The implementation of the ice phase microphysical process into a four-dimensional Variational Doppler Radar Analysis System (VDRAS) and its impact on quantitative precipitation nowcasting

The microphysical process of a cloud-scale model used by a four-dimensional Variational Doppler Radar Analysis System (VDRAS) is improved from the original warm rain parameterization scheme to a cold rain process containing ice and snow. Instead of adding additional prognostic equations for ice and snow and developing their adjoint equations, the implementation of the ice phase microphysical process is accomplished by fully taking advantage of the existing four-dimensional variational (4DVar) minimization framework already employed by VDRAS. A series of observation system simulation experiments (OSSEs) and a real case study are conducted to examine the accuracy of the new microphysical scheme, and to explore the influence of the ice phase process on the model simulations, parameter retrievals, radar data assimilation, and the numerical model's short-term quantitative precipitation nowcasting (QPN) capability.

The forward simulations show that implementing the ice phase process leads to more latent heat release, causing stronger updrafts at upper levels than those produced by the warm rain process. Results obtained from the OSSEs reveal that the retrieved liquid water content will be underestimated if all radar reflectivity is assumed to be in the form of liquid phase. This underestimation, however, can be effectively mitigated when the ice phase process is considered. Using the VDRAS-generated freezing level during the data assimilation cycle to imitate the true but unknown 0o C line is found to be a feasible approach for separating the rain and snow, and at the same time allows the 4DVar minimization algorithm to converge to an optimal solution. A real case study from Intensive Operation Period (IOP) #8 of the 2008 Southwest Monsoon Experiment (SoWMEX) demonstrates that by adding ice phase process, VDRAS is more capable of capturing the actual evolution of the reflectivity field than the original scheme equipped with only liquid phase microphysics. There is also a significant improvement in the model's QPN skill in terms of the pattern of precipitation and accumulated rainfall amounts.