Regional climate models have been used since 1989 in order to improve climate simulation in regions where mesoscale forcings modulate the regional climate. These models are driven by time‐dependent ...lateral boundary conditions from global climate models or reanalysis, and this process is called dynamical downscaling. Here, we review the evolution of regional climate modeling, as well as present the studies developed for South America.
Regional climate models have been used since 1989 in order to improve climate simulation in regions where the mesoscale forcings modulate the regional climate. These models are driven by time‐dependent lateral boundary conditions from global climate models or reanalysis, and this process is called dynamical downscaling. Here, we review the evolution of regional climate modeling as well as present the studies developed for South America.
Future climate projections focusing on precipitation and water resource trends over South America (SA) are investigated using two ensembles. One of them is composed of three global climate models ...(GCMs), and the other of eight regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX). The present (1970–2005) and the future (2006–2100) climate trends are analyzed for representative pathway scenarios 4.5 (RCP4.5) and 8.5 (RCP8.5). For the most pessimistic scenario (RCP8.5), trends in water resources are assessed considering the terrestrial branch of the hydrologic cycle by analyzing the precipitation minus evapotranspiration (P-ET). For the present climate, RCMs added value to the GCMs in simulating more realistic precipitation fields in several regions. GCMs and RCMs project, in general, the same precipitation change signal for the end of the 21st century over SA, which is stronger in RCP8.5 than in RCP4.5. For RCP8.5 in most regions, GCMs and RCMs ensembles have the same precipitation trend signal, but a great spread between the ensemble members, which is greater in austral summer than winter, can be noted. In winter a negative trend in rainfall in most members and regions predominates. At the end of the 21st century, relative changes in rainfall in RCP8.5 are in the range of +14% (over northeastern Brazil in summer) to − 36% (over the Andes Mountains in winter). In RCP8.5, the ensembles project an increase in air temperature with a similar magnitude, while in RCP4.5 the trends are weaker. For air temperature, there is small spread between members, and the positive trend is statistically significant for all ensemble members in the RCP8.5 scenario. In terms of water resources, on an annual scale, for RCP8.5 the RCM ensemble projects a larger area with wetter conditions in the future than GCMs. Regionally, it is expected a decrease in water availability in the Amazon basin and an increase over northeast Brazil and southeast SA during the summer. In other regions (northern Amazon, the Andes Mountains and Patagonia) the ensembles indicate drier conditions in the future winter, except in southern Amazon. It is expected that such information could be useful for devising adaptation and mitigation policies due to climate change over the SA.
Renewable energy is key for the development of African countries, and knowing the best location for the implementation of solar and wind energy projects is important within this context. The purpose ...of this study is to assess the impact of climate change on solar and wind energy potential over Africa under low end (RCP2.6) and high end (RCP8.5) emission scenarios using a set of new high resolution (25 km) simulations with the Regional Climate Model version 4 (RegCM4) produced as part of the CORDEX-CORE initiative. The projections focus on two periods: (i) the near future (2021–2040) and ii) the mid-century future (2041–2060). The performance of the RegCM4 ensemble mean (Rmean) in simulating relevant present climate variables (1995–2014) is first evaluated with respect to the ERA5 reanalysis and satellite-based data. The Rmean reproduces reasonably well the observed spatial patterns of solar irradiance, air temperature, total cloud cover, wind speed at 100 m above the ground level, photovoltaic power potential (PVP), concentrated solar power output (CSPOUT) and wind power density (WPD) over Africa, though some biases are still evident, especially for cloud-related variables. For the future climate, the sign of the changes is consistent in both scenarios but with more intense magnitude in the middle of the century RCP8.5 scenario. Considering the energy variables, the Rmean projects a general decrease in PVP, which is more pronounced in the mid-century future and under RCP8.5 (up to 2%). Similarly, a general increase in CSPOUT (up to 2%) is projected over the continent under both the RCP2.6 and RCP8.5 scenarios. The projection in WPD shows a similar change (predominant increase) in the near and mid-century future slices under both RCPs with a maximum increase of 20%. The present study suggests that the RCP2.6 emission scenario, in general, favours the implementation of renewable energy in Africa compared to the RCP8.5.
In this study we analyse the climatic impact over South America due to Amazon deforestation for positive (PDO+) and negative (PDO−) PDO phases. The regional climatic model RegCM4 was run from 1968 to ...2003 for the domain including a great area of the Pacific Ocean and South America, using 50 km as spatial resolution. The Amazon deforestation scenario is that one extrapolated to the 2050 year. Under deforestation, the results show precipitation depletion over the extreme northern South America and precipitation increase over areas to the south, including deforested pixels and east‐southern sectors. These changes are more intense and occupy larger areas during the rainy season. Simulations also indicate that deforestation may impose a drier corridor following the Andes Mountains oriental slopes, from northwestern to south‐southeastern South America, in the rainy season. The impact from deforestation in distinct PDO phases presents the greatest signals over central‐southern South America, in a northwest–southeast direction. Over southeast Brazil, deforestation presents a slightly northeastward displacement of the PDO+ positive precipitation anomalies, intensifying the precipitation anomalies in the north sector and weakening over the south sector. The deforestation effects are more intense in the rainy season and have opposite signals between PDO+ and PDO−. Over the southeast South America, deforestation provides a weaker signal on PDO+ negative precipitation than in PDO−. The increased air temperature over the northern South America, near the northern coast, due to the joint effect of deforestation and PDO variability is more evident during PDO+ dry season than PDO− rainy season. This study illustrates the importance of considering long‐term climate simulations to better understand the role of deforestation in the lower frequency variability over South America.
South America precipitation impact due to Amazon deforestation on rainy season. The 850 hPa wind streamline climatology (1970–2003) is plotted.
This study investigates the influence of upper‐level potential vorticity (PV) structures on surface cyclogenesis in central‐eastern South America using 1979–2017 ERA‐Interim reanalysis data. Surface ...cyclones are identified in three regions (Argentina, Uruguay and SEBrazil) and it is quantified how often PV streamers and PV cutoffs co‐occur with cyclogenesis events. There are interesting regional and seasonal differences: in Argentina PV streamers occur mainly with cyclogenesis in summer, and in Uruguay and SEBrazil in both summer and winter. In the three regions, PV streamers associated with cyclogenesis occur most frequently at 320 K, except for summer in SEBrazil, where they predominate at 340 K. PV cutoffs occur with lower frequencies than PV streamers during cyclogenesis, and they occur more often in summer than in winter in all three regions. The dynamics of cyclogenesis differs among the three regions in some important aspects. In Argentina, the environment is slightly more baroclinic in summer and genesis occurs beneath the equatorial entrance of a jet streak. In this season, the anomalous PV associated with a PV streamer is important to favour ascent in the baroclinic environment contributing to surface cyclogenesis. Similar patterns occur for cyclogenesis in summer and winter in Uruguay, and in winter in SEBrazil. In Argentina during winter, cyclogenesis is located beneath the poleward exit of a jet streak, with a weaker PV streamer upstream. In SEBrazil during summer, the jet stream is far displaced from the genesis region and cyclogenesis occurs in a more barotropic environment.
Cyclone studies over South America have been increased in the last decades. There are large interests to understand the development of cyclones and their projection in future climate. Nevertheless, there is still a lack of information on how the upper part of the troposphere interacts with surface cyclones. Hence, this study aims in to better understand the influence of upper‐level potential vorticity forcing on the dynamic aspects of surface cyclones over centre‐eastern South America in a climatological perspective.
This study applies a Lagrangian approach to identify the origin of moisture for subtropical cyclones (SCs) along their tracks in the South Atlantic Ocean (SAO) basin from 1980 to 2015. The analysis ...shows that the local evaporation cannot fully explain the moisture gained by SCs, highlighting the role of external sources in moisture support, mainly through the northeasterly winds associated with the South Atlantic Subtropical Anticyclone. Overall, the northwestern SAO was the principal moisture source for SCs. It was noticeable that its contribution (~40%–45%) remained quasi‐constant during the year. Conversely, the moisture supplied from the northeastern SAO, southwestern SAO and the terrestrial source southeastern Brazil exhibited a marked seasonal variability. While contributions from the southwestern SAO intensify (weaken) in austral winter (summer), the southeastern Brazil source is more intense (weak) in summer (winter). In addition, SCs predominantly gain atmospheric humidity from sources close to their position, which reduces the mean water vapor residence time to ~3.2 days. Interestingly, we also found that ~42%–47% of the moisture that reached the SCs precipitates. These findings constitute a further step toward improving our knowledge of mechanisms underlying SC activity in the SAO basin.
The moisture transport by northeasterly winds is crucial for the activity of subtropical cyclones in the South Atlantic Ocean.The northwestern South Atlantic Ocean is the main moisture source for subtropical cyclogenesis maintaining a quasi‐constant contribution (~40%–45%) throughout the year.Approximately 42%–47% of the moisture gained by subtropical cyclones becomes precipitation.
Oceanic heat sources disturb the atmosphere, which, to come back to its initial state, disperses waves. These waves affect the climate in remote regions, characterizing the teleconnection patterns. ...In this study, we describe eight teleconnection patterns that affect South America climate: the El Niño–Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Atlantic Multidecadal Oscillation (AMO), the Tropical Atlantic Dipole (TAD), the South Atlantic Dipole (SAD), the Southern Annular Mode (SAM), the Madden–Julian Oscillation (MJO), and the Indian Ocean Dipole (IOD). Precipitation and winds at 850‐hPa anomalies, considering these teleconnection patterns in ENSO neutral periods, are also presented. Overall, southeastern South America and the north sector of the North and Northeast regions of Brazil are the most affected areas by the teleconnection patterns. In general, there is a precipitation dipole pattern between these regions during each teleconnection pattern.
In this study, we describe eight teleconnection patterns that affect South American climate: the El Niño–Southern Oscillation, the Pacific Decadal Oscillation, the Atlantic Multidecadal Oscillation, the Tropical Atlantic Dipole, the South Atlantic Dipole, the Southern Annular Mode, the Madden–Julian Oscillation, and the Indian Ocean Dipole. Considering these teleconnection patterns in ENSO neutral periods, precipitation and winds at 850‐hPa anomalies are also presented. Overall, southeastern South America and north of the North and Northeast regions of Brazil are the most affected areas by the teleconnection patterns. In general, a precipitation dipole pattern exits between these regions during each teleconnection pattern.
In this study, we estimated near‐surface wind speed 100‐year return values over the southwestern South Atlantic Ocean, using present‐day (1979–2018) simulations from the regional climate models ...(RCMs) WRF and RegCM4. Extreme wind events, associated with hazardous conditions over coastal and oceanic areas, must be well represented in numerical models for risk assessment, and few studies focused on the added value offered by RCMs to wind extremes. Events were selected with the peaks‐over‐threshold method and extremes were calculated by fitting peaks to a generalized Pareto distribution. For the assessment of model performance, we used the satellite‐based dataset from the Cross‐Calibrated Multi Platform (CCMP), which has great agreement with in situ observations. While modern reanalysis underestimated higher wind speed quantiles, the CCMP was able to represent these quantiles. Dynamical downscaling with the WRF (RegCM4) indicates an underestimation (overestimation) of wind speed for upper quantiles. To mitigate the effects of these differences in the extreme value estimate, we applied a linear adjustment in the simulated wind speed using the CCMP as reference. This application reduced the bias for higher wind speeds in simulations for all regions, except over the coastal area near Argentina and Uruguay, where downscaling already realistically represents extreme events. The spatial distribution of the simulated extremes is compatible with previous results based on reanalysis and satellite data, although with finer‐scale structure, especially over the southern South Atlantic, a region frequently affected by cyclone occurrence and extreme near‐surface winds. The extreme wind speed maps estimated for 100 years reflect these conditions with values reaching around 30 m·s−1 in the area, even after the wind adjustment. Besides, the fine‐scale features aggregate important new information related to extreme winds in the region, which is a relevant added value in the study of return values estimates.
We estimated 10‐m wind return values over the southwestern South Atlantic Ocean using simulations from two regional models (figure), WRF (black) and RegCM4 (red), assessed with a calibrated satellite data (CCMP). Dynamical downscaling with the WRF (RegCM4) underestimates (overestimates) higher winds. We reduced the biases with a linear adjustment in the simulated wind speed using the CCMP as reference. Simulated extremes agrees with previous studies and shows finer‐scale structures over regions frequently affected by cyclones and storms.
The eastern coast of South America is a cyclogenetic region in terms of extratropical cyclones and, in lower number, of subtropical cyclones that are more frequent in austral summer and autumn. ...However, in June 2021, an unusual cyclone developed near the boundary of Uruguay and southern Brazil, initially having extratropical features and later undergoing a subtropical transition. At 1200 UTC 29 June, the Brazilian Navy named it as subtropical cyclone Raoni. This study aims to describe the synoptic evolution of the cyclone and address physical drivers for the subtropical transition based on the ECMWF‐ERA5 reanalysis and numerical experiments with the WRF model. The cyclone precursor of Raoni had its genesis at 1800 UTC 26 June 2021 forced by a trough at mid–upper levels that crossed the Andes Mountains and caused a rapid surface pressure drop. Less than 24 hr later, the cyclone presented a frontal T‐bone pattern and warm seclusion, following the Shapiro–Keyser development model. Strong surface heat fluxes, a deep moist troposphere, and the vertical alignment of the warm seclusion with an upper‐level cut‐off pattern provided the adequate environment for organising convection and, consequently, for subtropical transition at 0600 UTC 28 June. The fundamental role of the surface turbulent heat fluxes for the transition is confirmed through numerical experiments. This study is unprecedented in the sense that no subtropical cyclone originating from a warm seclusion has been documented over the South Atlantic before. These findings emphasise the need of monitoring cold‐season extratropical Shapiro–Keyser cyclones in the region since they can evolve to a subtropical or tropical cyclone and can cause damage to the maritime activities and coastal region due to the strong winds.
In June 2021, an unusual cyclone developed near the boundary of Uruguay and southern Brazil. Initially, it had extratropical features similar to the Shapiro–Keyser cyclone model and later underwent a subtropical transition. Cyclogenesis was forced by a trough at mid–upper levels that crossed the Andes and caused deepening of the surface pressure. Strong surface heat fluxes, a moist deep troposphere and the vertical alignment of the warm seclusion and an upper‐level blocking pattern are the main drivers that led to the subtropical transition.
In this study, multi-model ensembles are used to understand regional features of future climate trends of cyclones and associated winds in eastern South America. For this, we consider three ...cyclogenetic hot-spot regions located in south-southeastern Brazil, extreme southern Brazil-Uruguay, and southern Argentina, named, respectively, RG1, RG2 and RG3. The multi-model ensembles consist of four RegCM4 downscalings (RegCM4s) nested in three different global circulation models (GCMs) from CMIP5 under RCP8.5 for the period 1979–2100. ERA-Interim, and CFSR provide the reanalyses ensemble. For the present climate (1979–2005), RegCM4s and GCMs simulate the main characteristics of the cyclone’s genesis and propagation. There is greater agreement between RegCM4s and reanalyses regarding the magnitude and location of stronger winds associated with intense cyclones starting in RG1 and RG2. An important added value is the greater ability of RegCM4s to capture the observed features (phase and amplitude of the annual cycle, intensity, and near surface winds) of cyclogenesis starting in regions away from the boundary domain, such as in RG1 and RG2. In these regions, RegCM4s present smaller (higher) error (correlation) for the frequency of cyclones than GCMs, which improves the representation of cyclones for the whole southwestern South Atlantic domain. RegCM4s are able to simulate in greater agreement with reanalysis than GCMs, the initially stronger cyclones and associated low level winds. For these intense cyclones in the future climate, an intensification of low-level winds off the coast (south-southeast Brazil and south Argentina) and a shift to the south of the upper-level polar jet are projected. Furthermore, there is a clear trend towards decrease in the number of cyclogeneses in each hot-spot region, indicating that each intense cyclone will be associated with stronger low level winds near the eastern South America coast at the end of the twenty-first century.
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