Abstract
Gravity waves (GWs) generated by tropical convection are important for the simulation of large-scale atmospheric circulations, for example, the quasi-biennial oscillation (QBO), and small-scale phenomena like clear-air turbulence. However, the simulation of these waves still poses a challenge due to the inaccurate representation of convection, and the high computational costs of global, cloud-resolving models. Methods combining models with observations are needed to gain the necessary knowledge on GW generation, propagation, and dissipation so that we may encode this knowledge into fast parameterized physics for global weather and climate simulation or turbulence forecasting. We present a new method suitable for rapid simulation of realistic convective GWs. Here, we associate the profile of latent heating with two parameters: precipitation rate and cloud top height. Full-physics cloud-resolving WRF simulations are used to develop a lookup table for converting instantaneous radar precipitation rates and echo top measurements into a high-resolution, time-dependent latent heating field. The heating field from these simulations is then used to force an idealized dry version of the WRF model. We validate the method by comparing simulated precipitation rates and cloud tops with scanning radar observations and by comparing the GW field in the idealized simulations to satellite measurements. Our results suggest that including variable cloud top height in the derivation of the latent heating profiles leads to better representation of the GWs compared to using only the precipitation rate. The improvement is especially noticeable with respect to wave amplitudes. This improved representation also affects the forcing of GWs on large-scale circulation.