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Title: Campaign datasets for Observations and Modeling of the Green Ocean Amazon (GOAMAZON)

Abstract

The hydrologic cycle of the Amazon Basin is one of the primary heat engines of the Southern Hemisphere. Any accurate climate model must succeed in a good description of the Basin, both in its natural state and in states perturbed by regional and global human activities. At the present time, however, tropical deep convection in a natural state is poorly understood and modeled, with insufficient observational data sets for model constraint. Furthermore, future climate scenarios resulting from human activities globally show the possible drying and the eventual possible conversion of rain forest to savanna in response to global climate change. Based on our current state of knowledge, the governing conditions of this catastrophic change are not defined. Human activities locally, including the economic development activities that are growing the population and the industry within the Basin, also have the potential to shift regional climate, most immediately by an increment in aerosol number and mass concentrations, and the shift is across the range of values to which cloud properties are most sensitive. The ARM Climate Research Facility in the Amazon Basin seeks to understand aerosol and cloud life cycles, particularly the susceptibility to cloud aerosol precipitation interactions, within the Amazon Basin.

Authors:
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Publication Date:
DOE Contract Number:  
DE-AC05-00OR22725
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Archive; Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Data Center
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Collaborations:
PNNL, BNL, ANL, ORNL
Subject:
54 Environmental Sciences
Keywords:
Amazon, heat, climate, convection, tropical, basin, aerosol, global, mass, and cloud cycle
OSTI Identifier:
1346559
DOI:
https://doi.org/10.5439/1346559

Citation Formats

Martin, Scot, Mei, Fan, Alexander, Lizabeth, Artaxo, Paulo, Barbosa, Henrique, Bartholomew, Mary Jane, Biscaro, Thiago, Buseck, Peter, Chand, Duli, Comstock, Jennifer, Dubey, Manvendra, Godstein, Allen, Guenther, Alex, Hubbe, John, Jardine, Kolby, Jimenez, Jose-Luis, Kim, Saewung, Kuang, Chongai, Laskin, Alexander, Long, Chuck, Paralovo, Sarah, Petaja, Tuukka, Powers, Heath, Schumacher, Courtney, Sedlacek, Arthur, Senum, Gunnar, Smith, James, Shilling, John, Springston, Stephen, Thayer, Mitchell, Tomlinson, Jason, Wang, Jian, and Xie, Shaocheng. Campaign datasets for Observations and Modeling of the Green Ocean Amazon (GOAMAZON). United States: N. p., 2015. Web. doi:10.5439/1346559.
Martin, Scot, Mei, Fan, Alexander, Lizabeth, Artaxo, Paulo, Barbosa, Henrique, Bartholomew, Mary Jane, Biscaro, Thiago, Buseck, Peter, Chand, Duli, Comstock, Jennifer, Dubey, Manvendra, Godstein, Allen, Guenther, Alex, Hubbe, John, Jardine, Kolby, Jimenez, Jose-Luis, Kim, Saewung, Kuang, Chongai, Laskin, Alexander, Long, Chuck, Paralovo, Sarah, Petaja, Tuukka, Powers, Heath, Schumacher, Courtney, Sedlacek, Arthur, Senum, Gunnar, Smith, James, Shilling, John, Springston, Stephen, Thayer, Mitchell, Tomlinson, Jason, Wang, Jian, & Xie, Shaocheng. Campaign datasets for Observations and Modeling of the Green Ocean Amazon (GOAMAZON). United States. doi:https://doi.org/10.5439/1346559
Martin, Scot, Mei, Fan, Alexander, Lizabeth, Artaxo, Paulo, Barbosa, Henrique, Bartholomew, Mary Jane, Biscaro, Thiago, Buseck, Peter, Chand, Duli, Comstock, Jennifer, Dubey, Manvendra, Godstein, Allen, Guenther, Alex, Hubbe, John, Jardine, Kolby, Jimenez, Jose-Luis, Kim, Saewung, Kuang, Chongai, Laskin, Alexander, Long, Chuck, Paralovo, Sarah, Petaja, Tuukka, Powers, Heath, Schumacher, Courtney, Sedlacek, Arthur, Senum, Gunnar, Smith, James, Shilling, John, Springston, Stephen, Thayer, Mitchell, Tomlinson, Jason, Wang, Jian, and Xie, Shaocheng. 2015. "Campaign datasets for Observations and Modeling of the Green Ocean Amazon (GOAMAZON)". United States. doi:https://doi.org/10.5439/1346559. https://www.osti.gov/servlets/purl/1346559. Pub date:Wed Dec 30 00:00:00 EST 2015
@article{osti_1346559,
title = {Campaign datasets for Observations and Modeling of the Green Ocean Amazon (GOAMAZON)},
author = {Martin, Scot and Mei, Fan and Alexander, Lizabeth and Artaxo, Paulo and Barbosa, Henrique and Bartholomew, Mary Jane and Biscaro, Thiago and Buseck, Peter and Chand, Duli and Comstock, Jennifer and Dubey, Manvendra and Godstein, Allen and Guenther, Alex and Hubbe, John and Jardine, Kolby and Jimenez, Jose-Luis and Kim, Saewung and Kuang, Chongai and Laskin, Alexander and Long, Chuck and Paralovo, Sarah and Petaja, Tuukka and Powers, Heath and Schumacher, Courtney and Sedlacek, Arthur and Senum, Gunnar and Smith, James and Shilling, John and Springston, Stephen and Thayer, Mitchell and Tomlinson, Jason and Wang, Jian and Xie, Shaocheng},
abstractNote = {The hydrologic cycle of the Amazon Basin is one of the primary heat engines of the Southern Hemisphere. Any accurate climate model must succeed in a good description of the Basin, both in its natural state and in states perturbed by regional and global human activities. At the present time, however, tropical deep convection in a natural state is poorly understood and modeled, with insufficient observational data sets for model constraint. Furthermore, future climate scenarios resulting from human activities globally show the possible drying and the eventual possible conversion of rain forest to savanna in response to global climate change. Based on our current state of knowledge, the governing conditions of this catastrophic change are not defined. Human activities locally, including the economic development activities that are growing the population and the industry within the Basin, also have the potential to shift regional climate, most immediately by an increment in aerosol number and mass concentrations, and the shift is across the range of values to which cloud properties are most sensitive. The ARM Climate Research Facility in the Amazon Basin seeks to understand aerosol and cloud life cycles, particularly the susceptibility to cloud aerosol precipitation interactions, within the Amazon Basin.},
doi = {10.5439/1346559},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2015},
month = {12}
}

Works referenced in this record:

Convective storms and non-classical low-level jets during high ozone level episodes in the Amazon region: An ARM/GOAMAZON case study
journal, April 2017


Convective cloud vertical velocity and mass-flux characteristics from radar wind profiler observations during GoAmazon2014/5
journal, November 2016


Deep Convection and Column Water Vapor over Tropical Land versus Tropical Ocean: A Comparison between the Amazon and the Tropical Western Pacific
journal, October 2016


Tropical Convective Transition Statistics and Causality in the Water Vapor–Precipitation Relation
journal, March 2017


The Green Ocean Amazon Experiment (GoAmazon2014/5) Observes Pollution Affecting Gases, Aerosols, Clouds, and Rainfall over the Rain Forest
journal, May 2017


Amazon boundary layer aerosol concentration sustained by vertical transport during rainfall
journal, October 2016


Cloudiness over the Amazon rainforest: Meteorology and thermodynamics
journal, July 2016

  • Collow, Allison B. Marquardt; Miller, Mark A.; Trabachino, Lynne C.
  • Journal of Geophysical Research: Atmospheres, Vol. 121, Issue 13, p. 7990-8005
  • https://doi.org/10.1002/2016JD024848