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81.
General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.  相似文献   
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This paper assesses linear regression‐based methods in downscaling daily precipitation from the general circulation model (GCM) scale to a regional climate model (RCM) scale (45‐ and 15‐km grids) and down to a station scale across North America. Traditional downscaling experiments (linking reanalysis/dynamical model predictors to station precipitation) as well as nontraditional experiments such as predicting dynamic model precipitation from larger‐scale dynamic model predictors or downscaling dynamic model precipitation from predictors at the same scale are conducted. The latter experiments were performed to address predictability limit and scale issues. The results showed that the downscaling of daily precipitation occurrence was rarely successful at all scales, although results did constantly improve with the increased resolution of climate models. The explained variances for downscaled precipitation amounts at the station scales were low, and they became progressively better when using predictors from a higher‐resolution climate model, thus showing a clear advantage in using predictors from RCMs driven by reanalysis at its boundaries, instead of directly using reanalysis data. The low percentage of explained variances resulted in considerable underestimation of daily precipitation mean and standard deviation. Although downscaling GCM precipitation from GCM predictors (or RCM precipitation from RCM predictors) cannot really be considered downscaling, as there is no change in scale, the exercise yields interesting information as to the limit in predictive ability at the station scale. This was especially clear at the GCM scale, where the inability of downscaling GCM precipitation from GCM predictors demonstrates that GCM precipitation‐generating processes are largely at the subgrid scale (especially so for convective events), thus indicating that downscaling precipitation at the station scale from GCM scale is unlikely to be successful. Although results became better at the RCM scale, the results indicate that, overall, regression‐based approaches did not perform well in downscaling precipitation over North America. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
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Historically, paired watershed studies have been used to quantify the hydrological effects of land use and management practices by concurrently monitoring 2 similar watersheds during calibration (pretreatment) and post‐treatment periods. This study characterizes seasonal water table and flow response to rainfall during the calibration period and tests a change detection technique of moving sums of recursive residuals (MOSUM) to select calibration periods for each control–treatment watershed pair when the regression coefficients for daily water table elevation were most stable to minimize regression model uncertainty. The control and treatment watersheds were 1 watershed of 3–4‐year‐old intensely managed loblolly pine (Pinus taeda L.) with natural understory, 1 watershed of 3–4‐year‐old loblolly pine intercropped with switchgrass (Panicum virgatum), 1 watershed of 14–15‐year‐old thinned loblolly pine with natural understory (control), and 1 watershed of switchgrass only. The study period spanned from 2009 to 2012. Silvicultural operational practices during this period acted as external factors, potentially shifting hydrologic calibration relationships between control and treatment watersheds. MOSUM results indicated significant changes in regression parameters due to silvicultural operations and were used to identify stable relationships for water table elevation. None of the calibration relationships developed using this method were significantly different from the classical calibration relationship based on published historical data. We attribute that to the similarity of historical and 2010–2012 leaf area index on control and treatment watersheds as moderated by the emergent vegetation. Although the MOSUM approach does not eliminate the need for true calibration data or replace the classic paired watershed approach, our results show that it may be an effective alternative approach when true data are unavailable, as it minimizes the impacts of external disturbances other than the treatment of interest.  相似文献   
86.
Vestimentiferan tubeworms are a group of large sessile marine polychaete annelids (family Siboglinidae) found in the regions of hydrothermal venting or seepage of the reduced chemical hydrogen sulfide. Hydrocarbon seeps on the Louisiana Slope of the Gulf of Mexico support large communities of the co-occurring vestimentiferan species Lamellibrachia luymesi and Seepiophila jonesi. These sessile species have the opportunity to disperse between the patchy sites of active seepage on the seafloor during a planktonic larval stage. However, it is unclear whether dispersal occurs at a local or global scale. Four (L. luymesi) and seven (S. jonesi) microsatellite loci were used to test for population substructure among ten hydrocarbon seep sites on the Louisiana Slope. Both species showed high levels of allelic diversity, averaging 18.5 (L. luymesi) and 22 (S. jonesi) alleles/locus, respectively, and high observed heterozygosity at all microsatellite loci (0.71–0.9 in L. luymesi, 0.27–0.84 in S. jonesi). The two species showed a significant deficiency in heterozygotes compared to that predicted under the Hardy–Weinberg equilibrium. L. luymesi showed a small but significant amount of population structure, with a positive correlation between genetic and geographic distance among the sample sites spanning 540 km. S. jonesi, in contrast, showed no evidence for isolation by distance, but did show a significant genetic difference between aggregations of different ages. These results suggest that these two species differ in how larvae are able to colonize new seep sites through space (L. luymesi) and though time (S. jonesi).  相似文献   
87.
This paper focuses on the late Holocene occupation of hunter‐gatherers at the Marazzi 2 site located on the northwestern steppe of Tierra del Fuego, Chile. Our aim is to understand stratigraphy, formation processes, and pedogenesis with respect to human occupation over the last 3000 years. Based on archaeological excavations on a fluvial terrace of the Torcido River, we integrate soil micromorphology, mineralogy, geochemistry, magnetic susceptibility, and geomorphology, as well as the micro‐ and macrofrequency distributions of archaeological material. A micro‐taphonomical perspective is also applied to anthropogenic components recorded in sedimentary thin sections. We discuss various events in the interplay between soil development and human occupation through time. Marazzi 2 was witness to aggradation and pedogenesis with an episode of surface stability coincident with a phase of more intense human occupation at about 860 BC. Taphonomic analysis suggests that there are multiple occupation events mixed together, probably by biomechanical processes, resulting in a palimpsest with poor temporal resolution.  相似文献   
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89.
This paper examines whether experience of extreme weather events—such as excessive heat, droughts, flooding, and hurricanes—increases an individual’s level concern about climate change. We bring together micro-level geospatial data on extreme weather events from NOAA’s Storm Events Database with public opinion data from multiple years of the Cooperative Congressional Election Study to study this question. We find evidence of a modest, but discernible positive relationship between experiencing extreme weather activity and expressions of concern about climate change. However, the effect only materializes for recent extreme weather activity; activity that occurred over longer periods of time does not affect public opinion. These results are generally robust to various measurement strategies and model specifications. Our findings contribute to the public opinion literature on the importance of local environmental conditions on attitude formation.  相似文献   
90.
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