The database presented in this study has been acquired during the SOuth west FOGs 3D (SOFOG3D) experiment for processes study. This international campaign led by Météo-France during the winter 2019–2020 aimed at deploying a unique network of both in situ and remote sensing measurements in order to document spatial and temporal variabilities of fog events. To support this scientific objective but also to conduct first data assimilation experiments within the French convective scale model AROME, an un-precedented network of 8 ground-based microwave radiometers (MWR) has been deployed in 7 different locations known to be prone to fog occurrences. The database gives access to vertical profiles of temperature and humidity (both absolute and relative) from the surface up to 10 km altitude as well as integrated water vapor and liquid water path estimates. The retrieved profiles offer a very large database that can be exploited for several scientific purposes: fog process studies at specific location, documentation on the variability of fog properties at the regional scale, better understanding of the atmospheric boundary layer (ABL) height and dynamics during wintertime conditions, development of nowcasting products dedicated to fog alerts, data assimilation experiments to improve fog forecasts, development of synergetical advanced products, and evaluation of new model configurations with advanced parameterization or resolutions.

The height of the mixing layer is a significant parameter for describing the dynamics of the planetary boundary layer (PBL), especially for air quality control and for the parametrizations in numerical modeling. The problem is that the heights of the mixing layer cannot be measured directly. The values of this parameter are depending both on the applied algorithms for calculation and on the measuring instruments which have been used by the data source. To determine the height of a layer of intense turbulent heat exchange, data were used from acoustic meteorological locator (sodar) and from a passive single-channel scanning microwave radiometer MTP-5 (MWR) to measure the temperature profile in a layer of up to 1 km. Sodar can provide information on the structure of temperature turbulence in the PBL directly. These data have been compared with the mixing layer height calculated with the Parcel method by using the MTP-5 data. For the analysis, July and September 2020 were selected in the city of Tomsk in Siberia as characteristic periods of mid-summer and the transition period to autumn. The measurement results, calculations and inter-comparisons are shown and discussed in this work. During temperature inversions in the boundary layer, it was observed that turbulent heat transfer (increased dispersion of air temperature) is covering the inversion layers and the overlying ones. Moreover, this phenomenon is not only occurring during the morning destruction of inversions, but also in the process of their formation and development.

In this work the WRF-ARW model was tested with several different combinations of physical parameterizations to assess the quality of temperature inversion parameter predictions over the Moscow city. The dynamic and statistical characteristics of temperature inversions have been calculated and analysed in selecting criteria for comparisons. The calculated of estimating of the dissipation conditions in dependence on the type of temperature inversions are presented. The data source was the results of temperature profiles measurements in a layer up to 1 km, obtained by the MTP-5 passive microwave profiler from 2018 to 2021. One MTP5 on the North of Moscow was used to tune the model parameters and another one on the East of Moscow for validation. The comparison results show that several parameterization options can be chosen to reproduce the main inversion parameters.

In this work, the optimal parametrization of a mesoscale meteorological model is sought based on a comparative analysis of model forecasts and measurement results on temperature inversions in the planetary boundary layer of the atmosphere of the Moscow megapolis. The WRF–ARW model was tested with several different combinations of physical parameterizations to assess the prediction quality for temperature inversion parameter over Moscow. The dynamic and statistical characteristics of temperature inversions have been calculated and analyzed in selecting criteria for the comparisons. The terms of temperature inversion destruction are estimated depending on the inversion type. The measurement results on temperature profiles in the layer of up to 1 km obtained by an MTP-5 passive microwave profiler from 2018 to 2021 served as the data source. One MTP-5 in the north of Moscow was used to tune the model parameters, and another one on the east of Moscow was used for validation. The comparison results show that the model can be optimally tuned using a set of several parameterization variants.