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Abstract To improve very‐short‐range forecasts particularly in convective situations, a version of the COSMO‐Model (formerly known as LM) which simulates deep convection explicitly (horizontal grid length: 2.8 km) has been developed and is now run operationally at DWD. This model uses a prognostic type of precipitation scheme accounting for the horizontal drift of falling hydrometeors. To initialise convective‐scale events, the latent heat nudging (LHN) approach has been adopted for the assimilation of surface precipitation rates derived from radar reflectivity data. It is found that a conventional LHN scheme designed for larger‐scale models with diagnostic treatment of precipitation does not perform well and leads to strong overestimation of precipitation when applied to the convective‐scale model with a prognostic treatment of precipitation. As illustrated here, surface precipitation and vertically integrated latent heating are far less correlated horizontally and temporally in such a model than with diagnostic precipitation, and this implies a violation of the basic assumption of LHN. Several revisions to the LHN scheme have therefore been developed in view of the characteristic model behaviour so as to re‐enhance the validity of the basic assumption and to reduce greatly the overestimation of precipitation during assimilation. With the revised scheme, the model is able to simulate the precipitation patterns in good agreement with radar observations during the assimilation and the first hours of the forecast. The scheme also has a positive impact on screen‐level parameters and on the longer‐term climatology of the model. Extending the temporal impact of the radar observations further into the free forecast will be the focus of future research. Copyright © 2008 Royal Meteorological Society
Stephan et al. (Tue,) studied this question.