Use of four-dimensional data assimilation by Newtonian relaxation and latent-heat forcing to improve a mesoscale-model precipitation forecast: a case study

Abstract

The conventional (control) initialization procedure that used only operational radiosonde data produced a precipitation prediction for the first three to four hours of the forecast period that would have been inadequate in an operational setting. Whereas at the initial time of the forecast there was substantial convective precipitation observed in a band near the edge of an elevated mixed layer, the model did not initiate the heavy rainfall until about the fourth hour of the forecast. The use of the experimental static initialization with prescribed latent heating during the first forecast hour produced greatly improved rainfall rates during the first three to four hours. Even though both the experimental static- and dynamic-initialization procedures produced considerably improved very-short-range precipitation forecasts, compared to the control, the experimental static-initialization procedure that used latent-heat forcing during the first forecast hour did slightly better for this case. -from Authors