Extreme climate indices in Brazil: evaluation of downscaled earth system models at high horizontal resolution

• Published in: Climate dynamics Vol. 54; no. 11-12; pp. 5065 - 5088
• Main Authors: Avila-Diaz, Alvaro, Abrahão, Gabriel, Justino, Flavio, Torres, Roger, Wilson, Aaron
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2020; Springer; Springer Nature B.V
• Subjects: Aeronautics; Analysis; basins; Brazil; Climate; Climate models; Climatic extremes; Climatic indexes; Climatology; Computer simulation; data collection; Datasets; dynamics; Earth; Earth and Environmental Science; Earth Sciences; Earth system science; Geophysics/Geodesy; Intercomparison; latitude; longitude; National Aeronautics and Space Administration; Oceanography; Performance evaluation; Precipitation (Meteorology); Regional climate models; Regional climates; Resolution; River basins; Space research; Statistical analysis; temperature; South America; Brazil; CMIP5; Climate extremes; Model evaluation; Performance metrics; Trends
• DOI: 10.1007/s00382-020-05272-9
• ISSN: 0930-7575

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.