Vol. 123, No. 2 * Pages 135–264 * April - June 2019

In this study, the performance of a high resolution numerical weather prediction (NWP) model is investigated in a particular weather situation, namely, in winter anticyclonic cases over land with low level clouds and fog. Most NWP models tend to underestimate low level cloudiness during these events which causes the overestimation of daytime temperature. Several sensitivity tests are performed to trace the cause of the erroneous model performance, and it is shown that model microphysics and, in particular, the autoconversion of cloud ice to snow is responsible for the underestimation of cloud cover. A modification is proposed which significantly reduces ice autoconversion and consequently keeps the low level clouds for situations with temperatures below freezing level. The modification is tested on several case studies and also on longer time intervals and proves to be applicable for operational model runs.