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A better understanding of the relative roles of internal climate variability and external contributions, from both natural (solar, volcanic) and anthropogenic greenhouse gas forcing, is important to better project future hydrologic changes. Changes in the evaporative demand play a central role in this context, particularly in tropical areas characterized by high precipitation seasonality, such as the tropical savannah and semi-desertic biomes. Here we present a set of geochemical proxies in speleothems from a well-ventilated cave located in central-eastern Brazil which shows that the evaporative demand is no longer being met by precipitation, leading to a hydrological deficit. A marked change in the hydrologic balance in central-eastern Brazil, caused by a severe warming trend, can be identified, starting in the 1970s. Our findings show that the current aridity has no analog over the last 720 years. A detection and attribution study indicates that this trend is mostly driven by anthropogenic forcing and cannot be explained by natural factors alone. These results reinforce the premise of a severe long-term drought in the subtropics of eastern South America that will likely be further exacerbated in the future given its apparent connection to increased greenhouse gas emissions.

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The increase in greenhouse gasses (GHG) anthropogenic emissions and deforestation over the last decades have led to many chemical and physical changes in the climate system, affecting the atmosphere's energy and water balance. A process that could be affected is the Amazonian moisture transport in the South American continent (including La Plata basin), which is crucial to the southeast Brazilian water regime. The focus of our research is on evaluating how local (i.e. Amazon deforestation) and global forcings (increase of atmospheric GHG concentration) may modify this moisture transport under climate change scenarios. We used two coupled land-atmosphere models forced by CMIP6 sea surface temperatures to simulate these processes for two scenarios: i) increase in carbon dioxide (CO2) - RCP8.5 atmospheric levels (00DEF), and ii) total Amazon deforestation simultaneous with atmospheric CO2 levels increased (100DEF). These scenarios were compared with a control simulation, set with a constant CO2 of 388 ppm and present-day Amazon Forest cover. The 30-year Specific Warming Level 2 (SWL2) index evaluated from the simulations is set to be reached 2 years earlier due to Amazon deforestation. A reduction in precipitation was observed in the Amazon basin (-3.1 mm·day-1) as well as in La Plata Basin (-0.5 mm·day-1) due to reductions in the Amazon evapotranspiration (-0.9 mm·day-1) through a stomatal conductance decrease (00DEF) and land cover change (100DEF). In addition, the income moisture transport decreased (22 %) in the northern La Plata basin in both scenarios and model experiments. Our results indicated a worse scenario than previously found in the region. Both Amazon and La Plata hydrological regimes are connected (moisture and energy transport), indicating that a large-scale Amazon deforestation will have additional climate, economic and social implications for South America.

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This study presents novel insight into the mechanisms of Atlantic Meridional Overturning Circulation (AMOC) reduction and its recovery under a warmer climate scenario. An one-thousand-year-long numerical simulation of a global coupled ocean-ice-atmosphere climate model, subjected to a stationary atmospheric radiative forcing, depict a coherent picture of the Arctic sea ice melting as a trigger for the initial AMOC reduction, along with decreases in the northward fluxes of salt and heat. Further atmospheric-driven ocean processes contribute to an erosion of the stable stratification of the fresher, yet colder waters in the surface layers of the North Atlantic, contributing to the recovery of a permanently altered AMOC.

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Since 2012, the semiarid region of Northeast Brazil (NEB) has been experiencing a continuous dry condition imposing significant social impacts and economic losses. Characterizing the recent extreme drought events and uncovering the influence from the surrounding oceans remain to be big challenges. The physical mechanisms of extreme drought events in the NEB are due to varying interacting time scales from the surrounding tropical oceans (Pacific and Atlantic). From time series observations, we propose a three-step strategy to establish the episodic coupling directions on intraseasonal time scales from the ocean to the precipitation patterns in the NEB, focusing on the distinctive roles of the oceans during the recent extreme drought events of 2012-2013 and 2015-2016. Our algorithm involves the following: (i) computing drought period length from daily precipitation anomalies to capture extreme drought events; (ii) characterizing the episodic coupling delays from the surrounding oceans to the precipitation by applying the Kullback-Leibler divergence (KLD) of complexity measure, which is based on ordinal partition transition network representation of time series; and (iii) calculating the ratio of high temperature in the ocean during the extreme drought events with proper time lags that are identified by KLD measures. From the viewpoint of climatology, our analysis provides data-based evidence of showing significant influence from the North Atlantic in 2012-2013 to the NEB, but in 2015-2016, the Pacific played a dominant role than that of the Atlantic. The episodic intraseasonal time scale properties are potential for monitoring and forecasting droughts in the NEB in order to propose strategies for drought impacts reduction.

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For half a century, the process of economic integration of the Amazon has been based on intensive use of renewable and nonrenewable natural resources, which has brought significant basin-wide environmental alterations. The rural development in the Amazonia pushed the agricultural frontier swiftly, resulting in widespread land-cover change, but agriculture in the Amazon has been of low productivity and unsustainable. The loss of biodiversity and continued deforestation will lead to high risks of irreversible change of its tropical forests. It has been established by modeling studies that the Amazon may have two "tipping points," namely, temperature increase of 4 °C or deforestation exceeding 40% of the forest area. If transgressed, large-scale "savannization" of mostly southern and eastern Amazon may take place. The region has warmed about 1 °C over the last 60 y, and total deforestation is reaching 20% of the forested area. The recent significant reductions in deforestation-80% reduction in the Brazilian Amazon in the last decade-opens up opportunities for a novel sustainable development paradigm for the future of the Amazon. We argue for a new development paradigm-away from only attempting to reconcile maximizing conservation versus intensification of traditional agriculture and expansion of hydropower capacity-in which we research, develop, and scale a high-tech innovation approach that sees the Amazon as a global public good of biological assets that can enable the creation of innovative high-value products, services, and platforms through combining advanced digital, biological, and material technologies of the Fourth Industrial Revolution in progress.

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Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarém tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.

Apesar da redução na taxa de desmatamento nos últimos anos, o impacto do aquecimento global por si só pode causar alterações na cobertura vegetal. O Objetivo deste trabalho foi investigar as possíveis alterações no maior bioma brasileiro, a Floresta Amazônica, levando em consideração diferentes cenários de mudanças climáticas. Os modelos de vegetação dinâmica permitem representar as mudanças na distribuição de vegetação bem como nos processos biogeoquímicos diante de mudanças no clima. Na primeira parte do trabalho, o modelo de vegetação dinâmica Inland foi forçado com condições iniciais e de contorno geradas a partir de dados de reanálise (CFSR) e pela regionalização da simulação histórica de um modelo global do sistema terrestre (HadGEM2-ES) com o modelo Eta. Estas simulações foram validadas utilizando os dados da torre de Santarém-K83. Na segunda parte, avaliou-se o impacto de uma futura mudança climática sobre o bioma floresta através das projeções do modelo Inland forçado com um modelo regional climático. As projeções mostram que algumas áreas de floresta tropical na Amazônia são substituídas por tipo de floresta decídua e pastagem natural no cenário RCP4.5 e apenas por pastagem natural no cenário RCP8.5 no final do século XXI. No Estado do Amazonas, o modelo indica uma redução de cerca de 9% da área de floresta tropical no cenário RCP4.5 e uma redução maior no cenário RCP8.5 de cerca de 50%. Embora o aumento da concentração de CO2 atmosférico possa favorecer o crescimento das árvores, as projeções do modelo Eta-HadGEM2-ES mostram aumento da temperatura e redução da precipitação na região Amazônica, levando a degradação da floresta nestas simulações.

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Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarém tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.(AU)

Apesar da redução na taxa de desmatamento nos últimos anos, o impacto do aquecimento global por si só pode causar alterações na cobertura vegetal. O Objetivo deste trabalho foi investigar as possíveis alterações no maior bioma brasileiro, a Floresta Amazônica, levando em consideração diferentes cenários de mudanças climáticas. Os modelos de vegetação dinâmica permitem representar as mudanças na distribuição de vegetação bem como nos processos biogeoquímicos diante de mudanças no clima. Na primeira parte do trabalho, o modelo de vegetação dinâmica Inland foi forçado com condições iniciais e de contorno geradas a partir de dados de reanálise (CFSR) e pela regionalização da simulação histórica de um modelo global do sistema terrestre (HadGEM2-ES) com o modelo Eta. Estas simulações foram validadas utilizando os dados da torre de Santarém-K83. Na segunda parte, avaliou-se o impacto de uma futura mudança climática sobre o bioma floresta através das projeções do modelo Inland forçado com um modelo regional climático. As projeções mostram que algumas áreas de floresta tropical na Amazônia são substituídas por tipo de floresta decídua e pastagem natural no cenário RCP4.5 e apenas por pastagem natural no cenário RCP8.5 no final do século XXI. No Estado do Amazonas, o modelo indica uma redução de cerca de 9% da área de floresta tropical no cenário RCP4.5 e uma redução maior no cenário RCP8.5 de cerca de 50%. Embora o aumento da concentração de CO2 atmosférico possa favorecer o crescimento das árvores, as projeções do modelo Eta-HadGEM2-ES mostram aumento da temperatura e redução da precipitação na região Amazônica, levando a degradação da floresta nestas simulações.(AU)

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Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs.

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The carbon and water cycles for a southwestern Amazonian forest site were investigated using the longest time series of fluxes of CO2 and water vapor ever reported for this site. The period from 2004 to 2010 included two severe droughts (2005 and 2010) and a flooding year (2009). The effects of such climate extremes were detected in annual sums of fluxes as well as in other components of the carbon and water cycles, such as gross primary production and water use efficiency. Gap-filling and flux-partitioning were applied in order to fill gaps due to missing data, and errors analysis made it possible to infer the uncertainty on the carbon balance. Overall, the site was found to have a net carbon uptake of ≈5 t C ha(-1) year(-1), but the effects of the drought of 2005 were still noticed in 2006, when the climate disturbance caused the site to become a net source of carbon to the atmosphere. Different regions of the Amazon forest might respond differently to climate extremes due to differences in dry season length, annual precipitation, species compositions, albedo and soil type. Longer time series of fluxes measured over several locations are required to better characterize the effects of climate anomalies on the carbon and water balances for the whole Amazon region. Such valuable datasets can also be used to calibrate biogeochemical models and infer on future scenarios of the Amazon forest carbon balance under the influence of climate change.

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We developed a new world natural vegetation map at 1 degree horizontal resolution for use in global climate models. We used the Dorman and Sellers vegetation classification with inclusion of a new biome: tropical seasonal forest, which refers to both deciduous and semi-deciduous tropical forests. SSiB biogeophysical parameters values for this new biome type are presented. Under this new vegetation classification we obtained a consensus map between two global natural vegetation maps widely used in climate studies. We found that these two maps assign different biomes in ca. 1/3 of the continental grid points. To obtain a new global natural vegetation map, non-consensus areas were filled according to regional consensus based on more than 100 regional maps available on the internet. To minimize the risk of using poor quality information, the regional maps were obtained from reliable internet sources, and the filling procedure was based on the consensus among several regional maps obtained from independent sources. The new map was designed to reproduce accurately both the large-scale distribution of the main vegetation types (as it builds on two reliable global natural vegetation maps) and the regional details (as it is based on the consensus of regional maps).

Elaborou-se um novo mapa global de vegetação natural naresolução horizontal de 1 grau para uso em modelos climáticos de circulação geral. Utilizou-se a classificação de vegetação de Dorman e Sellers com a inclusão de um novo bioma: floresta tropical estacional, que compreende as florestas tropicais decíduas e semidecíduas. Para este novo tipo de bioma, apresentaram-se os valores de parâmetros biogeofísicos domodelo de processos à superfície SSiB. Sob essa nova classificação de vegetação, obteve-se um mapa de consenso entre dois mapas globais de vegetação natural amplamente utilizados em estudos climáticos. Mostrou-se que esses dois mapas alocam biomas diferentes em cerca de 1/3 dos pontos de grade continentais. Para obter um novo mapa global de vegetação natural, as áreas de não-consenso foram preenchidas utilizando-se um conjunto de mais de 100 mapas regionais disponíveis na Internet. Para minimizar os riscos de se usar informação de baixa qualidade, os mapas regionais foram obtidos de sítios confiáveis da Internet, e o procedimento de preenchimento baseou-se no consenso entre vários mapas regionais obtidos de fontes independentes. Elaborou-se o novo mapa de modo a reproduzir em grande escala a distribuição dos principais tipos de vegetação (uma vez que se pauta em dois mapas globais de vegetação natural confiáveis) e também detalhes regionais (uma vez que se baseia em consenso de mapas regionais) com precisão.

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We developed a new world natural vegetation map at 1 degree horizontal resolution for use in global climate models. We used the Dorman and Sellers vegetation classification with inclusion of a new biome: tropical seasonal forest, which refers to both deciduous and semi-deciduous tropical forests. SSiB biogeophysical parameters values for this new biome type are presented. Under this new vegetation classification we obtained a consensus map between two global natural vegetation maps widely used in climate studies. We found that these two maps assign different biomes in ca. 1/3 of the continental grid points. To obtain a new global natural vegetation map, non-consensus areas were filled according to regional consensus based on more than 100 regional maps available on the internet. To minimize the risk of using poor quality information, the regional maps were obtained from reliable internet sources, and the filling procedure was based on the consensus among several regional maps obtained from independent sources. The new map was designed to reproduce accurately both the large-scale distribution of the main vegetation types (as it builds on two reliable global natural vegetation maps) and the regional details (as it is based on the consensus of regional maps).

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