@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 = "28 abr. 2024"
}