Base-State Substitution: An Idealized Modeling Technique for Approximating Environmental Variability

Abstract

ase-state substitution (BSS) is a novel modeling technique for approximating environmental heterogeneity in idealized simulations. After a certain amount of model run time, base-state substitution replaces the original horizontally homogeneous background environment with a new horizontally homogeneous environment while maintaining any perturbations that have developed during the preceding simulation. This allows the user to independently modify the kinematic or thermodynamic environments, or replace the entire sounding without altering the structure of the perturbation fields. Such an approach can provide a powerful hypothesis test, for example, in a study of how an isolated convective storm would respond to a different environment within a horizontally homogeneous setting. The BSS modifications can be made gradually or instantaneously, depending on the needs of the user. In this paper both the gradual and instantaneous BSS procedures are demonstrated for simulations of deep moist convection, using first a wholly idealized setup and then a pair of observed near-storm soundings. Examination of domainwide model statistics demonstrates that model stability is maintained following the introduction of the new background environment. Following BSS, domain total mass and energy exhibit the expected instantaneous jumps upward or downward as a result of the imposed changes to the mean thermal and wind profiles, after which they remain steady during the subsequent simulation. The gridded model fields are well behaved and change gradually as the simulated storms respond meteorologically to their new environments. The paper concludes with a discussion of several unique aspects of the BSS approach.