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

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

doi:10.5439/1346559

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

Dataset
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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:

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 more »

ORNL

Publication Date:: Tue Dec 29 23:00:00 EST 2015

DOE Contract Number:: AC05-00OR22725

Research Org.:: Atmospheric Radiation Measurement (ARM) Archive, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Collaborations:: PNNL, BNL, ANL, ORNL

Subject:: 54 ENVIRONMENTAL SCIENCES; 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.

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                    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

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                    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:Tue Dec 29 23:00:00 EST 2015

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@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         = {Tue Dec 29 23:00:00 EST 2015},

  month        = {Tue Dec 29 23:00:00 EST 2015}

}

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DOI: https://doi.org/10.5439/1346559

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