations was able to correct large temperatureerrors of the AROME (Application of Research to Operations at MEsoscale) model as well as vertical and temporal errorsobserved in the fog life cycle. A statistical evaluation through thewhole period has demonstrated that the largest impact whenassimilating MWR observations is obtained on the temperature and LWPfields, while it is neutral to slightly positive for the specifichumidity. Most of the temperature improvement is observed during falsealarms when the AROME forecasts tend to significantly overestimate thetemperature cooling. During missed fog profiles, 1D-Var analyses werefound to increase the atmospheric stability within the first100 m above the surface compared to the initial backgroundprofile. Concerning the LWP, the RMSE with respect to MWR statisticalregressions is decreased from 101 g m−2 in the backgroundto 27 g m−2 in the 1D-Var analysis. These encouragingresults led to the deployment of eight MWRs during the internationalSOFOG3D (SOuth FOGs 3D experiment for fog processes study) experimentconducted by Météo-France.

atmospheric measurement techniques

Improvement of numerical weather prediction model analysis during fog conditions through the assimilation of ground-based microwave radiometer observations: a 1D-Var study