975 resultados para climate models
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Models suggest that dramatic changes in the ocean circulation are responsible for abrupt climate changes during the last ice age and may possibly alter the relative climate stability of the last 10,000 years.
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The Atlantic thermohaline circulation (THC) is an important part of the earth's climate system. Previous research has shown large uncertainties in simulating future changes in this critical system. The simulated THC response to idealized freshwater perturbations and the associated climate changes have been intercompared as an activity of World Climate Research Program (WCRP) Coupled Model Intercomparison Project/Paleo-Modeling Intercomparison Project (CMIP/PMIP) committees. This intercomparison among models ranging from the earth system models of intermediate complexity (EMICs) to the fully coupled atmosphere-ocean general circulation models (AOGCMs) seeks to document and improve understanding of the causes of the wide variations in the modeled THC response. The robustness of particular simulation features has been evaluated across the model results. In response to 0.1-Sv (1 Sv equivalent to 10^6 ms^3 s^-1) freshwater input in the northern North Atlantic, the multimodel ensemble mean THC weakens by 30% after 100 yr. All models simulate sonic weakening of the THC, but no model simulates a complete shutdown of the THC. The multimodel ensemble indicates that the surface air temperature could present a complex anomaly pattern with cooling south of Greenland and warming over the Barents and Nordic Seas. The Atlantic ITCZ tends to shift southward. In response to 1.0-Sv freshwater input, the THC switches off rapidly in all model simulations. A large cooling occurs over the North Atlantic. The annual mean Atlantic ITCZ moves into the Southern Hemisphere. Models disagree in terms of the reversibility of the THC after its shutdown. In general, the EMICs and AOGCMs obtain similar THC responses and climate changes with more pronounced and sharper patterns in the AOGCMs.
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Six Denver metro water reservoirs were sampled to see what types of algae were found, and what impact the algae would have on drinking water reservoirs in the event of a bloom caused by warming water temperatures. Each sample contained algae. Toxic cyanobacteria, filamentous green algae, and different species of diatoms were found in the samples. Current climate change models show the temperature along the Front Range is rising and will continue to rise. With an increase in climate change and an increase in population, humans and animals will be at a greater risk of ingesting or coming into contact with toxic algae.
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Time-variable gravity data from the Gravity Recovery And Climate Experiment (GRACE) mission are used to study total water content over Australia for the period 2002–2010. A time-varying annual signal explains 61% of the variance of the data, in good agreement with two independent estimates of the same quantity from hydrological models. Water mass content variations across Australia are linked to Pacific and Indian Ocean variability, associated with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), respectively. From 1989, positive (negative) IOD phases were related to anomalously low (high) precipitation in southeastern Australia, associated with a reduced (enhanced) tropical moisture flux. In particular, the sustained water mass content reduction over central and southern regions of Australia during the period 2006–2008 is associated with three consecutive positive IOD events.
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Tese de doutoramento, Biologia (Biologia Marinha e Aquacultura), Universidade de Lisboa, Faculdade de Ciências, 2016
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This study projects land cover probabilities under climate change for corn (maize), soybeans, spring and winter wheat, winter wheat-soybean double cropping, cotton, grassland and forest across 16 central U.S. states at a high spatial resolution, while also taking into account the influence of soil characteristics and topography. The scenarios span three oceanic-atmospheric global circulation models, three Representative Concentration Pathways, and three time periods (2040, 2070, 2100). As climate change intensifies, the suitable area for all six crops display large northward shifts. Total suitable area for spring wheat, followed by corn and soybeans, diminish. Suitable area for winter wheat and for winter wheat-soybean double-cropping expand northward, while cotton suitability migrates to new, more northerly, locations. Suitability for forest intensifies in the south while yielding to crops in the north; grassland intensifies in the western Great Plains as crop suitability diminishes. To maintain current broad geographic patterns of land use, large changes in the thermal response of crops such as corn would be required. A transition from corn-soybean to winter wheat-soybean doubling cropping is an alternative adaptation.
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Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values.
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Planktonic foraminiferal faunas of the southeast Pacific indicate that sea surface temperatures (SST) have varied by as much as 8-10°C in the Peru Current, and by ?5-7°C along the equator, over the past 150,000 years. Changes in SST at times such as the Last Glacial Maximum reflect incursion of high-latitude species Globorotalia inflata and Neogloboquadrina pachyderma into the eastern boundary current and as far north as the equator. A simple heat budget model of the equatorial Pacific shows that observed changes in Peru Current advection can account for about half of the total variability in equatorial SSTs. The remaining changes in equatorial SST, which are likely related to local changes in upwelling or pycnocline depth, precede changes in polar climates as recorded by d18O. This partitioning of processes in eastern equatorial Pacific SST reveals that net ice-age cooling here reflects first a rapid response of equatorial upwelling to insolation, followed by a later response to changes in the eastern boundary current associated with high-latitude climate (which closely resembles variations in atmospheric CO2 as recorded in the Vostok ice core). Although precise mechanisms responsible for the equatorial upwelling component of climate change remain uncertain, one likely candidate that may operate independently of the ice sheets is insolation-driven changes in El Niño/Southern Oscillation (ENSO) frequency. Early responses of equatorial SST detected both here and elsewhere highlight the sensitivity of tropical systems to small changes in seasonal insolation. The scale of tropical changes we have observed are substantially greater than model predictions, suggesting a need for further quantitative assessment of processes associated with long-term climate change.
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The high-resolution delta18O and delta13C records of benthic foraminifera from a 150,000-year long core from the Caribbean Sea indicate that there was generally high delta13C during glaciations and low delta13C during interglaciations. Due to its 1800-m sill depth, the properties of deep water in the Caribbean Sea are similar to those of middepth tropical Atlantic water. During interglaciations, the water filling the deep Caribbean Sea is an admixture of low delta13C Upper Circumpolar Water (UCPW) and high delta13C Upper North Atlantic Deep Water (UNADW). By contrast, only high delta13C UNADW enters during glaciations. Deep ocean circulation changes can influence atmospheric CO2 levels (Broecker and Takahashi, 1985; Boyle, 1988 doi:10.1029/JC093iC12p15701; Keir, 1988 doi:10.1029/PA003i004p00413; Broecker and Peng, 1989 doi:10.1029/GB003i003p00215). By comparing delta13C records of benthic foraminifera from cores lying in Southern Ocean Water, the Caribbean Sea, and at several other Atlantic Ocean sites, the thermohaline state of the Atlantic Ocean (how close it was to a full glacial or full interglacial configuration) is characterized. A continuum of circulation patterns between the glacial and interglacial extremes appears to have existed in the past. Subtracting the deep Pacific (~mean ocean water) delta13C record from the Caribbean delta13C record yields a record which describes large changes in the Atlantic Ocean thermohaline circulation. The delta13C difference varies as the vertical nutrient distribution changes. This new proxy record bears a striking resemblance to the 150,000-year-long atmospheric CO2 record (Barnola et al., 1987 doi:10.1038/329408a0). This favorable comparison between the new proxy record and the atmospheric CO2 record is consistent with Boyle's (1988a) model that vertical nutrient redistribution has driven large atmospheric CO2 changes in the past. Changes in the relative contribution of NADW and Pacific outflow water to the Southern Ocean are also consistent with Broecker and Peng's (1989) recent model for atmospheric CO2 changes.
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Thesis (Ph.D.)--University of Washington, 2016-06
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The current research tested a theoretical model of employee adjustment during organizational change based on Lazarus and Folkman's (1984) cognitive-phenomenological framework. The model hypothesized that psychological climate variables would act as coping resources and predict improved adjustment during change. Two variations of this model were tested using survey data from two different organizational samples: 779 public hospital employees and 877 public sector employees. Confirmatory factor analyses and structural equation analyses were conducted in order to evaluate the models. Results showed that employees whose perceptions of the organization and environment in which they were working (that is, psychological climate) were more positive, were more likely to appraise change favourably and report better adjustment in terms of higher job satisfaction, psychological well-being, and organizational commitment, and lower absenteeism and turnover intentions.
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Long-term forecasts of pest pressure are central to the effective management of many agricultural insect pests. In the eastern cropping regions of Australia, serious infestations of Helicoverpa punctigera (Wallengren) and H. armigera (Hübner)(Lepidoptera: Noctuidae) are experienced annually. Regression analyses of a long series of light-trap catches of adult moths were used to describe the seasonal dynamics of both species. The size of the spring generation in eastern cropping zones could be related to rainfall in putative source areas in inland Australia. Subsequent generations could be related to the abundance of various crops in agricultural areas, rainfall and the magnitude of the spring population peak. As rainfall figured prominently as a predictor variable, and can itself be predicted using the Southern Oscillation Index (SOI), trap catches were also related to this variable. The geographic distribution of each species was modelled in relation to climate and CLIMEX was used to predict temporal variation in abundance at given putative source sites in inland Australia using historical meteorological data. These predictions were then correlated with subsequent pest abundance data in a major cropping region. The regression-based and bioclimatic-based approaches to predicting pest abundance are compared and their utility in predicting and interpreting pest dynamics are discussed.
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Elevated ocean temperatures can cause coral bleaching, the loss of colour from reef-building corals because of a breakdown of the symbiosis with the dinoflagellate Symbiodinium. Recent studies have warned that global climate change could increase the frequency of coral bleaching and threaten the long-term viability of coral reefs. These assertions are based on projecting the coarse output from atmosphere-ocean general circulation models (GCMs) to the local conditions around representative coral reefs. Here, we conduct the first comprehensive global assessment of coral bleaching under climate change by adapting the NOAA Coral Reef Watch bleaching prediction method to the output of a low- and high-climate sensitivity GCM. First, we develop and test algorithms for predicting mass coral bleaching with GCM-resolution sea surface temperatures for thousands of coral reefs, using a global coral reef map and 1985-2002 bleaching prediction data. We then use the algorithms to determine the frequency of coral bleaching and required thermal adaptation by corals and their endosymbionts under two different emissions scenarios. The results indicate that bleaching could become an annual or biannual event for the vast majority of the world's coral reefs in the next 30-50 years without an increase in thermal tolerance of 0.2-1.0 degrees C per decade. The geographic variability in required thermal adaptation found in each model and emissions scenario suggests that coral reefs in some regions, like Micronesia and western Polynesia, may be particularly vulnerable to climate change. Advances in modelling and monitoring will refine the forecast for individual reefs, but this assessment concludes that the global prognosis is unlikely to change without an accelerated effort to stabilize atmospheric greenhouse gas concentrations.
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The speculation that climate change may impact on sustainable fish production suggests a need to understand how these effects influence fish catch on a broad scale. With a gross annual value of A$ 2.2 billion, the fishing industry is a significant primary industry in Australia. Many commercially important fish species use estuarine habitats such as mangroves, tidal flats and seagrass beds as nurseries or breeding grounds and have lifecycles correlated to rainfall and temperature patterns. Correlation of catches of mullet (e.g. Mugil cephalus) and barramundi (Lates calcarifer) with rainfall suggests that fisheries may be sensitive to effects of climate change. This work reviews key commercial fish and crustacean species and their link to estuaries and climate parameters. A conceptual model demonstrates ecological and biophysical links of estuarine habitats that influences capture fisheries production. The difficulty involved in explaining the effect of climate change on fisheries arising from the lack of ecological knowledge may be overcome by relating climate parameters with long-term fish catch data. Catch per unit effort (CPUE), rainfall, the Southern Oscillation Index (SOI) and catch time series for specific combinations of climate seasons and regions have been explored and surplus production models applied to Queensland's commercial fish catch data with the program CLIMPROD. Results indicate that up to 30% of Queensland's total fish catch and up to 80% of the barramundi catch variation for specific regions can be explained by rainfall often with a lagged response to rainfall events. Our approach allows an evaluation of the economic consequences of climate parameters on estuarine fisheries. thus highlighting the need to develop forecast models and manage estuaries for future climate chan e impact by adjusting the quota for climate change sensitive species. Different modelling approaches are discussed with respect to their forecast ability. (c) 2006 Elsevier Ltd. All rights reserved.
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Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.