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https://doi.org/10.5194/essd-2024-438
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2024-438
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Preprints
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.

How to cite. Lopes, C. D. C., Albrecht, R. I., Uba, D. M., Biscaro, T. S., and Saraiva, I.: Deep convection lifecycle characteristics: a database from GoAmazon experiment, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2024-438, in review, 2024.
Received: 26 Sep 2024 – Discussion started: 30 Oct 2024
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Camila da Cunha Lopes, Rachel Ifanger Albrecht, Douglas Messias Uba, Thiago Souza Biscaro, and Ivan Saraiva

Status: open (until 06 Dec 2024)

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

Data sets

GoAmazon convective systems datasets (systems and systems_filtered) Camila Lopes https://doi.org/10.5281/zenodo.13732692

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

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Short summary
This study used observations collected during The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment to create a database of storms and thunderstorms characteristics with weather radar and lightning measurements. These storms have different sizes and durations between wet and dry seasons as well as throughout the day, with the most intense ones occurring in the dry-to-wet transition. This database is useful in future studies on Amazonian clouds.
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