Results of Tuned Parameterizations of a Weather Forecast Numerical Model by Measured Characteristics of Temperature Inversions in the Planetary Boundary Layer of the Moscow Megapolis

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.