Realistic simulations of gravity waves over the continental US using precipitation radar data
However, large uncertainties remain. In coarse-resolution models convection itself is a sub-grid-scale process such that the true extent, depth and amplitude of convective cells are unknown. Establishing appropriate values for these quantities is challenging as they are only loosely constrained by observations. Full physics high-resolution model simulations are of case-study nature and lack general applicability. Other common assumptions include that waves propagate conservatively, within one time step, and within the same column, to the height where they deposit their momentum and create drag. For these reasons all GWD parameterizations include adjustable parameters that scale the wave drag or impact the height where the wave dissipates. Tuning these parameters to obtain desired middle-atmosphere circulations in global models is common practice.
We present a new modeling approach that combines the realism of local full-physics simulations with the spatial and temporal scope of larger scale models to study gravity wave effects on regional circulation patterns. An idealized dry version of the WRF model is forced with a three-dimensional time-varying heating field. We introduce an algorithm to derive this heating field from local precipitation rates and show that conventional precipitation radar data is suitable to drive the model. The idealized model is capable of simulating stratospheric gravity wave spectra that reproduce the shape, magnitude and complexity obtained from full-physics models. Focusing on the continental summer US, where convection is the main source of gravity waves, we present examples of simulations using radar precipitation data to force the model. Radar products can accurately capture the high spatial and temporal variability in occurrence and strength associated with convective sources of gravity waves.