Year: 2025
Type: article
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.
Source: Earth system science data
Authors: Camila da Cunha Lopes, Rachel Ifanger Albrecht, Douglas Messias Uba, Thiago Souza Biscaro, Ivan Saraiva
Language: English
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $1,509
Awards: G1224617333, Cloud processes of the main precipitation systems in Brazil: a contribution to cloud resolving modeling and to the GPM (Global Precipitation Measurement), G2511304606, G2823776494, G3572101131, G6191138830, Trace gases-aerosols-cloud interactions in Amazonia: from bioaerosols emissions to large-scale impacts (GAIA), G6756993358, G7004311969, G7027428251, Connecting the level of cloud organization to the hydrologic and aerosol cycles in the Amazon (CLOUDORG), G7806338897
OpenAlex ID: W7092286526