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Multivariate statistical methods may be used to enhance large data bases by predicting missing information and verifying unchecked data vectors. In addition, new techniques may be used for exploratory purposes to investigate the interrelationships between variables. The techniques are being applied successfully in coal mining.  相似文献   
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Adaptive management of the marine environment requires an understanding of the complex interactions within it. Establishing levels of natural variability within and between marine ecosystems is a necessary prerequisite to this process and requires a monitoring programme which takes account of the issues of time, space and scale. In this paper, we argue that an ecosystem approach to managing the marine environment should take direct account of climate change indicators at a regional level if it is to cope with the unprecedented change expected as a result of human impacts on the earth climate system. We discuss the purpose of environmental monitoring and the importance of maintaining long-term time series. Recommendations are made on the use of these data in conjunction with modern extrapolation and integration tools (e.g. ecosystem models, remote sensing) to provide a diagnostic approach to the management of marine ecosystems, based on adaptive indicators and dynamic baselines.  相似文献   
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As a Philippine contribution to the International Heliophysical Year, we propose to use the MAGnetic Data Acquisition System/Circum Pan-Pacific Magnetometer Network (MAGDAS/CPMN), installed by the Space Environment Research Center (SERC), Kyushu University along the 210° magnetic meridian and the magnetic equator, to study the equatorial electrojet (EEJ) and counter electrojet (CEJ). Through this installation, it is made possible to observe geomagnetic field variations in real time. By utilizing this network of ground-based instruments, we hope to elucidate their regular day-to-day and seasonal variabilities and variations during magnetic storms and substorms. We also want to study the behavior of this ionospheric current system before, during, and after the occurrence of an earthquake.  相似文献   
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We separate and quantify the sources of uncertainty in projections of regional (~2,500 km) precipitation changes for the twenty-first century using the CMIP3 multi-model ensemble, allowing a direct comparison with a similar analysis for regional temperature changes. For decadal means of seasonal mean precipitation, internal variability is the dominant uncertainty for predictions of the first decade everywhere, and for many regions until the third decade ahead. Model uncertainty is generally the dominant source of uncertainty for longer lead times. Scenario uncertainty is found to be small or negligible for all regions and lead times, apart from close to the poles at the end of the century. For the global mean, model uncertainty dominates at all lead times. The signal-to-noise ratio (S/N) of the precipitation projections is highest at the poles but less than 1 almost everywhere else, and is far lower than for temperature projections. In particular, the tropics have the highest S/N for temperature, but the lowest for precipitation. We also estimate a ‘potential S/N’ by assuming that model uncertainty could be reduced to zero, and show that, for regional precipitation, the gains in S/N are fairly modest, especially for predictions of the next few decades. This finding suggests that adaptation decisions will need to be made in the context of high uncertainty concerning regional changes in precipitation. The potential to narrow uncertainty in regional temperature projections is far greater. These conclusions on S/N are for the current generation of models; the real signal may be larger or smaller than the CMIP3 multi-model mean. Also note that the S/N for extreme precipitation, which is more relevant for many climate impacts, may be larger than for the seasonal mean precipitation considered here.  相似文献   
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