TY - JOUR
T1 - Extreme climate indices in Brazil
T2 - evaluation of downscaled earth system models at high horizontal resolution
AU - Avila-Diaz, Alvaro
AU - Abrahão, Gabriel
AU - Justino, Flavio
AU - Torres, Roger
AU - Wilson, Aaron
N1 - Funding Information:
The authors would like to thank the Universidade Federal de Viçosa. This work was supported by Minas Gerais Research Foundation (FAPEMIG) and to the Coordination for the Improvement of Higher Education Personnel (CAPES). The authors thank to the Byrd Polar and Climate Research Center. The authors are grateful to the climate simulations used from National Institute for Space Research (INPE), and we thank NEX-GDDP dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS). The authors further thank Alexandre Xavier, Carey King, and Bridget Scanlon that provided a gridded observational dataset used in this work.
Funding Information:
The authors would like to thank the Universidade Federal de Vi?osa. This work was supported by Minas Gerais Research Foundation (FAPEMIG) and to the Coordination for the Improvement of Higher Education Personnel (CAPES). The authors thank to the Byrd Polar and Climate Research Center. The authors are grateful to the climate simulations used from National Institute for Space Research (INPE), and we thank NEX-GDDP dataset, prepared by the Climate Analytics Group and NASA Ames Research Center using the NASA Earth Exchange, and distributed by the NASA Center for Climate Simulation (NCCS). The authors further thank Alexandre Xavier, Carey King, and Bridget Scanlon that provided a gridded observational dataset used in this work.
Publisher Copyright:
© 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - This study evaluated the performance of 25 earth system models (ESMs), statistically and dynamically downscaled to a high horizontal resolution (0.25° of latitude/longitude), in simulating extreme climate indices of temperature and precipitation for 1980–2005. Datasets analyzed include 21 statistically downscaled ESMs from the National Aeronautics and Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) and dynamically downscaled Eta Regional Climate Model simulations driven by 4 ESMs generated by the Brazilian National Institute for Space Research (INPE). Downscaled outputs were evaluated against observational gridded datasets at 0.25° resolution over Brazil, quantifying the skill in simulating the observed spatial patterns and trends of climate extremes. Results show that the downscaled products are generally able to reproduce the observed climate indices, although most of them have poorest performance over the Amazon basin for annual and seasonal indices. We find larger discrepancies in the warm spell duration index for almost all downscaled ESMs. The overall ranking shows that three downscaled models (CNRM-CM5, CCSM4, and MRI-CGCM3) perform distinctively better than others. In general, the ensemble mean of the statistically downscaled models achieves better results than any individual models at the annual and seasonal scales. This work provides the largest and most comprehensive intercomparison of statistically and dynamically downscaled extreme climate indices over Brazil and provides a useful guide for researchers and developers to select the models or downscaling techniques that may be most suitable to their applications of interest over a given region.
AB - This study evaluated the performance of 25 earth system models (ESMs), statistically and dynamically downscaled to a high horizontal resolution (0.25° of latitude/longitude), in simulating extreme climate indices of temperature and precipitation for 1980–2005. Datasets analyzed include 21 statistically downscaled ESMs from the National Aeronautics and Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) and dynamically downscaled Eta Regional Climate Model simulations driven by 4 ESMs generated by the Brazilian National Institute for Space Research (INPE). Downscaled outputs were evaluated against observational gridded datasets at 0.25° resolution over Brazil, quantifying the skill in simulating the observed spatial patterns and trends of climate extremes. Results show that the downscaled products are generally able to reproduce the observed climate indices, although most of them have poorest performance over the Amazon basin for annual and seasonal indices. We find larger discrepancies in the warm spell duration index for almost all downscaled ESMs. The overall ranking shows that three downscaled models (CNRM-CM5, CCSM4, and MRI-CGCM3) perform distinctively better than others. In general, the ensemble mean of the statistically downscaled models achieves better results than any individual models at the annual and seasonal scales. This work provides the largest and most comprehensive intercomparison of statistically and dynamically downscaled extreme climate indices over Brazil and provides a useful guide for researchers and developers to select the models or downscaling techniques that may be most suitable to their applications of interest over a given region.
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U2 - 10.1007/s00382-020-05272-9
DO - 10.1007/s00382-020-05272-9
M3 - Article
AN - SCOPUS:85085146984
SN - 0930-7575
VL - 54
SP - 5065
EP - 5088
JO - Climate Dynamics
JF - Climate Dynamics
IS - 11-12
ER -
