@Article{GonçalvesCoelKuboSouz:2022:InClAt,
               author = "Gon{\c{c}}alves, Layrson de Jesus Menezes and Coelho, Simone 
                         Marilene Sievert da Costa and Kubota, Paulo Yoshio and Souza, 
                         Dayana Castilho de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Interaction between cloud-radiation, atmospheric dynamics and 
                         thermodynamics based on observational data from GoAmazon 2014/15 
                         and a cloud-resolving model",
              journal = "Atmospheric Chemistry and Physics",
                 year = "2022",
               volume = "22",
               number = "23",
                pages = "15509--15526",
                month = "Dec.",
             abstract = "Observational meteorological data from the field experiment 
                         GoAmazon 2014/15 and data from numerical simulations with the 
                         cloud-resolving model (CRM) called the System for Atmospheric 
                         Modeling (SAM) are used to study the interaction between the 
                         cloudiness-radiation as well as the atmospheric dynamics and 
                         thermodynamics variables for a site located in the central Amazon 
                         region (-3.2 \& LCIRC; S, -60.6 \& LCIRC; W) during the wet and 
                         dry periods. The main aims are to (a) analyze the temporal series 
                         of the integrated cloud fraction, precipitation rate and downward 
                         shortwave flux as well as (b) to determine the relationship 
                         between the integrated cloud fraction, radiative fluxes and 
                         large-scale variable anomalies as a function of the previous day's 
                         average. The temporal series of the integrated cloud fraction, 
                         precipitation rate and downward shortwave flux from SAM 
                         simulations showed physical consistency with the observations from 
                         GoAmazon 2014/15. Shallow and deep convection clouds show to have 
                         a meaningful impact on radiation fluxes in the Amazon region 
                         during wet and dry periods. Anomalies of large-scale variables 
                         (relative to the previous day's average) are physically associated 
                         with cloud formation, evolution and dissipation. SAM consistently 
                         simulated these results, where the cloud fraction vertical profile 
                         shows a pattern very close to the observed data (cloud type). 
                         Additionally, the integrated cloud fraction and large-scale 
                         variable anomalies, as a function of the previous day's average, 
                         have a good correlation. These results suggest that the memory of 
                         the large-scale dynamics from the previous day can be used to 
                         estimate the cloud fraction as well as the water content, which is 
                         a variable of the cloud itself. In general, the SAM satisfactorily 
                         simulated the interaction between cloud-radiation as well as 
                         dynamic and thermodynamic variables of the atmosphere during the 
                         periods of this study, being able to obtain atmospheric variables 
                         that are impossible to obtain in an observational way.",
                  doi = "10.5194/acp-22-15509-2022",
                  url = "http://dx.doi.org/10.5194/acp-22-15509-2022",
                 issn = "1680-7316 and 1680-7324",
             language = "en",
           targetfile = "acp-22-15509-2022.pdf",
        urlaccessdate = "05 maio 2024"
}