Assessment of dry and heavy rainfall days and their projected changes over Northeast Brazil in Coupled Model Intercomparison Project Phase 6 models

Abstract

The Northeast Brazil (NEB) is considered a region that is strongly vulnerable to extreme rainfall events due to climate change. In this context, this study evaluates the performance of 12 general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in representing the number of dry (DD) and heavy rainfall days (HRD) over NEB in the historical period and their projections for the near (2016-2040) and far future (2076-2100) under three Shared Socioeconomic Pathways (SSP2-4.5, SSP3-7.0 and SSP5-8.5) scenarios. For selection of extreme rainfall days, we used the absolute threshold of less than 1 mm for DD and the 99th percentile for HRD. The results indicate that four (three) models show an overall superior performance in reproducing the dry (heavy rainfall) days, being common in both aspects only the EC-EARTH3. Thus, the skill of the CMIP6 models for NEB varies according to the extreme rainfall conditions analysed. For the future climate (near and far), results show that dry days are project to increase over the entire NEB territory, especially during DJF and MAM and more pronounce in the east coast, with projections that these conditions will be more severe under the SSP5-8.5 scenario. The number of dry days may increase up to 15%. For HRD, although the results indicate that the number of days with heavy precipitation will be more frequent in the future (the increase can exceed 140%), the analysis show that under the low (SSP2-4.5) or intermediate (SSP3-7.0) forcing scenarios the HRD tends to be higher than in the most pessimistic scenario (SSP5-8.5). Such result was explained according to the dryness of the atmosphere. Therefore, this study shows that it might either rain too much within a short range of time or the water scarcity will be longer-lasting in the future in NEB. K E Y W O R D S climate change, climate projections, CMIP models, extreme events, percentile 1 | INTRODUCTION The Northeast Brazil (NEB) is a region characterized by high spatial-temporal rainfall variability (Kousky, 1979; Luiz-Silva et al., 2021) due to the actions of different atmospheric systems, such as Intertropical Convergence Zone (ITCZ;

Current and Future Climate Extremes Over Latin America and Caribbean: Assessing Earth System Models from High Resolution Model Intercomparison Project (HighResMIP)

“…On the other hand, the models and the observations show high consistency in increasing drought events in the NES region. All of the above align with previous studies (Almeida et al 2017 ; da Silva et al 2019 ; Olmo and Bettolli 2021 ; Solman et al 2021 ; Medeiros and Oliveira 2022 ).…”

“…15 . Studies that have found similar results (Ge et al 2021 ; Medeiros and Oliveira 2022 ; Santos et al 2019 ) conclude that this could imply a potential risk of intensified extreme rainfall, which would accentuate the vulnerability of various socioeconomic sectors, such as agriculture, water management, forests and, disasters preparedness.

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“…The intensification of temperature warm extreme events may increase heat stress vulnerability (Lapola et al 2019 ). Likewise, the projected increase in the extreme precipitation climate indices elevates the risk of heavy rainfall and landslides and indicates that dry spells may be long-lasting in the near future due to climate change (Debortoli et al 2017 ; Marengo et al 2017 ; Medeiros and Oliveira, 2022 ). This is consistent with much of what we have experienced over the twentieth and early twenty-first centuries due to a strongly globalized, fossil-fueled society (Chen and Sun 2021 ; Riahi et al 2017 ).…”

“…Understanding the dynamics and trends in extreme climate events provides vital information to help policymakers establish actions necessary to combat climate change and its impacts. Providing reliable information regarding historical and future projections of such events represents an enormous challenge for climate researchers (McPhillips et al 2018 ; Medeiros and Oliveira 2022 ; Mistry 2019 ; Mysiak et al 2018 ; Santos et al 2017 ). Previous studies have investigated the historical evolution of climate extremes in different parts of the world, including Latin America and the Caribbean, using the set of indices established by the Expert Team on Climate Change Detection and Indices (ETCCDI) (Aguilar et al 2005 ; Avila-Diaz et al 2020b ; Cornes and Jones 2013 ; Donat et al 2013 , 2016 ; Dunn et al 2020 ; Gouveia et al 2022 ; Kitoh and Endo 2016 ; Nakaegawa et al 2014 ; Skansi et al 2013 ; Zilli et al 2017 ).…”

“…In a recent study, Akinsanola et al ( 2020 ) found that MME from CMIP6 performs better than most individual models in capturing precipitation extremes at a seasonal scale over the United States. On the other hand, most regional studies indicated that to assess the ability of CMIP models to capture the variability of climate extremes, it is necessary to evaluate the performance of individual models to identify the shortcomings (Akinsanola et al 2020 ; Avila-Diaz et al 2020b ; Medeiros and Oliveira 2022 ; Rivera and Arnould 2020 ).…”