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Luiz A. T. Machado, Maria A. F. Silva Dias, Carlos Morales, Gilberto Fisch, Daniel Vila, Rachel Albrecht, Steven J. Goodman, Alan J. P. Calheiros, Thiago Biscaro, Christian Kummerow, Julia Cohen, David Fitzjarrald, Ernani L. Nascimento, Meiry S. Sakamoto, Christopher Cunningham, Jean-Pierre Chaboureau, Walter A. Petersen, David K. Adams, Luca Baldini, Carlos F. Angelis, Luiz F. Sapucci, Paola Salio, Henrique M. J. Barbosa, Eduardo Landulfo, Rodrigo A. F. Souza, Richard J. Blakeslee, Jeffrey Bailey, Saulo Freitas, Wagner F. A. Lima, and Ali Tokay

CHUVA, meaning “rain” in Portuguese, is the acronym for the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (GPM). The CHUVA project has conducted five field campaigns; the sixth and last campaign will be held in Manaus in 2014. The primary scientific objective of CHUVA is to contribute to the understanding of cloud processes, which represent one of the least understood components of the weather and climate system. The five CHUVA campaigns were designed to investigate specific tropical weather regimes. The first two experiments, in Alcantara and Fortaleza in northeastern Brazil, focused on warm clouds. The third campaign, which was conducted in Belém, was dedicated to tropical squall lines that often form along the sea-breeze front. The fourth campaign was in the Vale do Paraiba of southeastern Brazil, which is a region with intense lightning activity. In addition to contributing to the understanding of cloud process evolution from storms to thunderstorms, this fourth campaign also provided a high-fidelity total lightning proxy dataset for the NOAA Geostationary Operational Environmental Satellite (GOES)-R program. The fifth campaign was carried out in Santa Maria, in southern Brazil, a region of intense hailstorms associated with frequent mesoscale convective complexes. This campaign employed a multimodel high-resolution ensemble experiment. The data collected from contrasting precipitation regimes in tropical continental regions allow the various cloud processes in diverse environments to be compared. Some examples of these previous experiments are presented to illustrate the variability of convection across the tropics.

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David K. Adams, Rui M. S. Fernandes, Kirk L. Holub, Seth I. Gutman, Henrique M. J. Barbosa, Luiz A. T. Machado, Alan J. P. Calheiros, Richard A. Bennett, E. Robert Kursinski, Luiz F. Sapucci, Charles DeMets, Glayson F. B. Chagas, Ave Arellano, Naziano Filizola, Alciélio A. Amorim Rocha, Rosimeire Araújo Silva, Lilia M. F. Assunção, Glauber G. Cirino, Theotonio Pauliquevis, Bruno T. T. Portela, André Sá, Jeanne M. de Sousa, and Ludmila M. S. Tanaka


The complex interactions between water vapor fields and deep atmospheric convection remain one of the outstanding problems in tropical meteorology. The lack of high spatial–temporal resolution, all-weather observations in the tropics has hampered progress. Numerical models have difficulties, for example, in representing the shallow-to-deep convective transition and the diurnal cycle of precipitation. Global Navigation Satellite System (GNSS) meteorology, which provides all-weather, high-frequency (5 min), precipitable water vapor estimates, can help. The Amazon Dense GNSS Meteorological Network experiment, the first of its kind in the tropics, was created with the aim of examining water vapor and deep convection relationships at the mesoscale. This innovative, Brazilian-led international experiment consisted of two mesoscale (100 km × 100 km) networks: 1) a 1-yr (April 2011–April 2012) campaign (20 GNSS meteorological sites) in and around Manaus and 2) a 6-week (June 2011) intensive campaign (15 GNSS meteorological sites) in and around Belem, the latter in collaboration with the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) Project in Brazil. Results presented here from both networks focus on the diurnal cycle of precipitable water vapor associated with sea-breeze convection in Belem and seasonal and topographic influences in and around Manaus. Ultimately, these unique observations may serve to initialize, constrain, or validate precipitable water vapor in high-resolution models. These experiments also demonstrate that GNSS meteorology can expand into logistically difficult regions such as the Amazon. Other GNSS meteorology networks presently being constructed in the tropics are summarized.

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