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Preprints
https://doi.org/10.5194/essd-2024-438
https://doi.org/10.5194/essd-2024-438
30 Oct 2024
 | 30 Oct 2024
Status: this preprint is currently under review for the journal ESSD.

Deep convection lifecycle characteristics: a database from GoAmazon experiment

Camila da Cunha Lopes, Rachel Ifanger Albrecht, Douglas Messias Uba, Thiago Souza Biscaro, and Ivan Saraiva

Abstract. The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment provided a comprehensive suite of cloud-aerosol-precipitation observations with both in situ and remote sensing instruments. In this study, we apply a tracking methodology to volumetric radar data, creating a refined database focused on deep convective systems with full lifecycle, incorporating lightning data. This refined deep convection database is shown to be a robust sample of the complete dataset in terms of convective systems morphology. The analysis reveals significant seasonal and diurnal variations in convective morphology and intensity, with most intense systems occurring during the dry-to-wet season transition. The filtered dataset offers a robust sample for future studies on Amazonian convection.

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This study used observations collected during The Observations and Modeling of the Green Ocean...
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