全文获取类型
收费全文 | 2496篇 |
免费 | 754篇 |
国内免费 | 696篇 |
专业分类
测绘学 | 119篇 |
大气科学 | 924篇 |
地球物理 | 519篇 |
地质学 | 1008篇 |
海洋学 | 566篇 |
天文学 | 54篇 |
综合类 | 158篇 |
自然地理 | 598篇 |
出版年
2024年 | 9篇 |
2023年 | 41篇 |
2022年 | 114篇 |
2021年 | 150篇 |
2020年 | 139篇 |
2019年 | 123篇 |
2018年 | 131篇 |
2017年 | 154篇 |
2016年 | 150篇 |
2015年 | 187篇 |
2014年 | 194篇 |
2013年 | 233篇 |
2012年 | 172篇 |
2011年 | 156篇 |
2010年 | 153篇 |
2009年 | 171篇 |
2008年 | 175篇 |
2007年 | 164篇 |
2006年 | 135篇 |
2005年 | 148篇 |
2004年 | 124篇 |
2003年 | 124篇 |
2002年 | 119篇 |
2001年 | 101篇 |
2000年 | 92篇 |
1999年 | 72篇 |
1998年 | 67篇 |
1997年 | 50篇 |
1996年 | 45篇 |
1995年 | 42篇 |
1994年 | 38篇 |
1993年 | 27篇 |
1992年 | 49篇 |
1991年 | 20篇 |
1990年 | 25篇 |
1989年 | 12篇 |
1988年 | 22篇 |
1987年 | 7篇 |
1986年 | 1篇 |
1984年 | 3篇 |
1983年 | 2篇 |
1982年 | 1篇 |
1981年 | 1篇 |
1980年 | 1篇 |
1979年 | 1篇 |
1977年 | 1篇 |
排序方式: 共有3946条查询结果,搜索用时 234 毫秒
101.
通过对西藏藏北高原多格错仁盐湖湖岸3101cm高度剖面进行地形地貌、地层沉积特征、矿物学特征及粒度、频率磁化率等气候环境变化指标的分析研究发现,整个剖面反映出大致6个较大的气候变化过程:233. 3kaBP~223. 5kaBP气候波动较大,总体趋势气候趋于干冷,期间出现过两次较温暖气候,之后气候逐渐变冷;在223. 5kaBP~213. 6kaBP总体变化为气温大幅度上升,但在期间有一次较大的相对冷干过程;213. 6kaBP~170kaBP之间总体变化气候趋于变冷,中间有2次明显的气候变暖湿过程及两次冷干过程;170kaBP~117. 1kaBP气候转为明显湿热;117. 1kaBP~75. 6kaBP气候变化趋势明显降低;75. 6kaBP~56. 7kaBP气候又明显上升达到湿热状态。以上气候波动规律与极地冰芯记录及深海氧同位素记录的古气候波动规律有很好的一致性,同时本盐湖区与柴达木盆地察尔汗盐湖区的CH0310钻孔及青海湖南岸二郎剑阶地的 QH 86钻孔所揭示的中更新世晚期以来的气候变化的分析对比,发现西藏羌北的多格错仁盐湖区与青海的察尔汗盐湖区及青海湖湖区在更新世中晚期以来的气候环境变迁存在极好的可比性,说明青藏高原的气候演化在中晚更新世以来基本具有一致性,在时间上的微小超前与滞后具有区域上的细微变化,说明气候变迁在不同的区域又具有各自的独特性。 相似文献
102.
ABSTRACTRain-on-snow (ROS) has the potential to produce devastating floods by enhancing runoff from snowmelt. Although a common phenomenon across the eastern United States, little research has focused on ROS in this region. This study used a gridded observational snow dataset from 1960–2009 to establish a comprehensive seasonal climatology of ROS for this region. Additionally, different rain and snow thresholds were compared while considering temporal trends in ROS occurrence at four grid cells representing individual locations. Results show most ROS events occur in MAM (March-April-May). ROS events identified with rainfall >1 cm are more frequent near the east coast and events identified with >1 cm snow loss are more common in higher latitudes and/or elevations. Decreasing trends in DJF (December-January-February) ROS events were identified near the coastal areas, with increasing trends in the northern portion of the domain. Significant decreasing trends in MAM ROS are likewise present on a regional scale. Factors playing a role in snowpack depth and rainfall, such as movement of storm tracks in this region, should be considered with future work to discern mechanisms causing the changes in ROS frequency. 相似文献
103.
中国物理海洋学研究70年:发展历程、学术成就概览 总被引:2,自引:2,他引:0
魏泽勋 郑全安 杨永增 刘克修 徐腾飞 王凡 胡石建 谢玲玲 李元龙 杜岩 周磊 林霄沛 胡建宇 朱建荣 李均益 张正光 侯一筠 刘泽 田纪伟 黄晓冬 管玉平 刘志宇 杨庆轩 赵玮 宋振亚 刘海龙 董昌明 于卫东 连涛 陈朝晖 史久新 雷瑞波 刘煜 于福江 尹宝树 陈戈 王岩峰 李整林 熊学军 汪嘉宁 李晓峰 王永刚 《海洋学报》2019,41(10):23-64
本文概略评述新中国成立70年来物理海洋学各分支研究领域的发展历程和若干学术成就。中国物理海洋学研究起步于海浪、潮汐、近海环流与水团,以及以风暴潮为主的海洋气象灾害的研究。随着国力的增强,研究领域不断拓展,涌现了大量具有广泛影响力的研究成果,其中包括:提出了被国际广泛采用的“普遍风浪谱”和“涌浪谱”,发展了第三代海浪数值模式;提出了“准调和分析方法”和“潮汐潮流永久预报”等潮汐潮流的分析和预报方法;发现并命名了“棉兰老潜流”,揭示了东海黑潮的多核结构及其多尺度变异机理等,系统描述了太平洋西边界流系;提出了印度尼西亚贯穿流的南海分支(或称南海贯穿流);不断完善了中国近海陆架环流系统,在南海环流、黑潮及其分支、台湾暖流、闽浙沿岸流、黄海冷水团环流、黄海暖流、渤海环流,以及陆架波方面均取得了深刻的认识;从大气桥和海洋桥两个方面对太平洋–印度洋–大西洋洋际相互作用进行了系统的总结;发展了浅海水团的研究方法,基本摸清了中国近海水团的分布和消长特征与机制,在大洋和极地水团分布及运动研究方面也做出了重要贡献;阐明了南海中尺度涡的宏观特征和生成机制,揭示了中尺度涡的三维结构,定量评估了其全球物质与能量输运能力;基本摸清了中国近海海洋锋的空间分布和季节变化特征,提出了地形、正压不稳定和斜压不稳定等锋面动力学机制;构建了“南海内波潜标观测网”,实现了对内波生成–演变–消亡全过程机理的系统认识;发展了湍流的剪切不稳定理论,提出了海流“边缘不稳定”的概念,开发了海洋湍流模式,提出了湍流混合参数化的新方法等;在海洋内部混合机制和能量来源方面取得了新的认识,并阐述了混合对海洋深层环流、营养物质输运等过程的影响;研发了全球浪–潮–流耦合模式,推出一系列海洋与气候模式;发展了可同化主要海洋观测数据的海洋数据同化系统和用于ENSO预报的耦合同化系统;建立了达到国际水准的非地转(水槽/水池)和地转(旋转平台)物理模 型实验平台;发展了ENSO预报的误差分析方法,建立了海洋和气候系统年代际变化的理论体系,揭示了中深层海洋对全球气候变化的响应;初步建成了中国近海海洋观测网;持续开展南北极调查研究;建立了台风、风暴潮、巨浪和海啸的业务化预报系统,为中国气象减灾提供保障;突破了国外的海洋技术封锁,研发了万米水深的深水水听器和海洋光学特性系列测量仪器;建立了溢油、危险化学品漂移扩散等预测模型,为伴随海洋资源开发所带来的风险事故的应急处理和预警预报提供科学支撑。文中引用的大量学术成果文献(每位第一作者优选不超过3篇)显示,经过70年的发展,中国物理海洋学研究培养了一支实力雄厚的科研队伍,这是最宝贵的成果。这支队伍必将成为中国物理海洋学研究攀登新高峰的主力军。 相似文献
104.
This work presents a canonical study on a wedge entering water near a single piece of ice using computational-fluid-dynamics (CFD) and a Wagner-type theoretical model with corrections for non-linear effects. Calculations for a series of conditions with ice of different sizes and locations relative to the wedge are conducted. The hydrodynamic force due to impact, the pressure distribution on the wedge surface, and the pile-up phenomenon are examined to study the role of ice in the impact process. The theoretical model is shown to be accurate and can serve as a useful method to assess slamming loads under the influence of ice. It is shown that even for the case of a small piece of ice, the slamming force on the wedge can increase by 30%. 相似文献
105.
106.
The impacts of mountain pine beetle disturbance on the energy balance of snow during the melt period 下载免费PDF全文
Christopher M. Welch Paul C. Stoy F. Aaron Rains Aiden V. Johnson Brian L. McGlynn 《水文研究》2016,30(4):588-602
Mountain snowpacks provide most of the annual discharge of western US rivers, but the future of water resources in the western USA is tenuous, as climatic changes have resulted in earlier spring melts that have exacerbated summer droughts. Compounding changes to the physical environment are biotic disturbances including that of the mountain pine beetle (MPB), which has decimated millions of acres of western North American forests. At the watershed scale, MPB disturbance increases the peak hydrograph, and at the stand scale, the ‘grey’ phase of MPB canopy disturbance decreases canopy snow interception, increases snow albedo, increases net shortwave radiation, and decreases net longwave radiation versus the ‘red’ phase. Fewer studies have been conducted on the red phase of MPB disturbance and in the mixed coniferous stands that may follow MPB‐damaged forests. We measured the energy balance of four snowpacks representing different stages of MPB damage, management, and recovery: a lodgepole pine stand, an MPB‐infested stand in the red phase, a mixed coniferous stand (representing one successional trajectory), and a clear‐cut (representing reactive management) in the Tenderfoot Creek Experimental Forest in Montana, USA. Net longwave radiation was lower in the MPB‐infested stand despite higher basal area and plant area index of the other forests, suggesting that the desiccated needles serve as a less effective thermal buffer against longwave radiative losses. Eddy covariance observations of sensible and latent heat flux indicate that they are of similar but opposite magnitude, on the order of 20 MJ m?2 during the melt period. Further analyses reveal that net turbulent energy fluxes were near zero because of the temperature and atmospheric vapour pressure encountered during the melt period. Future research should place snow science in the context of forest succession and management and address important uncertainties regarding the timing and magnitude of needlefall events. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
107.
Caroline Dolant Alexandre Langlois Benoit Montpetit Ludovic Brucker Alexandre Roy Alain Royer 《水文研究》2016,30(18):3184-3196
Currently observed climate warming in the Arctic has numerous consequences. Of particular relevance, the precipitation regime is modified where mixed and liquid precipitation can occur during the winter season leading to rain‐on‐snow (ROS) events. This phenomenon is responsible for ice crust formation, which has a significant impact on ecosystems (such as biological, hydrological, ecological and physical processes). The spatially and temporally sporadic nature of ROS events makes the phenomenon difficult to monitor using meteorological observations. This paper focuses on the detection of ROS events using passive microwave (PMW) data from a modified brightness temperature (TB) gradient approach at 19 and 37 GHz. The approach presented here was developed empirically for observed ROS events with coincident ground‐based PMW measurements in Sherbrooke, Quebec, Canada. It was then tested in Nunavik, Quebec, with the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E). We obtained a detection accuracy of 57, 71 and 89% for ROS detection for three AMSR‐E grid cells with a maximum error of 7% when considering all omissions and commissions with regard to the total number of AMSR‐E passes throughout the winter period. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
108.
Journal of Geographical Sciences - Lake ice phenology is considered a sensitive indicator of regional climate change. We utilized time series information of this kind extracted from a series of... 相似文献
109.
海冰参数的合理取值是海洋工程海冰灾害风险评估的重要内容。利用1950—2018年的冰情等级(5个等级)数据,进行了1950—2018、1950—1990、1991—2018三种情景下的回归分析,确定了不同时期的冰情等级概率分布密度函数。利用鲅鱼圈雷达观测站2002—2017年的海冰现场实测资料,分别对鲅鱼圈附近海域一般冰厚、最大冰厚、最小冰厚进行概率分布拟合。基于上述概率分布结果,给出不同冰情等级的重现期,进而对海冰作业条件给出的设计参考值进行评价。结果表明:1990年以后2级、3级冰情重现期相对1990年之前变小,4级、5级冰情重现期相对1990年之前变大,规范给出重现期范围已不能代表辽东湾冬季海冰情况。本研究成果可为辽东湾海洋工程可靠性设计提供重要数据支撑。 相似文献
110.
Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size,random sampling,predictor quality,and validation procedures 下载免费PDF全文
Historically, observing snow depth over large areas has been difficult. When snow depth observations are sparse, regression models can be used to infer the snow depth over a given area. Data sparsity has also left many important questions about such inference unexamined. Improved inference, or estimation, of snow depth and its spatial distribution from a given set of observations can benefit a wide range of applications from water resource management, to ecological studies, to validation of satellite estimates of snow pack. The development of Light Detection and Ranging (LiDAR) technology has provided non‐sparse snow depth measurements, which we use in this study, to address fundamental questions about snow depth inference using both sparse and non‐sparse observations. For example, when are more data needed and when are data redundant? Results apply to both traditional and manual snow depth measurements and to LiDAR observations. Through sampling experiments on high‐resolution LiDAR snow depth observations at six separate 1.17‐km2 sites in the Colorado Rocky Mountains, we provide novel perspectives on a variety of issues affecting the regression estimation of snow depth from sparse observations. We measure the effects of observation count, random selection of observations, quality of predictor variables, and cross‐validation procedures using three skill metrics: percent error in total snow volume, root mean squared error (RMSE), and R2. Extremes of predictor quality are used to understand the range of its effect; how do predictors downloaded from internet perform against more accurate predictors measured by LiDAR? Whereas cross validation remains the only option for validating inference from sparse observations, in our experiments, the full set of LiDAR‐measured snow depths can be considered the ‘true’ spatial distribution and used to understand cross‐validation bias at the spatial scale of inference. We model at the 30‐m resolution of readily available predictors, which is a popular spatial resolution in the literature. Three regression models are also compared, and we briefly examine how sampling design affects model skill. Results quantify the primary dependence of each skill metric on observation count that ranges over three orders of magnitude, doubling at each step from 25 up to 3200. Whereas uncertainty (resulting from random selection of observations) in percent error of true total snow volume is typically well constrained by 100–200 observations, there is considerable uncertainty in the inferred spatial distribution (R2) even at medium observation counts (200–800). We show that percent error in total snow volume is not sensitive to predictor quality, although RMSE and R2 (measures of spatial distribution) often depend critically on it. Inaccuracies of downloaded predictors (most often the vegetation predictors) can easily require a quadrupling of observation count to match RMSE and R2 scores obtained by LiDAR‐measured predictors. Under cross validation, the RMSE and R2 skill measures are consistently biased towards poorer results than their true validations. This is primarily a result of greater variance at the spatial scales of point observations used for cross validation than at the 30‐m resolution of the model. The magnitude of this bias depends on individual site characteristics, observation count (for our experimental design), and sampling design. Sampling designs that maximize independent information maximize cross‐validation bias but also maximize true R2. The bagging tree model is found to generally outperform the other regression models in the study on several criteria. Finally, we discuss and recommend use of LiDAR in conjunction with regression modelling to advance understanding of snow depth spatial distribution at spatial scales of thousands of square kilometres. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献