Abstract
AbstractGeneral Circulation and Earth System Models are the most advanced tools for investigating climate responses to future scenarios of greenhouse gas emissions, playing the role of projecting the climate throughout the century. Nevertheless, climate projections are model-dependent and may show systematic biases, requiring a bias correction for any further application. Here, we provide a dataset based on an ensemble of 19 bias-corrected CMIP6 climate models projections for the Brazilian territory based on the SSP2-4.5 and SSP5-8.5 scenarios. We used the Quantile Delta Mapping approach to bias-correct daily time-series of precipitation, maximum and minimum temperature, solar net radiation, near-surface wind speed, and relative humidity. The bias-corrected dataset is available for both historical (1980–2013) and future (2015–2100) simulations at a 0.25° × 0.25° spatial resolution. Besides the gridded product, we provide area-averaged projections for 735 catchments included in the Catchments Attributes for Brazil (CABra) dataset. The dataset provides important variables commonly used in environmental and hydroclimatological studies, paving the way for the development of high-quality research on climate change impacts in Brazil.
Funder
Fundação de Amparo à Pesquisa do Estado de São Paulo
Ministry of Science, Technology and Innovation | Conselho Nacional de Desenvolvimento Científico e Tecnológico
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
Cited by
20 articles.
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