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Sue Ellen Haupt Andrew J. Annunzio Kerrie J. Schmehl 《Boundary-Layer Meteorology》2013,149(2):197-217
A significant difference exists between estimates of contaminant atmospheric transport and dispersion calculated by an ensemble-averaged model and the turbulent details of any particular atmospheric transport and dispersion realization. In some cases, however, it is important to be able to make inferences of these realizations using ensemble-averaged models. It is possible to make such inferences if there are sensors in the field to report contaminant concentration observations. Any information determined about the atmospheric transport and dispersion realization can then be assimilated into a forecast model. This approach can enhance the accuracy of the atmospheric transport and dispersion forecast of a particular event. This work adopts that approach and reports on a genetic algorithm used to optimize the variational problem. Given contaminant sensor measurements and a transport and dispersion model, one can back-calculate unknown source and meteorological parameters. In this case, we demonstrate the dynamic recovery of unknown meteorological variables, including the transport variables that comprise the “outer variability” (wind speed and wind direction) and the dispersion variables that comprise the “inner variability” (contaminant spread). The optimization problem is set up in an Eulerian grid space, where the comparison of the concentration field variable between the predictions and the observations forms the cost function. The transport and dispersion parameters, which are determined from the optimization, are in Lagrangian space. This calculation is applied to continuous and instantaneous releases in a horizontally homogeneous wind field such as that observed during traditional transport and dispersion field experiments. The method proves to be successful at recovering the unknown transport and dispersion parameters for a numerical experiment. 相似文献
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Key limitations of integrated assessment models (IAMs) are their highly stylized and aggregated representation of climate damages and associated economic responses, as well as the omission of specific investments related to climate change adaptation. This paper proposes a framework for modeling climate impacts and adaptation that clarifies the relevant research issues and provides a template for making improvements. We identify five desirable characteristics of an ideal integrated assessment modeling platform, which we elaborate into a conceptual model that distinguishes three different classes of adaptation-related activities. Based on these elements we specify an impacts- and adaptation-centric IAM, whose optimality conditions are used to highlight the types of functional relationships necessary for realistic representations of adaptation-related decisions, the specific mechanisms by which these responses can be incorporated into IAMs, and the ways in which the inclusion of adaptation is likely to affect the simulations’ results. 相似文献
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Spatial and seasonal variations in CO2 and CH4 concentrations in streamwater and adjacent soils were studied at three sites on Brocky Burn, a headwater stream draining a peatland catchment in upland Britain. Concentrations of both gases in the soil atmosphere were significantly higher in peat and riparian soils than in mineral soils. Peat and riparian soil CO2 concentrations varied seasonally, showing a positive correlation with air and soil temperature. Streamwater CO2 concentrations at the upper sampling site, which mostly drained deep peats, varied from 2·8 to 9·8 mg l?1 (2·5 to 11·9 times atmospheric saturation) and decreased markedly downstream. Temperature‐related seasonal variations in peat and riparian soil CO2 were reflected in the stream at the upper site, where 77% of biweekly variation was explained by an autoregressive model based on: (i) a negative log‐linear relationship with stream flow; (ii) a positive linear relationship with soil CO2 concentrations in the shallow riparian wells; and (iii) a negative linear relationship with soil CO2 concentrations in the shallow peat wells, with a significant 2‐week lag term. These relationships changed markedly downstream, with an apparent decrease in the soil–stream linkage and a switch to a positive relationship between stream flow and stream CO2. Streamwater CH4 concentrations also declined sharply downstream, but were much lower (<0·01 to 0·12 mg l?1) than those of CO2 and showed no seasonal variation, nor any relationship with soil atmospheric CH4 concentrations. However, stream CH4 was significantly correlated with stream flow at the upper site, which explained 57% of biweekly variations in dissolved concentrations. We conclude that stream CO2 can be a useful integrative measure of whole catchment respiration, but only at sites where the soil–stream linkage is strong. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
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Christopher Packham Keith L. Thompson Almudena Zurita Johan H. Knapen Ian Smail Robert Greimel Daniel F. M. Folha Chris Benn rew Humphrey Rene Rutten David Ciardi Matthieu Bec Richard Bingham Simon Craig Kevin Dee Derek Ives Paul Jolley Peter Moore Marti Pi i Puig Simon Rees Gordon Talbot Sue Worswick 《Monthly notices of the Royal Astronomical Society》2003,345(2):395-405
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Alastair G. Dawson 《第四纪科学杂志》1989,4(3):276-277
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Summary. The secular variation of the declination, inclination and total force of the geomagnetic field has been plotted for 74 locations in North America. A comparison of the occurrences of maxima and minima in the SV curves from different stations shows little evidence of drift in North America. Although a declination maximum exhibits westward drift up to 1915, all other extrema in declination, inclination and total intensity occur almost simultaneously over a wide area. The major feature of SV in North America appears to be a 4000 nT decrease in the total field since 1850, which may be due to a decrease in the dipole moment coupled with the decay of a large non-dipole anomaly situated under the continent. Short-period changes in the rate of decrease are possibly jerks of the magnetic field. Maximum entropy spectral analysis of all three components of the field indicates periods of 102 and 53 yr. 相似文献