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Mesoscale Convective Systems over the rainiest spot on Earth: OTREC field campaign and Cloud-Resolving Simulations
  • John Mejia,
  • Juan Henao
John Mejia
Desert Research Institute Reno

Corresponding Author:[email protected]

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Juan Henao
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This research study shows the ability of cloud resolving models (CRM) to simulate Mesoscale Convective Systems (MCS) over the far Eastern Pacific region, off the coast of Colombia and Panama. The simulation period coincides with the newly developed OTREC field campaign (August-September, 2019), which provided enhanced upper-air soundings, NSF/NCAR G-V dropsonde and HIAPER Cloud Radar data to help evaluate the model and diagnose the environmental conditions favoring MCS development. We tested the model sensitivity to three different microphysics schemes: two popular bulk schemes (Thomson and Morrison) and one spectral bin (SBM) scheme. The models are diagnosed on their ability to simulate the observed large-scale and mesoscale environments associated with MCSs development, including the ChocoJet and Caribbean low-level jets, the semi-permanent Panama low, vertical shear, and mid-level diurnal gravity waves. We also examined the vertical distribution of hydrometeors concentrations and diabatic heat and cooling profiles. Results show that not only the SBM represents better the spatial and vertical distribution of precipitation, but also simulates better MCSs characteristics (intensity, duration, organization) and their predominant westward movement. We hypothesize that the success of the SBM in producing better organized and more long-lasting MCS stands in the stronger diabatic heating, related to a top-heavier mass profile that helps support upper-level convergence, and more intense low-level diabatic cooling that helps support stronger gravity currents. OTREC observations and CRM results shed light on the role of MCSs in the generation of enhanced mid-level mesoscale vorticity, which has been related to generation of easterly waves or enhancement of existing ones. Although the SBM is unpractical due to its computation cost (fast version takes about 10-12 times longer), it represents an important step forward in cloud modeling, with suggestive results indicating that SBM improves confidence of the physical basis of the elusive and challenging simulation of realistic tropical MCSs.