Tuesday, 29 August 2023: 10:45 AM
Great Lakes A (Hyatt Regency Minneapolis)
The TRacking Aerosol Convection interactions ExpeRiment (TRACER) field campaign, sponsored by the Department of Energy, collected radiosonde and precipitation radar data from June to September 2022 to investigate meteorological and aerosol influences on deep moist convection in and around Houston, Texas. This study focuses on 29 Intensive Operation Periods (IOPs) during which mesoscale circulations associated with the sea/bay-breeze fronts (SBF) served as a forcing for convection initiation. We present an analysis of the spatiotemporal heterogeneities in thermodynamic and kinematic near-storm environments across the SBF. To assess the meteorological variability, the mobile radiosonde data from the TAMU team are compared with fixed ARM sites AMF1 (La Porte, TX) and ANC (Guy, TX) using composite Skew T-log P plots, convective indices, and other sounding parameters.
We hypothesize that thunderstorms that initiate south of the SBF (in the maritime airmass) are more intense and last longer than those that initiate north of the SBF (in the continental airmass). This is because the maritime airmass has higher CAPE and more moisture at lower to mid-levels than the continental airmass. To test our hypothesis, we compare maximum composite reflectivity, echo top heights, and overall lifetime of convective cells in each airmass. By tracking the SBF location each day, we classify each cell track obtained from the PyFLEXTRKR algorithm according to the characteristic airmass in which the cell initiated.
We analyze CSAPR2 RHI data to examine the vertical profiles of cell reflectivity, differential reflectivity (ZDR), and specific differential phase (KDP) to assess environmental influences on deep convective updraft characteristics during convection initiation and at the time of maximum composite reflectivity. We also use KHGX cell tracking data to examine the correlation between cell attributes (such as cell lifetime, area, echo-top heights, and maximum reflectivity) and sounding parameters [such as CAPE, storm-relative flow, entrainment CAPE (ECAPE), total precipitable water (TPW), etc.] obtained from the most representative radiosonde data for each cell.
We analyze a well-sampled subset of cells to investigate the potential impacts and relative importance of thermodynamic versus aerosol variability on observed differences in convection across air masses. This analysis will guide our future efforts to establish causal relationships between airmass type and thunderstorm intensity.
We hypothesize that thunderstorms that initiate south of the SBF (in the maritime airmass) are more intense and last longer than those that initiate north of the SBF (in the continental airmass). This is because the maritime airmass has higher CAPE and more moisture at lower to mid-levels than the continental airmass. To test our hypothesis, we compare maximum composite reflectivity, echo top heights, and overall lifetime of convective cells in each airmass. By tracking the SBF location each day, we classify each cell track obtained from the PyFLEXTRKR algorithm according to the characteristic airmass in which the cell initiated.
We analyze CSAPR2 RHI data to examine the vertical profiles of cell reflectivity, differential reflectivity (ZDR), and specific differential phase (KDP) to assess environmental influences on deep convective updraft characteristics during convection initiation and at the time of maximum composite reflectivity. We also use KHGX cell tracking data to examine the correlation between cell attributes (such as cell lifetime, area, echo-top heights, and maximum reflectivity) and sounding parameters [such as CAPE, storm-relative flow, entrainment CAPE (ECAPE), total precipitable water (TPW), etc.] obtained from the most representative radiosonde data for each cell.
We analyze a well-sampled subset of cells to investigate the potential impacts and relative importance of thermodynamic versus aerosol variability on observed differences in convection across air masses. This analysis will guide our future efforts to establish causal relationships between airmass type and thunderstorm intensity.
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