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@Article{MartinsRandOlivDolm:2015:PrAmRe,
               author = "Martins, Guilherme and von Randow, Celso and Oliveira, Gilvan 
                         Sampaio de and Dolman, Han A. J.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Vrije Universiteit Amsterdam}",
                title = "Precipitation in the Amazon and its relationship with moisture 
                         transport and tropical Pacific and Atlantic SST from the CMIP5 
                         simulation",
              journal = "Hydrology and Earth System Sciences Discussions",
                 year = "2015",
               volume = "12",
               number = "1",
                pages = "671--704",
             abstract = "Studies on numerical modeling in Amazonia show that the models 
                         fail to capture important aspects of climate variability in this 
                         region and it is important to understand the reasons that cause 
                         this drawback. Here, we study how the general circulation 5 models 
                         of the Coupled Model Intercomparison Project Phase 5 (CMIP5) 
                         simulate the inter-relations between regional precipitation, 
                         moisture convergence and Sea Surface Temperature (SST) in the 
                         adjacent oceans, to assess how flaws in the representation of 
                         these processes can translate into biases in simulated rainfall in 
                         mazonia. Using observational data (GPCP, CMAP, ERSST.v3, ERAI and 
                         evapotranspiration) and 21numerical simulations from CMIP5 during 
                         the present climate (19792005) in June, July and August (JJA) and 
                         December, January and February (DJF), respectively, to represent 
                         dry and wet season characteristics, we evaluate how the models 
                         simulate precipitation, moisture transport and convergence, and 
                         pressure velocity (omega) in different regions of Amazonia. Thus, 
                         it is possible to identify areas of Amazonia that are more or less 
                         influenced by adjacent ocean SSTs. Our results showed that most of 
                         the CMIP5 models have poor skill in adequately representing the 
                         observed data. The regional analysis of the variables used showed 
                         that the underestimation in the dry season (JJA) was twice in 
                         relation to rainy season as quantified by the Standard Error of 
                         the Mean (SEM). It was found that Atlantic and Pacific SSTs 
                         modulate the 20 northern sector of Amazonia during JJA, while in 
                         DJF Pacific SST only influences the eastern sector of the region. 
                         The analysis of moisture transport in JJA showed that moisture 
                         preferentially enters Amazonia via its eastern edge. In DJF this 
                         occurs both via its northern and eastern edge. The moisture 
                         balance is always positive, which indicates that Amazonia is a 
                         source of moisture to the atmosphere. Additionally, our results 
                         showed that during DJF the simulations in northeast sector of 
                         Amazonia have a strong bias in precipitation and an 
                         underestimation of moisture convergence due to the higher 
                         influence of biases in the Pacific SST. During JJA, a strong 
                         precipitation bias was observed in the southwest sector 
                         associated, also with a negative bias of mois-ture convergence, 
                         but with weaker influence of SSTs of adjacent oceans. The poor 
                         representation of precipitation-producing systems in Amazonia by 
                         the models and the difficulty of adequately representing the 
                         variability of SSTs in the Pacific and Atlantic oceans may be 
                         responsible for these underestimates in Amazonia.",
                  doi = "10.5194/hessd-12-671-2015",
                  url = "http://dx.doi.org/10.5194/hessd-12-671-2015",
                 issn = "1812-2108",
             language = "en",
        urlaccessdate = "25 nov. 2020"
}


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