Midlatitude Deep Convective Transport to the Upper-Troposphere and Lower-Stratosphere

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Climate change can be understood as a change in the radiative budget of the earth; the radiative budget is sensitive to the chemical makeup of the upper-troposphere/lower-stratosphere (UTLS) region. The chemical makeup of the UTLS region remains poorly understood at scales important to chemistry models because of the difficulty in getting high temporal and spatial measurements at high altitude. Deep convection, such as the severe thunderstorms observed throughout the central United States in the summer months, is an efficient transporter of gases from the surface to the UTLS region and, therefore, is a significant source of uncertainty in UTLS composition.The research focuses on two primary objectives, both of which are important for improving our understanding of deep convective mass transport: 1) Improvement of the Algorithm to Estimate Deep Convective Transport using Radar Reflectivity, and 2) Impact of Variable UTLS Structure on Storm-Scale Deep Convective Mass Transport. Objective 1 will utilize the unique dataset provided by the 2012 Deep Convective Clouds and Chemistry (DC3) campaign to further improve a radar-only convective transport algorithm previously developed by the PI's research group. The radar-only algorithm was developed to allow cloud-scale convective transport estimates in the absence of dual-Doppler radar coverage or in situ chemical measurements. The DC3 campaign data is unique in that dual-Doppler radar coverage is co-located with a wide range of in situ chemical measurements, allowing extensive testing of the radar-only algorithm, and leading to additional improvements (e.g. objective storm maturity estimates). Objective 2 will utilize an idealized cloud-resolving model with identical storms to quantify the impact of varied UTLS structures on deep convective transport. The idealized soundings represent archetypal UTLS structures that have been observed in recent case studies and are hypothesized to strongly impact the irreversible transport, specifically a tropopause inversion and a double tropopause.Intellectual Merit:The algorithm development (objective 1) will allow for cloud-scale convective transport estimates using the NEXRAD radar network. Previously, cloud-scale transport measurements were only available in focused campaigns. The investigation into the impact of the UTLS structure on deep convective transport (objective 2) will allow for an improved understanding of the dynamical role of the tropopause region on convective evolution and transport. The impacts of varied tropopause structures on transport have been observed, but it is difficult to quantify the impact and/or understand the dynamical influences, as the storms themselves (e.g. CAPE, storm morphology) varied significantly in cases observed.Broader Impacts:The ability to use the NEXRAD radar network to estimate cloud-scale convective transport (objective 1) in the central U.S. is very important for constraining the convective contribution in chemical transport models. Previously, transport models have had to rely on satellite measurements (which are not cloud scale in at least one of dimension, i.e. x,y,z,t) or on aircraft or dual-Doppler measurements, which are limited to case studies. This feedback to the modeling community will allow for improvements to the convective transport parameterizations. The improved understanding of the impact of tropopause structures on deep convection (objective 2) is also important for constraining transport models, because often the tropopause regions is only poorly represented in regional models. This study will quantify the need for improvements to UTLS representation. This project also has educational impacts, as several graduate and undergraduate students will be trained over the course of the project.