988 resultados para Southern oscillation


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Coral palaeoclimatic studies are under way at many sites throughout the wet tropics. However, arid environments have received less attention. Here we report a high-resolution, 63 yr record of coral d18O and d13C extracted from a Porites colony from the Dahlak Archipelago, off the Eritrean coast, in the southern Red Sea. The annual cycles of the coral d18O and d13C are inversely related while their inter-annual variations show a strong positive correlation, with similar inter-decadal trends. Inter-annual variations in coral d18O show a relatively weak correlation with the southern Red Sea SST, but are strongly correlated with the Indian Ocean SST, especially on the decadal time-scale. The range of the inter-annual variations in the coral d18O is high compared to changes in local SST, due to the amplifying effect of simultaneous changes in water isotopic composition. Due to this amplification of the climate signal the coral provides a better indication of regional oceangraphic behaviour than the local SST record. The norrtheast monsoon signal in the coral d18O dominates the mean annual signal and shows the best correlation with the instrumental data sets. It appears that variations in the coral d18O are controlled mainly by variations in the intensity of surface water influx from the Indian Ocean to the Red Sea during the winter northeast monsoon. Of particular significance is that the decadal time-scale variations in the coral skeletal d18O are closely correlated with both the Indian Ocean SST and with variations in the Pacific-based Southern Oscillation index. That is, isotopically light coral skeleton, indicating strong NE monsoon Red Sea inflow, correlates with periods of high Indian Ocean SST and with predominantly negative (El Nino) phases of the Southern Oscillation. The simultaneous nature of inter-decadal changes in Asian monsoon and ENSO behaviour suggest pan-Indo-Pacific tropical climate reorganisation and evolution.

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Background: Identifying clusters of acute paracoccidioidomycosis cases could potentially help in identifying the environmental factors that influence the incidence of this mycosis. However, unlike other endemic mycoses, there are no published reports of clusters of paracoccidioidomycosis. Methodology/Principal Findings: A retrospective cluster detection test was applied to verify if an excess of acute form (AF) paracoccidioidomycosis cases in time and/or space occurred in Botucatu, an endemic area in Sao Paulo State. The scan-test SaTScan v7.0.3 was set to find clusters for the maximum temporal period of 1 year. The temporal test indicated a significant cluster in 1985 (P<0.005). This cluster comprised 10 cases, although 2.19 were expected for this year in this area. Age and clinical presentation of these cases were typical of AF paracccidioidomycosis. The space-time test confirmed the temporal cluster in 1985 and showed the localities where the risk was higher in that year. The cluster suggests that some particularities took place in the antecedent years in those localities. Analysis of climate variables showed that soil water storage was atypically high in 1982/83 (similar to 2.11/2.5 SD above mean), and the absolute air humidity in 1984, the year preceding the cluster, was much higher than normal (similar to 1.6 SD above mean), conditions that may have favored, respectively, antecedent fungal growth in the soil and conidia liberation in 1984, the probable year of exposure. These climatic anomalies in this area was due to the 1982/83 El Nino event, the strongest in the last 50 years. Conclusions/Significance: We describe the first cluster of AF paracoccidioidomycosis, which was potentially linked to a climatic anomaly caused by the 1982/83 El Nino Southern Oscillation. This finding is important because it may help to clarify the conditions that favor Paracoccidioides brasiliensis survival and growth in the environment and that enhance human exposure, thus allowing the development of preventive measures.

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The Community Climate Model (CCM3) from the National Center for Atmospheric Research (NCAR) is used to investigate the effect of the South Atlantic sea surface temperature (SST) anomalies on interannual to decadal variability of South American precipitation. Two ensembles composed of multidecadal simulations forced with monthly SST data from the Hadley Centre for the period 1949 to 2001 are analysed. A statistical treatment based on signal-to-noise ratio and Empirical Orthogonal Functions (EOF) is applied to the ensembles in order to reduce the internal variability among the integrations. The ensemble treatment shows a spatial and temporal dependence of reproducibility. High degree of reproducibility is found in the tropics while the extratropics is apparently less reproducible. Austral autumn (MAM) and spring (SON) precipitation appears to be more reproducible over the South America-South Atlantic region than the summer (DJF) and winter (JJA) rainfall. While the Inter-tropical Convergence Zone (ITCZ) region is dominated by external variance, the South Atlantic Convergence Zone (SACZ) over South America is predominantly determined by internal variance, which makes it a difficult phenomenon to predict. Alternatively, the SACZ over western South Atlantic appears to be more sensitive to the subtropical SST anomalies than over the continent. An attempt is made to separate the atmospheric response forced by the South Atlantic SST anomalies from that associated with the El Nino - Southern Oscillation (ENSO). Results show that both the South Atlantic and Pacific SSTs modulate the intensity and position of the SACZ during DJF. Particularly, the subtropical South Atlantic SSTs are more important than ENSO in determining the position of the SACZ over the southeast Brazilian coast during DJF. On the other hand, the ENSO signal seems to influence the intensity of the SACZ not only in DJF but especially its oceanic branch during MAM. Both local and remote influences, however, are confounded by the large internal variance in the region. During MAM and JJA, the South Atlantic SST anomalies affect the magnitude and the meridional displacement of the ITCZ. In JJA, the ENSO has relatively little influence on the interannual variability of the simulated rainfall. During SON, however, the ENSO seems to counteract the effect of the subtropical South Atlantic SST variations on convection over South America.

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Recent El Nino events have stimulated interest in the development of modeling techniques to forecast extremes of climate and related health events. Previous studies have documented associations between specific climate variables (particularly temperature and rainfall) and outbreaks of arboviral disease. In some countries, such diseases are sensitive to Fl Nino. Here we describe a climate-based model for the prediction of Ross River virus epidemics in Australia. From a literature search and data on case notifications, we determined in which years there were epidemics of Ross River virus in southern Australia between 1928 and 1998. Predictor variables were monthly Southern Oscillation index values for the year of an epidemic or lagged by 1 year. We found that in southeastern states, epidemic years were well predicted by monthly Southern Oscillation index values in January and September in the previous year. The model forecasts that there is a high probability of epidemic Ross River virus in the southern states of Australia in 1999. We conclude that epidemics of arboviral disease can, at least in principle, be predicted on the basis of climate relationships.

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To reconstruct oceanographic variations in the subtropical South Pacific, 271-year long subseasonal time series of Sr/Ca and delta(18)O were generated from a coral growing at Rarotonga (21.5degreesS, 159.5degreesW). In this case, coral Sr/Ca appears to be an excellent proxy for sea surface temperature (SST) and coral delta(18)O is a function of both SST and seawater delta(18)O composition (delta(18)O(sw)). Here, we focus on extracting the delta(18)O(sw) signal from these proxy records. A method is presented assuming that coral Sr/Ca is solely a function of SST and that coral delta(18)O is a function of both SST and delta(18)O(sw). This method separates the effects of delta(18)O(sw) from SST by breaking the instantaneous changes of coral delta(18)O into separate contributions by instantaneous SST and delta(18)O(sw) changes, respectively. The results show that on average delta(18)O(sw) at Rarotonga explains similar to39% of the variance in delta(18)O and that variations in SST explains the remaining similar to61% of delta(18)O variance. Reconstructed delta(18)O(sw) shows systematic increases in summer months (December-February) consistent with the regional pattern of variations in precipitation and evaporation. The delta(18)O(sw) also shows a positive linear correlation with satellite-derived estimated salinity for the period 1980 to 1997 (r = 0.72). This linear correlation between reconstructed delta(18)O(sw) and salinity makes it possible to use the reconstructed delta(18)O(sw) to estimate the past interannual and decadal salinity changes in this region. Comparisons of coral delta(18)O and delta(18)O(sw) at Rarotonga with the Pacific decadal oscillation index suggest that the decadal and interdecadal salinity and SST variability at Rarotonga appears to be related to basin-scale decadal variability in the Pacific. Copyright (C) 2002 Elsevier Science Ltd.

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1. Ice-volume forced glacial-interglacial cyclicity is the major cause of global climate variation within the late Quaternary period. Within the Australian region, this variation is expressed predominantly as oscillations in moisture availability. Glacial periods were substantially drier than today with restricted distribution of mesic plant communities, shallow or ephemeral water bodies and extensive aeolian dune activity. 2. Superimposed on this cyclicity in Australia is a trend towards drier and/or more variable climates within the last 350 000 years. This trend may have been initiated by changes in atmospheric and ocean circulation resulting from Australia's continued movement into the Southeast Asian region and involving the onset or intensification of the El Nino-Southern Oscillation system and a reduction in summer monsoon activity. 3. Increased biomass burning, stemming originally from increased climatic variability and later enhanced by activities of indigenous people, resulted in a more open and sclerophyllous vegetation, increased salinity and a further reduction in water availability. 4. Past records combined with recent observations suggest that the degree of environmental variability will increase and the drying trend will be enhanced in the foreseeable future, regardless of the extent or nature of human intervention.

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Four pollen and charcoal records derived from marine cores around the northern perimeter of Australia are examined to provide a regional picture of patterns, causes and impacts of climate change over the last 100-300 ka. The availability of radiocarbon dates and oxygen isotope records for the cores provides primary chronological control. Spectral analysis of components of these records demonstrates an overall importance of Milankovitch frequencies with clear glacial-interglacial cyclicity dominated by variation in precipitation. In addition, a number of pollen taxa, as well as charcoal particles, exhibit a 30 ka frequency that is considered, from its relationship with biomass burning and with results of past modelling, to reflect changes in the intensity of El Nino-Southern Oscillation (ENSO) variability. Pollen components of all records show a decline, frequently stepwise, in more fire-sensitive vegetation and its replacement with more fire-tolerant vegetation. There is some evidence that this trend is linked to an onset or general increase in ENSO activity and perhaps also to variation in monsoon activity dating from about 300 ka BP that was caused by changes to oceanic circulation within the Indonesian region. The trend may have accelerated within the last 45 ka due to burning by indigenous people. (C) 2003 Elsevier B.V. All rights reserved.

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Over 1000 marine and terrestrial pollen diagrams and Some hundreds of vertebrate faunal sequences have been studied in the Austral-Asian region bisected by the PEPII transect, from the Russian arctic extending south through east Asia, Indochina, southern Asia, insular Southeast Asia (Sunda), Melanesia, Australasia (Sahul) and the western south Pacific. The majority of these records are Holocene but sufficient data exist to allow the reconstruction of the changing biomes over at least the past 200,000 years. The PEPII transect is free of the effects of large northern ice caps yet exhibits vegetational change in glacial cycles of a similar scale to North America. Major processes that can be discerned are the response of tropical forests in both lowlands and uplands to glacial cycles, the expansion of humid vegetation at the Pleistocene-Holocene transition and the change in faunal and vegetational controls as humans occupy the region. There is evidence for major changes in the intensity of monsoon and El Nino-Southern oscillation variability both on glacial-interglacial and longer time scales with much of the region experiencing a long-term trend towards more variable and/or drier climatic conditions. Temperature variation is most marked in high latitudes and high altitudes with precipitation providing the major climate control in lower latitude, lowland areas. At least some boundary shifts may be the response of vegetation to changing CO2 levels in the atmosphere. Numerous questions of detail remain, however, and current resolution is too coarse to examine the degree of synchroneity of millennial scale change along the transect. (C) 2003 Elsevier Ltd and INQUA. All rights reserved.

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Methods Stepwise regression of annual data was applied to model incidence, calculated based on 91 cases, from lagged variables: antecedent precipitation, air temperature, soil water storage, absolute and relative air humidity, and Southern Oscillation Index (SOI). Results Multiple regression analyses resulted in a model, which explains 49% of the incidence variance, taking into account the absolute air humidity in the year of exposure, soil water storage and SOI of the previous 2 years. Conclusions The correlations may reflect enhanced fungal growth after increase in soil water storage in the longer term and greater spore release with increase in absolute air humidity in the short term.

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The value of a seasonal forecasting system based on phases of the Southern Oscillation was estimated for a representative dryland wheat grower in the vicinity of Goondiwindi. In particular the effects on this estimate of risk attitude and planting conditions were examined. A recursive stochastic programming approach was used to identify the grower's utility-maximising action set in the event of each of the climate patterns over the period 1894-1991 recurring In the imminent season. The approach was repeated with and without use of the forecasts. The choices examined were, at planting, nitrogen application rate and cultivar and, later in the season, choices of proceeding with or abandoning each wheat activity, The value of the forecasting system was estimated as the maximum amount the grower could afford to pay for its use without expected utility being lowered relative to its non use.

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Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.

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Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Spatial and temporal variability in wheat production in Australia is dominated by rainfall occurrence. The length of historical production records is inadequate, however, to analyse spatial and temporal patterns conclusively. In this study we used modelling and simulation to identify key spatial patterns in Australian wheat yield, identify groups of years in the historical record in which spatial patterns were similar, and examine association of those wheat yield year groups with indicators of the El Nino Southern Oscillation (ENSO). A simple stress index model was trained on 19 years of Australian Bureau of Statistics shire yield data (1975-93). The model was then used to simulate shire yield from 1901 to 1999 for all wheat-producing shires. Principal components analysis was used to determine the dominating spatial relationships in wheat yield among shires. Six major components of spatial variability were found. Five of these represented near spatially independent zones across the Australian wheatbelt that demonstrated coherent temporal (annual) variability in wheat yield. A second orthogonal component was required to explain the temporal variation in New South Wales. The principal component scores were used to identify high- and low-yielding years in each zone. Year type groupings identified in this way were tested for association with indicators of ENSO. Significant associations were found for all zones in the Australian wheatbelt. Associations were as strong or stronger when ENSO indicators preceding the wheat season (April-May phases of the Southern Oscillation Index) were used rather than indicators based on classification during the wheat season. Although this association suggests an obvious role for seasonal climate forecasting in national wheat crop forecasting, the discriminatory power of the ENSO indicators, although significant, was not strong. By examining the historical years forming the wheat yield analog sets within each zone, it may be possible to identify novel climate system or ocean-atmosphere features that may be causal and, hence, most useful in improving seasonal forecasting schemes.

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Coral bleaching events have become more frequent and widespread, largely due to elevated sea surface temperatures. Global climate change could lead to increased variability of sea surface temperatures, through influences on climate systems, e.g. El Nino Southern Oscillation (ENSO). Field observations in 1999, following a strong ENSO, revealed that corals bleached in winter after unusually cold weather. To explore the basis for these observations, the photosynthetic responses of the coral species Montipora digitata Studer were investigated in a series of temperature and light experiments. Small replicate coral colonies were exposed to ecologically relevant lower temperatures for varying durations and under light regimes that ranged from darkness to full sunlight. Photosynthetic efficiency was analyzed using a pulse amplitude modulated (PAM) fluorometer (F-0, F-m, F-v/F-m), and chlorophyll a (chl a) content and symbiotic dinoflagellate density were analyzed with spectrophotometry and microscopy, respectively. Cold temperature stress had a negative impact on M digitata colonies indicated by decreased photosynthetic efficiency (F-v/F-m), loss of symbiotic dinoflagellates and changes in photosynthetic pigment concentrations. Corals in higher light regimes were more susceptible to cold temperature stress, Moderate cold stress resulted in photoacclimatory responses, but severe cold stress resulted in photodamage, bleaching and increased mortality. Responses to cold temperature stress of M digitata appeared similar to that observed in corals exposed to warmer than normal temperatures, suggesting a common mechanism. The results of this study suggest that corals and coral reefs may also be impacted by exposure to cold as well as warm temperature extremes as climate change occurs.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.