Hosted by: Mike Jensen

Deep moist convection plays a pivotal role ranging from daily weather impacts to long-term climatic feedbacks. The height and depth of deep convection are particularly important parameters for studies focusing on convective mass transport. Deep convection has the potential to rapidly transport mass and chemical constituents from the boundary layer into the upper tropospheric and lower stratospheric layer. Depending on whether convection is able to reach and penetrate the tropopause has significant implications on whether mass is rapidly transported into the troposphere or the stratosphere, where long residence times can alter the chemical budget and have important effects on climate. Nevertheless, accurately identifying the dynamic convective detrainment height is not easily achieved and commonly used methods contain considerable limitations or assumptions. Observations, such as taken by satellite or aircraft, are typical limited temporally and/or spatially. To account for limited observations, focus is either directed on the use of parcel theory or chemical modeling; however, assumptions in parcel theory are often invalid in observed convection and limited knowledge is available on the accuracy of simulated storm depths and heights. To enhance our understanding and enable more common retrievals of convective detrainment heights, a methodology utilizing the reflectivity field from ground-based radars is used to locate the detrainment envelope and level of maximum detrainment (LMD). A new radar classification algorithm that uses three-dimensional radar observations to stratify radar echo is used to identify suitable regions of convectively-generated anvil, which are used as a proxy for dynamic detrainment. The methodology is validated against dual-Doppler observations and preliminary results of applying the methodology to several months of volumetric radar composites are presented. Additionally, four months of convective forecasts are evaluated to determine the ac