Deep convection life cycle characteristics: a database from the GoAmazon experiment

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 a full life cycle, incorporating lightning data. This refined deep convection database is shown to be a robust sample of the complete dataset in terms of convective system morphology. The analysis reveals significant seasonal and diurnal variations in convective morphology and intensity, with most intense systems occurring during the dry-season–wet-season transition. The filtered dataset offers a robust sample for future studies on Amazonian convection. The database is available at https://doi.org/10.5281/zenodo.13732692 (Lopes, 2024).

Institutions

Publication Details

Journal
Earth system science data
Published
2025-10-17
DOI
https://doi.org/10.5194/essd-17-5489-2025
Primary Topic
Religion, Ecology, and Ethics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deep convection life cycle characteristics: a database from the GoAmazon experiment

Earth system science data
Religion, Ecology, and Ethics
article

Deep convection life cycle characteristics: a database from the GoAmazon experiment

article en

Abstract

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 a full life cycle, incorporating lightning data. This refined deep convection database is shown to be a robust sample of the complete dataset in terms of convective system morphology. The analysis reveals significant seasonal and diurnal variations in convective morphology and intensity, with most intense systems occurring during the dry-season–wet-season transition. The filtered dataset offers a robust sample for future studies on Amazonian convection. The database is available at https://doi.org/10.5281/zenodo.13732692 (Lopes, 2024).

Earth system science dataVol. 17(10)
Instituto Nacional de Pesquisas da Amazônia (BR), Instituto de Geofísica y Astronomía (CU), Instituto Nacional de Pesquisas Espaciais (BR)
Fundação de Amparo à Pesquisa do Estado de São Paulo, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Responsible consumption and production
Openalex Percentile: Top 36%
Religion, Ecology, and Ethics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Deep convection life cycle characteristics: a database from the GoAmazon experiment · Earth system science data (2025) | TGRS Research Map | TGRS