@InProceedings{AlvesMaBeJoKaCh:2009:EnClMo,
author = "Alves, Linconl Muniz and Marengo, Jos{\'e} Ant{\^o}nio and
Betts, Richard and Jones, Richard and Kay, Gillian and Chan, Sin
Chou",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Met Office Hadley
Centre} and {Met Office Hadley Centre} and {Met Office Hadley
Centre} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Large-scale changes in precipitation and temperature in South
America under climate change - ensemble climate model projections
and uncertainty assessments",
year = "2009",
organization = "International Conference on Southern Hemisphere Meteorology and
Oceanography, 9.",
keywords = "x.",
abstract = "Following the extensive conclusions from the IPCC
(Intergovernmental Panel on Climate Change) Fourth Assessment
Report and other reports (including INPEs report 2007 -
ww.cptec.inpe.br/mudancas_climaticas) we have credible evidence
that the climate is changing across the world. But it is important
to note that while the current versions of atmosphereocean general
circulation models (AOGCMs) have the ability to simulate well the
state of the global climate at the large and continental scales,
there are significant variations between these models in future
climate projections of precipitation and temperature changes at
the regional scale, including those for South America. One of the
top priorities for narrowing gaps between current knowledge and
policymaking needs is the quantitative assessment of the
sensitivity, adaptive capacity and vulnerability of human and
natural systems to climate change. Vital for such assessments are
reliable estimates of current and future climate variability at
the regional scale which can be readily used to assess the
sensitivity of these systems to climate change. Often an important
requirement for these assessments is for the climate data to be
provided at high spatial and temporal resolution, and the main
method for providing these data regionally is dynamical
downscaling, i.e. output from global climate models is used to
drive a high resolution regional climate model. Regional models
1provide improved spatial detail, but in order to improve
reliability of projections, it is essential to run multiple
realizations, to take uncertainties into account. There has been
much effort to quantify the range of uncertainties that are known
to exist in global climate model projections and dynamical
downscaling allows a detailed exploration of these. Important for
the interpretation of any downscaled projections is to assess the
regional-scale climate and climate changes in the global
projections. This can guide the selection of suitable global
models for driving the regional model where the quality of global
model control simulations and the identification of global model
large-scale projected changes which are considered reliable would
be relevant information. As a starting point for this, in the
present paper, we present the results of an ensemble simulation of
the HadCM3 climate model, where each ensemble member incorporates
different but plausible versions of the parameterizations of
important physical processes. This is used to assess the potential
impacts of climate change on precipitation and temperature over
South America and explore the range in projections obtained via
the modifications to the model parameterizations.",
conference-location = "Melbourne Australia",
conference-year = "9 - 13 Feb",
language = "en",
targetfile = "pdf_branco.pdf",
urlaccessdate = "04 maio 2024"
}