Assimilating Differential Reflectivity Columns into the High-Resolution Rapid Refresh Using Latent Heating Forcing

The High Resolution Rapid Refresh (HRRR) assimilates radar reflectivity information in order to skillfully forecast convection. This assimilation is done using an empirical relationship between reflectivity and latent heat release from hydrometeor condensation and freezing to update the temperature tendency field. The temperature tendency field then forces the HRRR to produce updrafts where the temperature tendency is large and positive. Two problems with this approach are that areas of high reflectivity are temporally and spatially offset from vertical velocity maxima. Differential reflectivity (Z_DR), which is now experimentally available on a national mosaic from the Multi Radar Multi Sensor (MRMS) project, provides a possible solution to these two problems.

Vertical columns of enhanced Z_DR above the environmental freezing level can be used as proxies for updrafts, so creating a two-dimensional field of Z_DR column locations can focus the latent heating forcing to where convective updrafts are actively occurring. This presentation will discuss the algorithm used to detect Z_DR columns and subjectively assess how well the analyzed Z_DR columns match the expected locations of updrafts in convective events. The method used to create a temperature tendency field from Z_DR column locations that can be assimilated into the HRRR will also be discussed. These Z_DR column-derived temperature tendency fields will then be compared to the temperature tendency fields currently used by the HRRR that are derived from radar reflectivity in order to demonstrate the feasibility of assimilating Z_DR columns instead of or in addition to radar reflectivity. Preliminary results from a case study in which Z_DR column information is assimilated may also be presented.