Latent Heat Retrievals Using Polarimetric Radar Data

Description

Latent heating and cooling associated with microphysical phase changes represent a primary driving force of atmospheric circulations at all scales. Much effort has been focused on the retrieval of these latent heating rates from remote-sensing measurements, particularly from satellites. However, satellites generally have coarse resolution and rely on reflectivity-based procedures for their retrievals, which require the use of some limiting assumptions. Dual-polarization radars are ideally suited for studying microphysical phase changes, due to the high spatial and temporal resolution of the data as well as the distinct polarimetric fingerprints these processes tend to have. However, few studies to date have directly investigated the potential for latent heat retrievals using polarimetric radar data. In this work, the relationship between the polarimetric variables and latent heating and cooling rates is studied using simulations performed using spectral bin microphysical models, including the Hebrew University Cloud Model and simple one-dimensional models and coupled polarimetric operator. It was found that ZDR columns within deep convection are useful in both time and space for quantitatively estimating both the magnitude of and height of the maximum latent heat release due to condensation in the updraft. The cooling rates associated with the sublimation, melting, and evaporation of stratiform snow are investigated using the one-dimensional spectral bin model. It is hypothesized that localized regions of enhanced cooling in the melting layer could be responsible for the observed sagging in the radar bright band that is frequently observed. Future work will also examine the polarimetric signatures associated with the melting and evaporation of hail, a major driver of cold pool formation and convective longevity.