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Based on 25-year(1987–2011) tropical cyclone(TC) best track data, a statistical study was carried out to investigate the basic features of upper-tropospheric TC–environment interactions over the western North Pacific. Interaction was defined as the absolute value of eddy momentum flux convergence(EFC) exceeding 10 m s~(-1)d~(-1). Based on this definition, it was found that 18% of all six-hourly TC samples experienced interaction. Extreme interaction cases showed that EFC can reach~120 m s~(-1)d~(-1) during the extratropical-cyclone(EC) stage, an order of magnitude larger than reported in previous studies.Composite analysis showed that positive interactions are characterized by a double-jet flow pattern, rather than the traditional trough pattern, because it is the jets that bring in large EFC from the upper-level environment to the TC center. The role of the outflow jet is also enhanced by relatively low inertial stability, as compared to the inflow jet. Among several environmental factors, it was found that extremely large EFC is usually accompanied by high inertial stability, low SST and strong vertical wind shear(VWS). Thus, the positive effect of EFC is cancelled by their negative effects. Only those samples during the EC stage, whose intensities were less dependent on VWS and the underlying SST, could survive in extremely large EFC environments, or even re-intensify. For classical TCs(not in the EC stage), it was found that environments with a moderate EFC value generally below ~25 m s~(-1)d~(-1) are more favorable for a TC's intensification than those with extremely large EFC.  相似文献   
994.
Based on observational precipitation at 63 stations in South China and NCEP NCAR reanalysis data during 1951 2010,a cluster analysis is performed to classify large-scale circulation patterns responsible for persistent precipitation extremes(PPEs) that are independent of the influence of tropical cyclones(TCs).Conceptual schematics depicting configurations among planetary-scale systems at different levels are established for each type.The PPEs free from TCs account for 38.6%of total events,and they tend to occur during April August and October,with the highest frequency observed in June.Corresponding circulation patterns during June August can be mainly categorized into two types,i.e.,summer-Ⅰ type and summer-Ⅱtype.In summer-Ⅰ type,the South Asian high takes the form of a zonal-belt type.The axis of upstream westerly jets is northwest-oriented.At the middle level,the westerly jets at midlatitudes extend zonally.Along the southern edge of the westerly jet,synoptic eddies steer cold air to penetrate southward;the Bay of Bengal(BOB) trough is located to the north;a shallow trough resides over coastal areas of western South China;and an intensified western Pacific subtropical high(WPSH) extends westward.The anomalous moisture is mainly contributed by horizontal advection via southwesterlies around 20°N and southeasterlies from the southern flange of the WPSH.Moisture convergence maximizes in coastal regions of eastern South China,which is the very place recording extreme precipitation.In summer-Ⅱ type,the South Asian high behaves as a western-center type.The BOB trough is much deeper,accompanied by a cyclone to its north;and a lower-level trough appears in northwestern parts of South China.Different to summer-Ⅰ type,moisture transport via southwesterlies is mostly responsible for the anomalous moisture in this type.The moisture convergence zones cover Guangdong,Guangxi,and Hainan,matching well with the areas of flooding.It is these set combinations among different systems at different levels that trigger PPEs in South China.  相似文献   
995.
Considering the characteristics of nonlinear problems, a new method based on the L-curve method and including the concept of entropy was designed to select the regularization parameter in the one-dimensional variational analysis-based sounding retrieval method. In the first iteration, this method uses an empirical regularization parameter derived by minimizing the entropy of variables. During subsequent iterations, it uses the L-curve method to select the regularization parameter in the vicinity of the regularization parameter selected in the last iteration. The new method was employed to select the regularization parameter in retrieving atmospheric temperature and moisture profiles from Atmospheric Infrared Sounder radiance measurements selected from the first day of each month in 2008. The results show that compared with the original L-curve method, the new method yields 5.5% and 2.5% improvements on temperature and relative humidity profiles, respectively. Compared with the discrepancy principle method, the improvements on temperature and relative humidity profiles are 1.6% and 2.0%, respectively.  相似文献   
996.
Big data has emerged as the next technological revolution in IT industry after cloud computing and the Internet of Things. With the development of climate observing systems, particularly satellite meteorological observation and high-resolution climate models, and the rapid growth in the volume of climate data, climate prediction is now entering the era of big data. The application of big data will provide new ideas and methods for the continuous development of climate prediction. The rapid integration, cloud storage, cloud computing, and full-sample analysis of massive climate data makes it possible to understand climate states and their evolution more objectively, thus predicting the future climate more accurately. This paper describes the application status of big data in operational climate prediction in China; it analyzes the key big data technologies, discusses the future development of climate prediction operations from the perspective of big data, speculates on the prospects for applying climatic big data in cloud computing and data assimilation, and puts forward the notion of big data-based super-ensemble climate prediction methods and computerbased deep learning climate prediction methods.  相似文献   
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颜娇珑  张武  单云鹏  柳丹 《高原气象》2016,(4):1073-1086
利用常规地面观测资料和CALIOP/CALIPSO卫星遥感资料统计分析了中国西北东部霾的多年变化以及霾事件期间气溶胶光学特性的垂直空间分布特征,并以2013年3月和11月发生在西北东部的霾天气为例分析了霾发生时大气气溶胶粒子的形状及大小的垂直分布特征、对应的天气形势和气象要素的变化。结果表明:西北东部霾日出现频率由20世纪80年代至90年代末逐渐减小,但21世纪起又明显增加;霾事件主要发生在11、12和1月。霾发生时,在对流层内霾影响最严重的区域在距地面2~4 km范围,垂直方向气溶胶后向散射系数的范围集中于0.8×10-3~2.5×10-3km-1·sr-1,且随高度增加而增大;气溶胶的体积退偏比大部分20%,气溶胶较为规则,不规则的多分布在地表向上4 km以下,随着高度的增加气溶胶不规则性减弱。色比数值大部分0.8,8~12 km气层中主要是色比为0.0~0.4的粒子。当高空受高压系统控制,地面为均压场,近地面出现逆温层时易产生霾。  相似文献   
1000.
基于Fisher判别的南方双季稻低温灾害等级预警   总被引:4,自引:3,他引:1       下载免费PDF全文
为了建立南方双季稻低温灾害综合预测预警技术体系, 基于南方双季稻种植区1961—2010年708个气象站的逐日气象资料、水稻生育期资料和低温灾害发生的气象行业标准,采用Fisher判别分析法、因子膨化法、相关性分析法,利用SPSS软件构建早稻春季低温灾害高风险区 (Ⅰ区) 未来10 d、晚稻寒露风高风险区 (Ⅰ区)、主灾区 (Ⅱ区) 未来5 d的低温灾害发生等级逐日滚动预警模型。其中,1961—2009年资料用于模型构建和回代检验,2010年资料用于模型的外延预测。结果表明:早稻、晚粳稻、晚籼稻Ⅰ区平均外延预测基本一致准确率分别达到90.5%,74.2%,80.3%,晚粳稻、晚籼稻Ⅱ区平均外延预测基本一致准确率分别为89.4%和80.3%。构建的南方双季稻低温灾害逐日滚动预警模型的外延预测基本一致准确率多超过80%,等级预测检验误差总体上在1个等级以内,模型评价效果较好。  相似文献   
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