Analysis of climate extremes indices in tropical South America through the RegCM4.7

Abstract

In recent decades, the frequency and intensity of extreme weather events induced by global warming have increased significantly, exerting serious impacts on the development of society and ecosystems. Based on low (RCP2.6) and high (RCP8.5) greenhouse gas emissions scenarios from the Intergovernmental Panel on Climate Change, we use the general circulation model HadGEM2‐ES that is part of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to drive the regional climate model RegCM4.7. This study evaluated the ability of both models to simulate (1986–2005) and projection (2080–2099) spatio‐temporal features of extreme indices over tropical South America (TSA). Indices based on precipitation and daily maximum and minimum temperature follow the definitions of the Expert Team on Climate Change Detection and Indices (ETCCDI). In general, the RegCM4.7 reproduces accordingly the spatial distribution of the ETCCDI indices derived from precipitation and temperature on the TSA, in addition to added value to HadGEM2‐ES, especially over regions of complex topography. HadGEM2‐ES performs poorly along the west coast, due to the topography and altitude of the Andes. On the other hand, it demonstrates better performance in the Amazon Basin compared to RegCM4.7. The projection results showed that climate extreme indices based on precipitation and temperature indicate that drought events may advance to the end of the century, showing a spatial pattern that precipitation will be gradually reduced in the Amazon Basin and Northeast region of Brazil. Despite some discrepancies between the models, studies like this one help us to understand how climate change can affect regional planning and development.

Future precipitation projections for Brazil and tropical South America from a Convection-permitting climate simulation

“…High temporal and spatial resolution is crucial for the representation of precipitation in order to assess the risk from these climatological features and in addressing the need for reliable and actionable climate information to inform policy and decision makers (Marengo, Espinoza, et al, 2021;Senior et al, 2021). In recent years, a large number of studies have been conducted using projections of future precipitation change over Brazil derived from GCMs and regional climate models (RCMs), showing a future drying signal over the Amazon basin, combined with increasing rainfall intensity over most of Brazil (Avila-Diaz et al, 2020;da Silva et al, 2023). Future drying increases the risk of drought and fire over northern and northeastern Brazil (Marengo et al, 2017;Vieira et al, 2021), while higher intensities could lead to increased risk of landslides and flash floods in Southern and Southeastern Brazil and the coastal area of Northeast Brazil (Debortoli et al, 2017;Marengo, Camarinha, et al, 2021).…”

Predicting Changes in Population Exposure to Precipitation Extremes over Beijing–Tianjin–Hebei Urban Agglomeration with Regional Climate Model RegCM4 on a Convection-Permitting Scale

“…Climate models with high spatial resolutions can better simulate precipitation extremes as well as physical processes related to precipitation extremes, such as large-scale atmospheric rivers [5,[33][34][35][36] and tropical cyclones [37,38]. Regional climate models (RCMs) describe dynamic and physical processes in more detail due to their high resolutions and can better reproduce spatiotemporal patterns of precipitation extremes over Asia [4,8,12,39], Europe [13,40], North America and South America [41]. GCMs are generally used to generate initial and boundary conditions (high temporal resolution of three-dimensional atmospheric temperature, specific humidity, atmospheric pressure, horizontal wind, etc.)…”