author = "Giangrande, Scott E. and Wang, Di{\'e} and Mechem, David B. and 
                         Machado, Luiz Augusto Toledo and Biscaro, Thiago Souza and 
                         Elsaesser, Gregory",
          affiliation = "{Brookhaven National Laboratory} and {Brookhaven National 
                         Laboratory} and {University of Kansas} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Columbia University/NASA GISS}",
                title = "Synoptic and Cloud Regimes Over the Amazon Basin: Perspectives 
                         From the GoAmazon2014/5 Campaign",
                 year = "2019",
         organization = "AGU Fall Meeting",
             abstract = "he primary source of uncertainty in global climate model (GCM) 
                         predictions of possible climate change is in the representation of 
                         clouds, cloud processes and associated feedbacks. As home to the 
                         largest tropical rainforest on the planet, the Amazon basin 
                         experiences complex and seasonal cloud conditions that promote 
                         local-scale cloud and precipitation changes, as well as 
                         larger-scale circulation feedbacks. The ongoing inability of GCMs 
                         to represent cloud conditions over this expansive tropical area 
                         recently motivated the 2-year US Department of Energy (DOE) 
                         Atmospheric Radiation Measurement (ARM) Observations and Modeling 
                         of the Green Ocean Amazon (GoAmazon2014/5) campaign. As part of 
                         this effort, ARM deployed its Mobile Facility (AMF) to the west of 
                         Manaus, Brazil in the central Amazon. The facility was equipped to 
                         continuously capture thermodynamic state, aerosol, cloud and 
                         precipitation properties in this unique location.",
  conference-location = "San Francisco, CA",
      conference-year = "09-13 dec.",
             language = "en",
        urlaccessdate = "20 jan. 2021"