Performance evaluation of AR5-CMIP5 models for the representation of seasonal and multi-annual variability of precipitation in Brazilian hydropower sector basins under RCP8.5 scenario

Projections of climate change in streamflow and affluent natural energy in the Brazilian hydroelectric sector of CORDEX models

“…For, in most cases, the declivity module is always greater for the RCP 8.5 scenario in comparison to the RCP 4.5 one. These results are similar to the ones obtained by Silveira et al (2014Silveira et al ( , 2016Silveira et al ( , 2019 with CMIP5 data. In the North and Southeast/Midwest sectors, most models and stations indicated a negative trend in the annual naturalized streamflows and NEA in both scenarios.…”

“…In the South sector, however, most models indicated an annual naturalized streamflows and NEA increase (see Figures 5, 6 and 7), with some models and model medians, respectively, presenting magnitudes greater than 5%. The possible increase in naturalized streamflows projections for the South sector had already been demonstrated in previous works using data from the CMIP3 and CMIP5 models, the works of Silveira et al (2014Silveira et al ( , 2016Silveira et al ( , 2019 and Ribeiro Neto et al (2016) are examples. As well as in the period 2010-2039, in the period 2040-2069, the annual NEA and naturalized streamflows average percentage anomalies also indicated a reduction for most NIS models and stations for all sectors and scenarios.…”

“…This model has been successfully used in several studies that analyse the climatic and hydrological variables, mainly for corrections of modeled precipitation data, although, it can also be applied in the estimated ETP (Fernandes et al, 2017;Silveira et al, 2016Silveira et al, , 2019. In this study, two gamma CDF functions were necessarily used due to the elaboration of the probability mapping for the bias correction in the monthly time series of precipitation and ETP of the CORDEX RCM for the 24 basins representing the NIS; the first function was obtained through modeled data and the second through observed data.…”

“…Using data from these CMIP models, coupled with hydrological models, several studies have analized the projections of the climate change impact on water and energy resources in South America and especially in Brazil (Gondim et al, 2018;Ho et al, 2016;Mendes et al, 2017;Ribeiro Neto et al, 2016;Oliveira et al, 2017;Sorribas et al, 2016;Silveira et al, 2019). In the work of Oliveira et al (2017), for example, the impacts of climate change on streamflows and hydropower potential in the Rio Grande basin headwaters, southeastern Brazil, were evaluated.…”

Influência Da Variabilidade Climática Decadal Na Disponibilidade Hídrica E Energética Da Usina De Sobradinho

“…A disponibilidade de água no Brasil depende em grande parte do clima. O ciclo anual das chuvas e de vazões no país varia entre bacias, e de fato a variabilidade interanual do clima, associada aos fenômenos de El Niño, La Niña, ou à variabilidade na temperatura da superfície do mar (TSM) do Atlântico Tropical e Sul podem gerar anomalias climáticas, que produzem grandes secas, como em 1877, 1983 e 1998 no Nordeste, 2004-2006no Sul do Brasil, 2001no Centro-Oeste e Sudeste, e em 1926, 1983, 1998e 2005na Amazônia (Marengo e Nobre, 2004Marengo et al, 2012;Silva, 2013), assim como projeções de secas futuras (da Costa et al, 2018;Marcos Junior et al, 2018;Silveira et al, 2019;da Silva, 2020).…”