Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-08-15T13:02:14Z No. of bitstreams: 1 ROBERTA ARAÚJO E SILVA - TESE (PPGMet) 2018.pdf: 3397527 bytes, checksum: d7b0de649c1e410cbeabdeea5fe40e82 (MD5) / Made available in DSpace on 2018-08-15T13:02:14Z (GMT). No. of bitstreams: 1 ROBERTA ARAÚJO E SILVA - TESE (PPGMet) 2018.pdf: 3397527 bytes, checksum: d7b0de649c1e410cbeabdeea5fe40e82 (MD5) Previous issue date: 2018-01-30 / CNPq / Neste estudo foram avaliadas as condições atuais e os efeitos das mudanças climáticas sobre a produtividade e pegada hídrica da soja cultivada na região de Matopiba. Para simular a produtividade da cultura foi usado o modelo AquaCrop versão 5.0 da FAO, calibrado com dados do ano de 2016 e validado com os de 2014, usando parâmetros de clima, solo, cultura e manejo coletados em duas campanhas experimentais realizadas entre os meses de junho e outubro nos anos de 2014 e 2016 em Palmas, TO. O desempenho do modelo foi avaliado utilizando os indicadores estatísticos: erro de previsão (Ep), coeficiente de determinação (R2), raiz quadrada do erro médio (RMSE), erro médio absoluto (EMA), eficiência de Nash e Sutcliffe (NSE), e o índice de concordância de Willmontt´s (d). A calibração e validação da produtividade da cultura de soja estimada pelo modelo AquaCrop, apresentaram resultados satisfatórios, ilustrando a robustez e a aplicabilidade geral do modelo. O modelo AquaCrop subestima a produtividade de grãos de soja, para condições de estresse hídrico severo durante todo o ciclo de cultivo. Após a calibração e validação, o AquaCrop foi utilizado como ferramenta de simulação de produtividade da cultura da soja para o cenário atual (2016) e de mudanças climáticas a médio (2045/2046; 2055/2056) e longo prazo (2075/2076; 2064/2095), alimentado por dados de dois modelos climáticos (HadGEM2-ES e MIROC5) e considerando as RCP 4.5 e 8.5. Em seguida, calculou-se a pegada hídrica (verde, azul e cinza) de soja atual dos principais municípios produtores, de cada estado que compõem a região do Matopiba. Posteriormente, avaliaram-se os efeitos das possíveis mudanças climáticas sob a produtividade e pegada hídrica da soja, considerando as variações climáticas com foco na temperatura, precipitação e CO2. Os modelos climáticos projetaram aumento da produtividade em ambas as RCP consideradas, porém mais acentuado sob a RCP 8.5, em decorrência do aumento da temperatura e concentração de CO2 e a precipitação, que mesmo sofrendo redução nos totais pluviométricos ao longo do tempo, ainda atendendo a necessidade hídrica da soja. As PHsoja atuais da região do Matopiba, variaram de 2036,60 m³t-1 a 2584,12 m³t-1, valores similares aos encontradas na literatura. Sob cenários de mudanças climáticas, a PHsoja decresce ao longos os anos. A PHsoja futura decresce, especialmente a componente verde, devido ao aumento menos acentuado da evapotranspiração, resultando em maior rendimento final. As PHverde diminuem ao longos dos anos, as PHazul aumenta na mesma proporção e as PHcinza apresentam comportamento praticamente continuo. Os resultados deste estudo podem ser usados para quantificar a produtividade futura da soja, a demanda de água e a sua utilização, bem como obter informações úteis para a gestão dos recursos hídricos na região de estudo. / This study evaluated the current conditions and effects of climate change on the productivity and water footprint of soybean cultivated in Matopiba region. To simulate crop productivity, the FAO AquaCrop version 5.0 model was used, calibrated with data from 2016 and validated with 2014, using climate, soil, crop and management parameters collected in two experimental campaigns conducted between the months of June and October in the years 2014 and 2016 in Palmas, TO. The performance of the model was evaluated using the statistical indicators: prediction error (Ep), coefficient of determination (R2), square root mean error (RMSE), mean absolute error (EMA), Nash efficiency and Sutcliffe (NSE) and Willmontt's agreement index (d). Calibration and validation of soybean crop productivity estimated by the AquaCrop model presented satisfactory results, illustrating the robustness and general applicability of the model. The AquaCrop model underestimates soybean grain yield for severe water stress conditions throughout the growing cycle. After calibration and validation, AquaCrop was used as a simulation tool for soybean crop productivity for the current scenario (2016) and medium-term (2045/2046; 2055/2056) and long-term (2075/2076; 2064/2095), fed by data from two climatic models (HadGEM2-ES and MIROC5) and considering RCPs 4.5 and 8.5. Then, the water footprint (green, blue and gray) of the current soybean of the main producing municipalities of each state that compose the Matopiba region was calculated. Subsequently, the effects of possible climatic changes under soybean productivity and water footprint, considering the climatic variations with focus on temperature, precipitation and CO2, were evaluated. The climatic models projected increase of productivity in both RCP considered, but more accentuated under RCP 8.5, due to the increase in temperature and concentration of CO2 and precipitation, that even undergoing a reduction in rainfall totals over time, still taking into account water requirement of soybeans. The current PHsoja of the Matopiba region, ranged from 2036.60 m³t-1 to 2584.12 m³t-1, values similar to those found in the literature. Under scenarios of climate change, the PHsoja decreases over the years. The future PHsoja decreases, especially the green component, due to the less accentuated increase of the evapotranspiration, resulting in greater final yield. PHverde decreases over the years, PHazul increases in the same proportion and PHcinza show practically continuous behavior. The results of this study can be used to quantify future soybean yield, water demand and utilization, as well as to obtain useful information for the management of water resources in the study region.

Master of Arts / Department of English / Katherine Karlin / By the year 2037, climate change has destabilized the world’s ecology, politics, and culture. Hawaii has seceded from the United States, instituting the Cultural Reaffirmation, which champions a sustainable, traditional way of life. Eenie is an astronomer on the Big Island of Hawaii. In order to keep the observatory on Mauna Kea operational, she must appease the newly independent island nation by reenacting a mythical sled race between Poliahu, the Hawaiian snow goddess of Maunakea, and Pele, the fierce goddess of lava, personified by a rival geoscientist from Maunaloa’s volcanic laboratory. Once an Olympic contender in the women’s luge, Eenie has won this race twice before. This year, though, the greenhouse effect has caught up with her; there is no snow on Maunakea. Without it, she cannot prevail, and if she doesn’t, the priests of Hawaii’s Cultural Reaffirmation will pull the telescopes down from their most sacred mountain. Eenie struggles against nature’s increasing wrath, gods, monsters, pigs, and political rivals, though her biggest struggle is within herself. Fire and water must live together takes place in an ecodystopic future, though its story pulls from Hawaiian myth. The story’s projection into the future is based on current events, including the Hawaiian sovereignty movement, climate change science, and technology. An accompanying essay frames the novella through three critical lenses: ecocriticism, eco-politics, and post-colonial hybridity. The essay includes a focused look at the setting of Hawaii as it stands today in terms of environment, politics, and people.

Modeling of the onset of permafrost formation and succeeding gas hydrate formation in the changing surface temperature environment has been done for the Beaufort-Mackenzie Basin (BMB). Numerical 1D modeling is constrained by deep heat flow from deep well bottom hole temperatures, deep conductivity, present permafrost thickness and thickness of Type I gas hydrates. Latent heat effects were applied to the model for the entire ice bearing permafrost and Type I hydrate intervals. Modeling for a set of surface temperature forcing during the glacial-interglacial history including the last 14 Myr, the detailed Holocene temperature history and a consideration of future warming due to a doubling of atmospheric CO2 was performed. Two scenarios of gas formation were considered; case 1: formation of gas hydrate from gas entrapped under deep geological seals and case 2: formation of gas hydrate from gas in a free pore space simultaneously with permafrost formation. In case 1, gas hydrates could have formed at a depth of about 0.9 km only some 1 Myr ago. In case 2, the first gas hydrate formed in the depth range of 290 – 300 m shortly after 6 Myr ago when the GST dropped from -4.5 °C to -5.5. °C. The gas hydrate layer started to expand both downward and upward subsequently. More detailed modeling of the more recent glacial–interglacial history and extending into the future was done for both BMB onshore and offshore models. These models show that the gas hydrate zone, while thinning will persist under the thick body of BMB permafrost through the current interglacial warming and into the future even with a doubling of atmospheric CO2.

No description available.

A large body of research has documented evidence of climate change impact already occurring on different systems on earth, future impacts can be expected. Accordingly, research is urgently needed to analyze the potential impacts of climate change on forest ecosystems in order to contribute to better landscape planning and management. This thesis investigates how climate change affects landscape change, and how to use this understanding in the analysis of land-use and landscape planning and management to adapt to climate change impacts. In particular, this study examines how climate change may impact a managed forest in terms of timber availability, and the regional community that relies on it for its survival. <br /><br /> I hypothesized that the Boreal forest in north western Ontario will change in the short term (i. e. 60 years) in species composition and will produce less available timber as a result of human-induced climate change as modeled by different General Circulation Models plus harvesting, compared to a baseline climate. The study objectives were (a) to evaluate the degree of change in land cover (species composition) under forest harvesting and various climate change scenarios; (b) to analyze timber availability under different climate change scenarios, and harvesting; (c) to describe possible scenarios of land cover change as a result of climate change impact and harvesting to assist in policy-making related to land-use and landscape planning; and (d) to identify possible sources of both land-use conflicts and synergies as a result of changes in landscape composition caused by climate change. <br /><br /> The study area was the Dog-River Matawin forest in north western Ontario (? 8 x 104 ha). It is currently under harvesting. I used the Boreal Forest Landscape Dynamic Simulator (BFOLDS) fire model to simulate landscape change under different climate change scenarios (CCSRNIES A21, CGCM2 A22), which were then compared to simulations under a baseline climate scenario (1961-1990). I also developed an algorithm for the geographic information systems Arc View©, that selected useful stands, and simulated harvesting and regeneration rules after logging, processes not currently included in BFOLDS. The studied period covered 60 years to analyze impacts in the medium term in the landscape change. <br /><br /> Results obtained were the following. (1) There will be a shortage in timber availability under all scenarios including the baseline. The impacts of climate change will cause a deficit in timber availability much earlier under a warmer scenario with respect to the baseline. The combined impact of climate change and harvesting could diminish timber availability up to 35% compared to the baseline by year 2040 under the CCSRNIES A21 scenario mainly due to an increase in fires. Deficits will occur 10 years before in the same scenario compared to the baseline (by year 2035). (2) In both scenarios and the baseline, there will be a younger forest. In 60 years, there will not be mature forest to support ecological, social and economic processes, as the forest will only have young stands. (3) Results obtained indicated that species composition will not change importantly among the scenarios of climate change and the baseline every decade, but there will be a change in dominance along the 60 years of the simulation under each scenario including the baseline. Softwood increased in dominance and hardwood decreased in all scenarios. <br /><br /> The period length used in the simulation of 60 years appeared to be too short to reveal conspicuous changes in species composition. Increases observed in softwood over hardwood related to the increase in fires which promoted the establishment of species such as jack pine as well as the application of regeneration rules after logging. This finding did not agree with the hypothesis. Results of timber availability were consistent with what I expected. Warmest climate change scenarios (CCSRNIES A21) impacted both the amount of timber available (less availability every ten years) from the beginning of the simulation and the time when deficits occurred. <br /><br /> There are important economic, social and environmental implications of the results of this study, namely a future forest that would be young and would supply much less timber. For the forestry industry, production goals would be hindered in the medium term, falling short of industry demands. For a society that depends heavily upon the forest to survive, declining production can imply unemployment, thus affecting the welfare of the community. For the environment, such a young, fragmented forest could be unable to sustain important key species and ecological processes, leading to a loss of biodiversity, Land-use and landscape planning should be used to regulate how the land is used to minimize climate change impact. They should be further used as adaptation tools, to help in ameliorate those climate change impacts that do occur.

A large body of research has documented evidence of climate change impact already occurring on different systems on earth, future impacts can be expected. Accordingly, research is urgently needed to analyze the potential impacts of climate change on forest ecosystems in order to contribute to better landscape planning and management. This thesis investigates how climate change affects landscape change, and how to use this understanding in the analysis of land-use and landscape planning and management to adapt to climate change impacts. In particular, this study examines how climate change may impact a managed forest in terms of timber availability, and the regional community that relies on it for its survival. <br /><br /> I hypothesized that the Boreal forest in north western Ontario will change in the short term (i. e. 60 years) in species composition and will produce less available timber as a result of human-induced climate change as modeled by different General Circulation Models plus harvesting, compared to a baseline climate. The study objectives were (a) to evaluate the degree of change in land cover (species composition) under forest harvesting and various climate change scenarios; (b) to analyze timber availability under different climate change scenarios, and harvesting; (c) to describe possible scenarios of land cover change as a result of climate change impact and harvesting to assist in policy-making related to land-use and landscape planning; and (d) to identify possible sources of both land-use conflicts and synergies as a result of changes in landscape composition caused by climate change. <br /><br /> The study area was the Dog-River Matawin forest in north western Ontario (? 8 x 104 ha). It is currently under harvesting. I used the Boreal Forest Landscape Dynamic Simulator (BFOLDS) fire model to simulate landscape change under different climate change scenarios (CCSRNIES A21, CGCM2 A22), which were then compared to simulations under a baseline climate scenario (1961-1990). I also developed an algorithm for the geographic information systems Arc View©, that selected useful stands, and simulated harvesting and regeneration rules after logging, processes not currently included in BFOLDS. The studied period covered 60 years to analyze impacts in the medium term in the landscape change. <br /><br /> Results obtained were the following. (1) There will be a shortage in timber availability under all scenarios including the baseline. The impacts of climate change will cause a deficit in timber availability much earlier under a warmer scenario with respect to the baseline. The combined impact of climate change and harvesting could diminish timber availability up to 35% compared to the baseline by year 2040 under the CCSRNIES A21 scenario mainly due to an increase in fires. Deficits will occur 10 years before in the same scenario compared to the baseline (by year 2035). (2) In both scenarios and the baseline, there will be a younger forest. In 60 years, there will not be mature forest to support ecological, social and economic processes, as the forest will only have young stands. (3) Results obtained indicated that species composition will not change importantly among the scenarios of climate change and the baseline every decade, but there will be a change in dominance along the 60 years of the simulation under each scenario including the baseline. Softwood increased in dominance and hardwood decreased in all scenarios. <br /><br /> The period length used in the simulation of 60 years appeared to be too short to reveal conspicuous changes in species composition. Increases observed in softwood over hardwood related to the increase in fires which promoted the establishment of species such as jack pine as well as the application of regeneration rules after logging. This finding did not agree with the hypothesis. Results of timber availability were consistent with what I expected. Warmest climate change scenarios (CCSRNIES A21) impacted both the amount of timber available (less availability every ten years) from the beginning of the simulation and the time when deficits occurred. <br /><br /> There are important economic, social and environmental implications of the results of this study, namely a future forest that would be young and would supply much less timber. For the forestry industry, production goals would be hindered in the medium term, falling short of industry demands. For a society that depends heavily upon the forest to survive, declining production can imply unemployment, thus affecting the welfare of the community. For the environment, such a young, fragmented forest could be unable to sustain important key species and ecological processes, leading to a loss of biodiversity, Land-use and landscape planning should be used to regulate how the land is used to minimize climate change impact. They should be further used as adaptation tools, to help in ameliorate those climate change impacts that do occur.

abstract: Climate change has been one of the major issues of global economic and social concerns in the past decade. To quantitatively predict global climate change, the Intergovernmental Panel on Climate Change (IPCC) of the United Nations have organized a multi-national effort to use global atmosphere-ocean models to project anthropogenically induced climate changes in the 21st century. The computer simulations performed with those models and archived by the Coupled Model Intercomparison Project - Phase 5 (CMIP5) form the most comprehensive quantitative basis for the prediction of global environmental changes on decadal-to-centennial time scales. While the CMIP5 archives have been widely used for policy making, the inherent biases in the models have not been systematically examined. The main objective of this study is to validate the CMIP5 simulations of the 20th century climate with observations to quantify the biases and uncertainties in state-of-the-art climate models. Specifically, this work focuses on three major features in the atmosphere: the jet streams over the North Pacific and Atlantic Oceans and the low level jet (LLJ) stream over central North America which affects the weather in the United States, and the near-surface wind field over North America which is relevant to energy applications. The errors in the model simulations of those features are systematically quantified and the uncertainties in future predictions are assessed for stakeholders to use in climate applications. Additional atmospheric model simulations are performed to determine the sources of the errors in climate models. The results reject a popular idea that the errors in the sea surface temperature due to an inaccurate ocean circulation contributes to the errors in major atmospheric jet streams. / Dissertation/Thesis / M.S. Mechanical Engineering 2014

L'augmentation du bilan de masse en surface de la calotte polaire Antarctique causée par celle des chutes de neige est la seule contribution négative à l'élévation du niveau de mer attendue dans le courant du 21ème siècle dans le cadre du réchauffement climatique causé par les activités humaines. La régionalisation dynamique de projections climatiques issues de modèles couplés océans-atmosphère est la méthode la plus couramment utilisée pour estimer les variations futures du climat Antarctique. Néanmoins, de nombreuses incertitudes subsistent suite à l'application de ces méthodes, en particulier en raison des biais conséquents sur les conditions océaniques de surface et sur la circulation atmosphérique aux hautes latitudes de l’Hémisphère Sud dans les modèles couplés.Dans la première partie de ce travail, différentes méthodes de corrections de biais des conditions océanique de surface ont été évaluées. Les résultats ont permis de retenir une méthode quantile-quantile pour la température de surface de l'océan et une méthode d'analogues pour la concentration en glace de mer. En raison de la forte sensibilité du climat future Antarctique aux variations de couverture de glace de mer dans l'Océan Austral, les conditions océaniques issues de deux modèles couplés, NorESM1-M et MIROC-ESM, présentant des diminutions d’étendues de glace de mer hivernales largement différentes (-14 et -45%) ont été retenues. Les conditions océaniques provenant d'un scénario RCP8.5 de ces deux modèles ont été corrigées afin de forcer le modèle atmosphérique global ARPEGE.Par la suite, ARPEGE a été utilisé dans une configuration grille-étirée, permettant d'atteindre une résolution horizontale de 40 kilomètres sur l'Antarctique. Il a été contraint aux limites par les conditions océaniques de surface observées et celles issues des simulations historiques des modèles NorESM1-M et MIROC-ESM pour la période récente (1981-2010). Pour la fin du 21ème siècle (2071-2100), les forçages océaniques originaux et corrigés issus de ces deux derniers modèles ont été utilisés. L'évaluation pour le présent a permis de mettre en évidence, la capacité du modèle ARPEGE de reproduire le climat et le bilan de masse de surface Antarctique ainsi que la persistance d'erreurs substantielles sur la circulation atmosphérique y compris dans la simulation forcée par les conditions océaniques observées. Pour le climat futur, l'utilisation des forçages océaniques MIROC-ESM corrigés a engendré des augmentations supplémentaires significatives à l'échelle continentale pour les températures hivernales et le bilan de masse annuel.Enfin, ARPEGE a été corrigé en ligne, à l'aide d'une climatologie des termes de rappel du modèle issus d'une simulation guidée par les réanalyses climatologiques. L'application de cette méthode sur la période récente a très largement amélioré la modélisation de la circulation atmosphérique et du climat de surface Antarctique. L'application pour le climat futur suggère des augmentations de températures (+0.7 à +0.9 C) et de précipitations (+6 à +9%) supplémentaires par rapport à celles issues des scénarios réalisés sans correction atmosphérique. Le forçage de modèles climatiques régionaux ou de dynamique glaciaire avec les scénarios ARPEGE corrigés est à explorer au regard des impacts potentiellement importants pour la calotte Antarctique et sa contribution à l'élévation du niveau des mers. / The increase of the Antarctic ice-sheet surface mass balance due to rise in snowfall is the only expected negative contribution to sea-level rise in the course of the 21st century within the context of global warming induced by mankind. Dynamical downscaling of climate projections provided by coupled ocean-atmosphere models is the most commonly used method to assess the future evolution of the Antarctic climate. Nevertheless, large uncertainties remain in the application of this method, particularly because of large biases in coupled models for oceanic surface conditions and atmospheric large-scale circulation at Southern Hemisphere high latitudes.In the first part of this work, different bias-correction methods for oceanic surface conditions have been evaluated. The results have allowed to select a quantile-quantile method for sea surface temperature and an analog method for sea-ice concentration. Because of the strong sensitivity of Antarctic surface climate to the variations of sea-ice extents in the Southern Ocean, oceanic surface conditions provided by two coupled models, NorESM1-M and MIROC-ESM, showing clearly different trends (respectively -14 and -45%) on winter sea-ice extent have been selected. Oceanic surface conditions of the ``business as usual" scenario (RCP8.5) coming from these two models have been corrected in order to force the global atmospheric model ARPEGE.In the following, ARPEGE has been used in a stretched-grid configuration, allowing to reach an horizontal resolution around 40 kilometers on Antarctica. For historical climate (1981-2010), the model was driven by observed oceanic surface conditions as well as by those from MIROC-ESM and NorESM1-M historical simulation. For late 21st century (2071-2100), original and bias corrected oceanic conditions from the latter two model have been used. The evaluation for present climate has evidenced excellent ARPEGE skills for surface climate and surface mass balance as well as large remaining errors on large-scale atmospheric circulation even when using observed oceanic surface conditions. For future climate, the use of bias-corrected MIROC-ESM oceanic forcings has yielded an additionally significant increase in winter temperatures and in annual surface mass balance at the continent-scale.In the end, ARPEGE has been corrected at run-time using a climatology of tendency errors coming from an ARPEGE simulation driven by climate reanalyses. The application of this method for present climate has dramatically improved the modelling of the atmospheric circulation and antarctic surface climate. The application for the future suggests significant additional warming (~ 0.7 to +0.9 C) and increase in precipitation (~ +6 to +9 %) with respect to the scenarios realized without atmospheric bias correction. Driving regional climate models or ice dynamics model with corrected ARPEGE scenarios is to explored in regards of the potentially large-impacts on the Antarctic ice-sheet and its contribution to sea-level rise.

The Models-3/Community Multi-scale Air Quality modeling system (CMAQ), coupled with Goddard Institute for Space Studies (GISS) atmospheric General Circulation Model (GCM), fifth Generation Mesoscale Model system (MM5), and Goddard Earth Observing System-CHEMistry (GEOS-Chem), was used to simulate atmospheric concentration of ozone and particulate matter over the continental United States 12-km and 36-km (CONUS) domains at year 2000 and year 2050. In the study, GISS GCM model outputs interfaced with MM5 were utilized to supply the current and future meteorological conditions for CMAQ. The conventional CMAQ profile initial and boundary conditions were replaced by time-varied and layer-varied GEOS-Chem outputs. The future emission concentrations were estimated using year 2000 based emissions with emission projections suggested by the IPCC A1B scenario. Multi-scenario statistical analyses were performed to investigate the effects of climate change and change of anthropogenic emissions toward 2050. The composite effects of these changes were broken down into individual effects and analyzed on three distinct regions (i.e., Midwest, Northeast and Southeast). The results of CMAQ hourly and 8-hour average concentrations indicate the maximum ozone concentration in the Midwest is increased slightly from year 2000 to year 2050, as a result of increasing average and maximum temperatures by 2 to 3 degrees Kelvin. In converse, there is an observed reduction of surface ozone concentration in the Southeast caused by the decrease in solar radiation. For the emission reduction scenario, the decline of anthropogenic emissions causes reductions of both ozone and PM2.5 for all regions. The emission reduction has compensated the effect of increasing temperature. The overall change on the maximum daily 8-hr ozone and average PM2.5 concentrations in year 2050 were estimated to be 10% and 40% less than the values in year 2000, respectively. The modeling results indicates the effect of emissions reduction has greater impact than the effect of climate change.

The water deficit is a major factor responsible for the soybean yield gap in Southern Brazil and tends to increase under climate change. Crop models are a tool that differ on levels of complexity and performance and can be used to evaluate strategies to manage crops, according the climate conditions. Based on that, the aims of this study were: to assess five soybean crop models and their ensemble; to evaluate the sensitivity of these models to systematic changes in climate; to assess soybean adaptive traits to water deficit for current and future climate; and to evaluate how the crop management contribute to soybean yields under current and future climates. The crop models FAO - Agroecological Zone, AQUACROP, DSSAT CSM-CROPGRO-Soybean, APSIM Soybean, and MONICA were assessed. These crop models were calibrated using experimental data obtained during 2013/2014 growing season in different sites, sowing dates and crop conditions (rainfed and irrigated). For the sensitivity analysis was considered climate changes on air temperature, [CO2], rainfall and solar radiation. For adapting traits to drought, the soybean traits manipulated only in DSSAT CSM-CROPGRO-Soybean were deeper root depth, maximum fraction of shoot dry matter diverted to root growth under water stress, early reduction of transpiration, transpiration limited as a function of vapor pressure deficit, N2 fixation drought tolerance and reduced acceleration of grain filling period in response to water deficit. The crop management options strategies evaluated were irrigation, sowing date, cultivar maturity group and planting density. The estimated yield had root mean square error (RMSE) varying between 553 kg ha-1 and 650 kg ha-1, with d indices always higher than 0.90 for all models. The best performance was obtained when an ensemble of all models was considered, reducing yield RMSE to 262 kg ha-1. The crop models had different sensitivity level for climate scenario, reduction yield with temperature increase, higher rate of reduction of yield with lower rainfall than increase of yield with higher rainfall amount, different yields response with solar radiation changes due to baseline climate and model, and an asymptotic soybean response to increase of [CO2]. Combining the climate scenarios, the yield was affected mainly by reduction of rainfall (increase of solar radiation), while temperature and [CO2] interaction showed compensation effect on yield losses and gains. The trait deeper rooting profile had greater improvement in total production for the Southern Brazil, with increase of 3.3 % and 4.0 %, respectively, for the current and future climates. For soybean management, in most cases, the models showed that no crop management strategy has a clear tendency to result in better yields in the future if shift from the best management of current climate. This way, the crop models showed different performance against observed data, where the model parametrization and structure affected the response to alternatives managements to climate change. Although these uncertainties, crop models and their ensemble are an important tool to evaluate impact of climate change and alternatives to mitigation. / O déficit hídrico é o principal fator causador de perda de produtividade para a soja no Centro-Sul do Brasil e tende a aumentar com as mudanças climáticas. Alternativas de mitigação podem ser avaliadas usando modelos de simulação de cultura, os quais diferem em nível de complexidade e desempenho. Baseado nisso, os objetivos desse estudo foram: avaliar cinco modelos de simulação para a soja e a média desses modelos; avaliar a sensibilidade dos modelos a mudança sistemática do clima; avaliar características adaptativas da soja ao déficit hídrico para o clima atual e futuro; e avaliar a resposta produtiva de manejos da soja para o clima atual e futuro. Os modelos utilizados foram FAO - Zona Agroecológica, AQUACROP, DSSAT CSM-CROPGRO-Soybean, APSIM Soybean e MONICA. Os modelos foram calibrados a partir de dados experimentais obtidos na safra 2013/2014 em diferentes locais e datas de semeadura sob condições irrigadas e de sequeiro. Na análise de sensibilidade foram modificadas a temperatura do ar, [CO2], chuva e radiação solar. Para as características de tolerância ao déficit hídrico foram manipulados, apenas no modelo DSSAT CSMCROPGRO- Soybean, a distribuição do sistema radicular, biomassa divergida para crescimento radicular sob déficit hídrico, redução antecipada da transpiração, limitação da transpiração em função do déficit de pressão de vapor, fixação de N2 sob déficit hídrico e redução da aceleração do ciclo devido ao déficit hídrico. Os manejos avaliados foram irrigação, data de semeadura, ciclo de cultivar e densidade de semeadura. A produtividade estimada obteve raiz do erro médio quadrático (REMQ) variando entre 553 kg ha-1 e 650 kg ha-1, com índice d acima de 0.90 para todos os modelos. O melhor desempenho foi obtido utilizando a média de todos os modelos, com REMQ de 262 kg ha-1. Os modelos obtiveram diferentes níveis de sensibilidade aos cenários climáticos, reduzindo a produtividade com aumento da temperatura, maior taxa de redução da produtividade com menor quantidade de chuva do que aumento de produtividade com maior quantidade de chuva, diferentes respostas com a mudança da radiação solar em função do clima local e do modelo, e resposta positiva assimptótica para o aumento da concentração de [CO2]. Quando combinado as mudanças dos cenários, a produtividade foi afetada principalmente pela redução da chuva (aumento da radiação solar), enquanto a mudança na temperatura e [CO2] mostrou compensação nas perdas e ganhos. A distribuição do sistema radicular foi o mecanismo de tolerância ao déficit hídrico com maior ganho de produtividade, representando ganho total na produção de 3,3 % e 4,0% para a região, respectivamente, para o clima atual e futuro. Para os manejos não se observou melhores resultados com a mudança do manejo para o futuro em relação a melhor condição para o clima atual. Desta forma, os modelos mostraram diferentes desempenho, em que a parametrização e a estrutura do modelo afetaram a resposta das alternativas avaliadas para mudanças climáticas. Apesar das incertezas, os modelos de cultura são uma importante ferramenta para avaliar o impacto e alternativas de mitigação as mudanças climáticas.