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951.
�����쳣ƥ�䵼�����㷨ʵ���������� 总被引:2,自引:2,他引:0
????μ???????????????????????????????????????????????????????????????????????Simulink???湤????????????????????????????????????????????仯???????????????????????侫???????????????????????? 相似文献
952.
DAIChang-lei CHIBao-ming GAOShu-qin 《中国地理科学(英文版)》2005,15(1):60-63
Groundwater reservoir is a kind of important engineering, which can optimize water resources arrangement by means of artificial regulation. Regulated water is the blood and value performance of groundwater reservoir. To resolve the problem of real-time quantification of regulated water, the paper analyzed sources and compositions of regulated water in detail. Then, under the conditions of satisfying water demand inside research area, the paper analyzed quantity available and regulation coefficient of different regulated water and established a formula to calculate regulated water. At last, based on a pore groundwater reservoir in the middle reaches of the Yinma River,Jilin Province, the paper calculated regulated water with the formula and the result shows that the method is feasible.With some constraint conditions, the formula can be adopted in other similar areas. 相似文献
953.
With a global GSSTF2 and NCEP/NCAR reanalysis database and observation data at the Yong Xing station of Xisha Island in the South China Sea, we simulated the turbulent sensible and latent heat flux at sea surface in Chinese and neighboring seas (hereafter termed as China seas) using a common bulk method with some improved parameters. Comparing the simulated results with the observed and reanalyzed data, the improvement yielded higher accuracy, a smaller mean square deviation within 10 W/m2, and a smaller average relative error at about 25%. In addition, spatial resolution was improved to 0.1°×0.1°. The simulation is able to replay the main features of regional and seasonal variation in turbulent heat fluxes, and also the general pattern of heat flux changes during the summer monsoon outbreak in the South China Sea. 相似文献
954.
The Upper Ocean Thermal Structure and the Genesis Locations of Tropical Cyclones in the South China Sea 总被引:2,自引:1,他引:1
WANG Lei Fung Chi-Hung Lau Kai-Hon 《中国海洋大学学报(英文版)》2007,6(2):125-131
The relationship between the upper ocean thermal structure and the genesis locations of tropical cyclones (TCs) in the South China Sea (SCS) is investigated by using the Joint Typhoon Warning Center (JTWC) best-track archives and high resolution (1/4 degree) temperature analyses of the world's oceans in this paper In the monthly mean genesis positions of TCs from 1945 to 2005 in the SCS, the mean sea surface temperature (SST) was 28.8℃ and the mean depth of 26℃ water was 53.1 m. From the monthly distribution maps of genesis positions of TCs, SST and the depth of 26℃ water in the SCS, we discovered that there existed regions with SST exceeding 26℃ and 26℃ water depth exceeding 50m where no tropical cyclones formed from 1945 to 2005 in the SCS, which suggests that there were other factors unfavorable for TC formation in these regions. 相似文献
955.
Yan Su Guang-You Fang Jian-Qing Feng Shu-Guo Xing Yi-Cai Ji Bin Zhou Yun-Ze Gao Han Li Shun Dai Yuan Xiao Chun-Lai Li 《中国天文和天体物理学报》2014,(12)
To improve our understanding of the formation and evolution of the Moon,one of the payloads onboard the Chang'e-3(CE-3) rover is Lunar Penetrating Radar(LPR). This investigation is the first attempt to explore the lunar subsurface structure by using ground penetrating radar with high resolution. We have probed the subsurface to a depth of several hundred meters using LPR. In-orbit testing, data processing and the preliminary results are presented. These observations have revealed the configuration of regolith where the thickness of regolith varies from about 4 m to 6 m.In addition, one layer of lunar rock, which is about 330 m deep and might have been accumulated during the depositional hiatus of mare basalts, was detected. 相似文献
956.
Xiaomang Liu Xiangqian Dai Yidan Zhong Jinjing Li Peng Wang 《Theoretical and Applied Climatology》2013,114(1-2):183-191
The Yiluo River is the largest tributary of the middle and lower Yellow River below the Sanmenxia Dam. Hydro-climatic variables have changed in the Yiluo River during the last half century. In this study, the trends in the annual precipitation and streamflow were analyzed in the Yiluo River during 1960–2006. The results indicated that both the annual precipitation and streamflow decreased significantly (P?<?0.05) from 1960 to 2006. Pettitt’s test shows that there was a change point for annual streamflow series around the year 1986 (P?<?0.05), while there was no change point identified for the annual precipitation series from 1960 to 2006. Annual streamflow decreased more significantly than annual precipitation since 1986. The relationship between the annual precipitation and streamflow presented a non-stationary state since 1986. This non-stationary relationship was mainly influenced by human activities. The average annual amount of water diversion from the Yiluo River increased significantly since the mid-1980s, accounting for 31.3 % of the total streamflow decrease from 1986 to 2006. In addition, land use/cover change (LUCC) contributed to 27.1–29.8 % of the decrease in streamflow. Human activities, including water diversion and LUCC, together contributed to 58.4–61.1 % of the decrease in streamflow and led to the non-stationary relationship between the annual precipitation and streamflow from 1986 to 2006. This study detected the changes in the precipitation–streamflow relationship and investigated the possible causes in the Yiluo River, which will be helpful for the understanding of the changes in streamflow in the Yellow River Basin. 相似文献
957.
Liming Zhou Yuhong Tian Somnath Baidya Roy Yongjiu Dai Haishan Chen 《Climate Dynamics》2013,41(2):307-326
This paper analyzes seasonal and diurnal variations of MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data at ~1.1 km for the period of 2003–2011 over a region in West-Central Texas, where four of the world’s largest wind farms are located. Seasonal anomalies are created from MODIS Terra (~10:30 a.m. and 10:30 p.m. local solar time) and Aqua (~1:30 a.m. and 1:30 p.m. local solar time) LSTs, and their spatiotemporal variability is analyzed by comparing the LST changes between wind farm pixels (WFPs) and nearby non wind farm pixels (NNWFPs) using different methods under different quality controls. Our analyses show consistently that there is a warming effect of 0.31–0.70 °C at nighttime for the nine-year period during which data was collected over WFPs relative to NNWFPs, in all seasons for both Terra and Aqua measurements, while the changes at daytime are much noisier. The nighttime warming effect is much larger in summer than winter and at ~10:30 p.m. than ~1:30 a.m. and hence the largest warming effect is observed at ~10:30 p.m. in summer. The spatial pattern and magnitude of this warming effect couple very well with the geographic distribution of wind turbines and such coupling is stronger at nighttime than daytime and in summer than winter. Together, these results suggest that the warming effect observed in MODIS over wind farms are very likely attributable to the development of wind farms. This inference is consistent with the increasing number of operational wind turbines with time during the study period, the diurnal and seasonal variations in the frequency of wind speed and direction distribution, and the changes in near-surface atmospheric boundary layer (ABL) conditions due to wind farm operations. The nocturnal ABL is typically stable and much thinner than the daytime ABL and hence the turbine enhanced vertical mixing produces a stronger nighttime effect. The stronger wind speed and the higher frequency of the wind speed within the optimal power generation range in summer than winter and at nighttime than daytime likely drives wind turbines to generate more electricity and turbulence and consequently results in the strongest warming effect at nighttime in summer. Similarly, the stronger wind speed and the higher frequency of optimal wind speed at ~10:30 p.m. than that at ~1:30 a.m. might help explain, to some extent, why the nighttime LST warming effect is slightly larger at ~10:30 p.m. than ~1:30 a.m. The nighttime warming effect seen in spring and fall are smaller than that in summer and can be explained similarly. 相似文献
958.
959.
为评估南昌CINRAD/SAD双偏振天气雷达对地物杂波的抑制效果,使用2019年6—10月南昌单偏振雷达基数据和2022年同期南昌双偏振雷达基数据,对比分析了不同仰角和晴、雨条件下单、双偏振天气雷达反射率频率。结果表明:单、双偏振雷达在0.5°仰角因周边山区地形、建筑物遮挡的影响,在西北方向和东南方向存在明显的数据缺失。升级为双偏振雷达后,在各个仰角上周围反射率高频区的范围明显减小,雷达能有效消除雷达站点周边杂波的影响。晴天时,双偏振雷达对晴空杂波的过滤效果极佳;雨天时,双偏振雷达对南昌周边及梅岭山区的回波进行了弱化处理,可以有效减少地形回波、非气象回波的干扰。双偏振天气雷达产品差分相移率和相关系数能较清楚地辨别出虚假回波,可更好地用于确定降水粒子的信息。 相似文献
960.