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1.
B. Rajagopalan U. Lall D. G. Tarboton D. S. Bowles 《Stochastic Environmental Research and Risk Assessment (SERRA)》1997,11(1):65-93
A nonparametric resampling technique for generating daily weather variables at a site is presented. The method samples the
original data with replacement while smoothing the empirical conditional distribution function. The technique can be thought
of as a smoothed conditional Bootstrap and is equivalent to simulation from a kernel density estimate of the multivariate
conditional probability density function. This improves on the classical Bootstrap technique by generating values that have
not occurred exactly in the original sample and by alleviating the reproduction of fine spurious details in the data. Precipitation
is generated from the nonparametric wet/dry spell model as described in Lall et al. [1995]. A vector of other variables (solar
radiation, maximum temperature, minimum temperature, average dew point temperature, and average wind speed) is then simulated
by conditioning on the vector of these variables on the preceding day and the precipitation amount on the day of interest.
An application of the resampling scheme with 30 years of daily weather data at Salt Lake City, Utah, USA, is provided. 相似文献
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Vertical dynamic and thermodynamic characteristics of urban lower boundary layer and its relationship with aerosol concentration over Beijing 总被引:1,自引:0,他引:1
By utilizing observational data from a 325 m tower of the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences (CAS) on March 19-29, 2001 and August 11-25, 2003, a comprehensive study was conducted on the vertical dynamical and thermodynamic characteristics of the urban lower boundary layer (ULBL) and its relationship with aerosol concentration over Beijing. Firstly, a comparative analysis was made on the gradient data (wind, temperature and humidity), ultrasonic data (atmospheric turbulences) and air-quality observations at different tower heights (47, 120 and 280 m). Secondly, a diagnosis was made to reveal the major features of normalized variances of velocity and temperature, turbulence kinetic energy as well as their relationship with aerosol concentrations. Furthermore, the characteristics of the ULBL vertical structure and the TSP concentration/distribution variations during a sand/dust weather process were also analyzed. The outcome of the study showed that under unstable stratification, the normalized variances of velocity (σu/u*, σv/u*, σw/u*) and temperature (σT/T*) at 47 and 120 m heights fit the Monin-Obukhov similarity (MOS) framework and the fitting formulas were given out accordingly. According to the stratification parameter (z′/L), the stable ULBL could be divided into 2 zones. With z′/L<0.1, it was a weakly stable zone and MOS framework was applicable. The other was a highly stable zone with z′/L>0.1 and the normalized velocity variances tended to increase along with higher stability, but it remained constant for normalized temperature variances. At daytime, the near-surface layer includes two heights of 47 and 120 m, while 280 m has been above it. The ULBL analysis in conjunction with a sand/dust weather process in Beijing in March 2001 indicated that the maximum concentration of Total Suspended Particulates (TSP) at 320 m reached 913.3 μg/m3 and the particles were transported from the upper to lower ULBL, which was apparently related to the development process of a low-level jet and its concomitant strong sinking motion. 相似文献
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天气雷达作为龙卷风监测预警的重要手段之一,应用具有超高时空分辨率的X波段双极化相控阵天气雷达系统,较好地捕获并提前预警龙卷风。以2022年6月19日07时发生在广东佛山南海的一次龙卷风为例,详细剖析龙卷生消及雷达监测预警过程。借助雷达智能预警软件,利用X波段双极化相控阵天气雷达的双偏振量和超高时空分辨率数据,实时反演三维风场和分析龙卷碎片(TVS)特征,能够显著提高龙卷风监测预警水平。实例表明,本次成功地提前18分钟预警龙卷,进一步说明了X波段双极化相控阵天气雷达在强对流天气探测方面具有较强的生命力。 相似文献
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Stochastic weather generators are statistical models that produce random numbers that resemble the observed weather data on which they have been fitted; they are widely used in meteorological and hydrologi- cal simulations. For modeling daily precipitation in weather generators, first-order Markov chain-dependent exponential, gamma, mixed-exponential, and lognormal distributions can be used. To examine the perfor- mance of these four distributions for precipitation simulation, they were fitted to observed data collected at 10 stations in the watershed of Yishu River. The parameters of these models were estimated using a maximum-likelihood technique performed using genetic algorithms. Parameters for each calendar month and the Fourier series describing parameters for the whole year were estimated separately. Bayesian infor- mation criterion, simulated monthly mean, maximum daily value, and variance were tested and compared to evaluate the fitness and performance of these models. The results indicate that the lognormal and mixed-exponential distributions give smaller BICs, but their stochastic simulations have overestimation and underestimation respectively, while the gamma and exponential distributions give larger BICs, but their stochastic simulations produced monthly mean precipitation very well. When these distributions were fitted using Fourier series, they all underestimated the above statistics for the months of June, July and August. 相似文献
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