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There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project (CMIP2) are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least. 相似文献
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据瑞典政府网报道,瑞典执政的四党派就瑞典可持续发展的能源政策达成一致,并发布了政策文件。联合政府将通过加大对可再生能源和节能的投入,来确保能源使用的安全性和竞争力,并使瑞典的研发和企业在全球向低碳经济转变中处于领先地位。 相似文献
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Statistical Downscaling Based on Dynamically DownscaledPredictors: Application to Monthly Precipitation in Sweden 总被引:3,自引:0,他引:3
A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors. It is tested whether a three-step method can improve conventional one-step statistical downscaling. The method uses predictors that are upscaled from a dynamical downscaling instead of predictors taken directly from a GCM simulation. The method is applied to downscaling of monthly precipitation in Sweden. The statistical model used is a multiple regression model that uses indices of large-scale atmospheric circulation and 850-hPa specific humidity as predictors. Data from two GCMs (HadCM2 and ECHAM4) and two RCM experiments of the Rossby Centre model (RCA1) driven by the GCMs are used. It is found that upscaled RCA1 predictors capture the seasonal cycle better than those from the GCMs, and hence increase the reliability of the downscaled precipitation. However, there are only slight improvements in the simulation of the seasonal cycle of downscaled precipitation. Due to the cost of the method and the limited improvements in the downscaling results, the three-step method is not justified to replace the one-step method for downscaling of Swedish precipitation. 相似文献
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基于瑞典条分法数值解的边坡蒙特卡罗可靠性分析 总被引:1,自引:0,他引:1
本文基于瑞典条分法数值解的基本思想,建立了蒙特卡罗(Monte-Carlo)边坡可靠性分析计算模型,对云南省香格里拉县冷都复杂斜坡体前缘滑动体的稳定性进行了分析,计算结果表明该复杂斜坡体在目前状况下具有较高的稳定系数和可靠度,在降雨和地震作用下稳定性差,需要采取工程措施进行加固。 相似文献
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2008年6月23~26日,第29届国际雷电防护会议(ICLP:International Conference on Lightning Protection,简称ICLP2008)在瑞典乌普萨拉(Uppsala)召开。ICLP是国际上关于雷电防护方法和技术研究方面最重要的学术交流活动之一,自1951年首次举办ICLP以来,ICLP一直致力于为全世界的科研和工程人员提供一个良好的交流平台,通过多学科之间的交叉融合,实现雷电防护方法和技术 相似文献