Estimating Vertical Velocity in Convective Clouds from Temperature, Pressure, and Diabatic Heating

The upcoming launch of INCUS will fill a gap in remote sensing and enable direct estimates of vertical velocity (w_c) in convective clouds. Here, we present a way to estimate w_c using equations that connect w_c to temperature, pressure, and convective core diabatic heating, and we compare the new formulations to one developed in Kukulies et al. (2024). We test the method for estimating w_c on a diverse set of large-eddy simulations (LESs), which include WRF and GCE simulations of tropical convective scenes and a mid-latitude convective scene. We find that the analytical formulations can reproduce the LES vertical velocities within a couple of m/s. We discuss the limitations of the method, focusing on the sensitivity of estimated vertical velocities to temperature, particularly for larger w_c. Formulations for w_c that analytically depend on diabatic heating and environmental variables enable us to address a historical gap in w_c using satellite observations of convective diabatic heating (GPM, TRMM), bridging w_c estimates from the past to future INCUS direct measurements. Doing so allows longer timescale and regime-dependent convective-anvil processes to be studied. Given the sensitivity to temperature, our results suggest the importance of quantifying local mesoscale variations in the environment to constrain w_c in the current program of record. We discuss future steps, including the potential for further validating the method's w_c estimates against INCUS retrievals.

Kukulies, J., Prein, A. F., & Morrison, H. (2024). Simulating precipitation efficiency across the deep convective gray zone. Journal of Geophysical Research: Atmospheres, 129(24), e2024JD041924.