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51.
There is an increased demand for the accurate prediction of fog events in the Sichuan Basin (SCB) using numerical methods. A dense fog event that occurred over the SCB on 22 December 2016 was investigated. The results show that this dense fog event was influenced by the southwest of a low pressure with a weak horizontal pressure gradient and high relative humidity. This fog event showed typical diurnal variations. The fog began to form at 1800 UTC on 21 December 2016 (0200 local standard time on 22 December 2016) and dissipated at 0600 UTC on 22 December 2016 (1400 local standard time on 22 December 2016). The Weather Research and Forecasting model was able to partially reproduce the main features of this fog event and the diurnal variation in the local mountain to basin winds. The simulated horizontal visibility and liquid water content were used to characterize the fog. The mountain to basin winds had an important role in the diurnal variation of the fog event. The positive feedback mechanism between the fog and mountain to basin winds was good for the formation and maintain of the fog during the night. During the day, the mountain to basin wind displayed a transition from downslope flows to upslope flows. Water vapor evaporated easily from the warm, strong upslope winds, which resulted in the dissipation of fog during the day. The topography surrounding the SCB favored the lifting and condensation of air parcels in the lower troposphere as a result of the low height of the lifting condensation level.  相似文献   
52.
为了进一步了解青藏高原闪电的产生氮氧化物(LNOx)经由光化学反应对O3浓度变化及夏季O3低谷形成的可能影响,本文利用2005~2013年由OMI卫星得到的对流层NO2垂直浓度柱(NO2 VCD)、O3总浓度柱(TOC)和O3廓线以及星载光学瞬变探测器OTD和闪电成像仪LIS获取的总闪电数资料,对青藏高原和同纬度长江中下游地区的TOC和NO2 VCD月均值时空分布特征、闪电与NO2 VCD的相关性和O3的垂直分布特征及其与LNOx的关系进行了对比分析。结果表明,青藏高原的O3低谷主要出现在夏季和秋季,其TOC值比同纬度长江中下游地区低约10~15 DU(Dobson unit)。青藏高原NO2VCD总体较小,表现为夏高冬低的分布特征。青藏高原夏季O3浓度受南亚高压的影响总体呈减小趋势,但因强雷暴天气导致对流层中上部LNOx浓度升高,并随强上升气流向对流层顶输送,同时通过光化学反应使O3浓度增加,缩小了青藏高原和同纬度地区的O3浓度差,减缓了O3总浓度的下降,抑制了夏季O3低谷的进一步深化。  相似文献   
53.
利用逐小时风云卫星TBB资料、逐小时中国自动站与CMORPH降水产品融合数据以及国家级地面观测站24小时累积降水量,统计分析2010~2016年夏季,伴随下游地区(104°E以东)降水的青藏高原云团东传过程以及东传过程中镶嵌于云团中的中尺度对流系统(Mesoscale Convective System,简称MCS)特征。结果表明,共出现120次伴随下游降水的高原云团东传过程,6月出现最频繁,但持续时间较长的过程多出现在7月。云团向东传播的主要三条路径是平直东传、沿长江折向东传和复合东传。其中路径二——沿长江折向东传中的过程是高影响过程,因为过程次数较多(46次),过程平均持续时间较长(62小时),在下游地区引发的降水日数和暴雨日数最多。属于东传过程的MCS在7月形成最多,集中分布在青藏高原东坡、云贵高原东部、长江沿岸及其以南地区。高原MCS影响长江中下游地区降水主要是通过向东传播的形式实现,因为即使生命史更长的中α尺度对流系统(Meso-α Convective System,简称MαCS)也鲜少直接移动至110°E以东地区。不同区域的中α尺度持续性拉长形对流系统(Permanent Elongated Convective System,简称PECS)的日变化特征显示,东传过程MCS更容易在夜间从高原东坡向东传播至下游地区。在三条路径中,路径二中的东传过程MCS数量最多、在下游地区发展最旺盛并与降水日数和覆盖范围存在更好的对应关系。  相似文献   
54.
青藏高原大气热力异常对西风急流的影响   总被引:1,自引:0,他引:1  
本文基于NCEP/NCAR月平均再分析资料,分析了对流层上层200 hPa纬向西风的时空变化特征,并通过EOF分解得到一个表征西风急流位置的指数(Westerly Jet Position Index,WJPI);同时基于对流层中上层(500~200 hPa)温度纬向偏差,构建了一个描述青藏高原(简称高原)大气热力特征的指标(Plateau Atmosphere Heating Index,PAHI),定量分析了该指数与西风急流位置的关系。结果表明:由冬到夏西风急流轴不断北抬西伸,风速逐渐减小;各季西风急流轴均处于西风变率的小值区,表明各季急流均轴的位置较稳定。各季PAHI与200 hPa纬向风的显著正相关区均分布在高原北侧,即高原PAHI增强时,其北侧西风增强,南侧西风减弱,对流层上层西风急流北移;各季WJPI与PAHI之间均存在显著相关,表明PAHI异常对西风急流位置的变化有重要作用。  相似文献   
55.
青藏高原中东部夏季极端降水年代际变化特征   总被引:3,自引:2,他引:1  
曹瑜  游庆龙  马茜蓉 《气象科学》2019,39(4):437-445
基于中国国家级地面气象站基本气象要素日值数据集得到的均一化降水序列,计算了夏季极端降水指数,分析青藏高原中东部1961—2014年夏季极端降水年代际变化趋势。结果表明:青藏高原中东部地区夏季降水量占全年总降水的50%以上,且夏季降水的变化趋势存在区域性差异,北部站点主要为增加趋势,南部增加和减少趋势的站点相当。夏季极端降水除西藏东部主要为减少趋势外,其他地区主要为增加趋势,且极强降水量的年代际变化趋势显著。大部分夏季极端降水指数的变化趋势在1970s发生转折,在此之前表现为减少的趋势,之后为增加趋势。通过Mann-Kendall趋势检验,在2000年之后强降水量和极强降水量出现突变。  相似文献   
56.
Deep convection systems (DCSs) can rapidly lift water vapor and other pollutants from the lower troposphere to the upper troposphere and lower stratosphere. The main detrainment height determines the level to which the air parcel is lifted. We analyzed the main detrainment height over the Tibetan Plateau and its southern slope based on the CloudSat Cloud Profiling Radar 2B_GEOPROF dataset and the Aura Microwave Limb Sounder Level 2 cloud ice product onboard the A-train constellation of Earth-observing satellites. It was found that the DCSs over the Tibetan Plateau and its southern slope have a higher main detrainment height (about 10?16 km) than other regions in the same latitude. The mean main detrainment heights are 12.9 and 13.3 km over the Tibetan Plateau and its southern slope, respectively. The cloud ice water path decreases by 16.8% after excluding the influences of DCSs, and the height with the maximum increase in cloud ice water content is located at 178 hPa (about 13 km). The main detrainment height and outflow horizontal range are higher and larger over the central and eastern Tibetan Plateau, the west of the southern slope, and the southeastern edge of the Tibetan Plateau than that over the northwestern Tibetan Plateau. The main detrainment height and outflow horizontal range are lower and broader at nighttime than during daytime.  相似文献   
57.
The northeastern margin of the Tibetan Plateau is the youngest part of the Tibetan Plateau where tectonic activity is intense and climate change is complex. In this study, combined with field investigations, we explored accelerator mass spectrometry 14C and optically stimulated luminescence dating and palynological analysis of the sedimentary sequence in the Qingshuihe Basin to explain the origin of soft-sediment deformation layer. Dating and palynological results from the Sanchahe section in th...  相似文献   
58.
The Tibetan Plateau in Western China is the world’s largest alpine landscape, sheltering a rich diversity of native flora and fauna. In the past few decades, the Tibetan Plateau was found to suffer from grassland degradation processes. Grassland degradation is assumed to not only endanger biodiversity but also to increase the risk for natural hazards in other parts of the country which are ecologically and hydrologically connected to the area. However, the mechanisms behind the degradation processes remain poorly understood due to scarce baseline data and insufficient scientific research.We argue that remote sensing data can help to better understand degradation processes and patterns by: (1) identifying the distribution of severely degraded areas and (2) comparing the patterns of key spatial attributes of the identified areas (altitude above sea level, aspect, slope, administrative districts) with existing theories on degradation drivers. Therefore, we applied four Landsat 8 images covering large portions of the three counties Jigzhi, Baima and Darlag in the Eastern Tibetan Plateau. The dates of the Landsat scenes were selected to cover differing phenological stages of the ecosystem. Reference data were collected with a remotely piloted aircraft and a standard consumer RGB camera. To exploit the phenological information in the Landsat data as well as deal with the problem of cloud cover in multiple images, we developed a straightforward PCA-based procedure to merge the Landsat scenes. The merged Landsat data served as input to a supervised support vector machine classification which was validated with an iterative bootstrap procedure and an additional independent validation set. The considered classes were “high-cover grassland”, “grassland (including several stages of grassland vitality)”, “(severely) degraded grassland”, “green shrubland”, “grey shrubland”, “urban areas” and “water bodies”. Kappa accuracies ranged between 0.84 and 0.93 in the iterative procedure, while the independent validation led to a kappa accuracy of 0.76. Mean producer’s and user’s accuracies for all classes were higher than 80%, and confusion mainly occurred between the two shrubland classes and between the three grassland classes.Analysis of the slope, aspect and altitude values of the vegetation classes revealed that the degraded areas mostly occurred at the higher altitudes of the study area (4300–4600 m), with no strong connection to any specific slope or aspect. High-cover grassland was mostly located on sunny slopes at lower altitudes (less than 4300 m), while shrubland preferred shady, relatively steep slopes across all altitudes. These observations proved to be stable across the examined counties, while the proportions of land-cover classes differed between the examined regions. Most counties showed 5–7% severely degraded land cover. Darlag, the county located at the edge of the permafrost zone, and featuring the highest average altitude and lowest annual temperature and precipitation, was found to suffer from larger areas of severe degradation (14%).Therefore, our findings support a strong connection between degradation patterns and climatic as well as altitudinal gradients, with an increased degradation risk for high altitude areas and areas in colder and drier climatic zones. This is relevant information for pastoral management to avoid further degradation of high altitude pastures.  相似文献   
59.
针对GRACE Level2卫星时变重力数据后处理方法如何评价的问题,该文以中国数字地震观测网络获得的青藏高原地区地面重力变化图像为参考,基于平均结构相似性等图像相似度指标,研究了与该区域地面重力观测同期、不同后处理方法得到的GRACE卫星重力变化图像的可靠性。结果显示,GRACE卫星重力和地面重力观测结果具有一定的可比性,滑动窗口去相关滤波和高斯400 km滤波的组合方法可以获得最优的处理效果。本文的方法和结论对GRACE及GRACE Follow-On卫星重力数据应用中后处理方法和参数的选取有一定的借鉴意义。  相似文献   
60.
加权平均温度(Tm)是将天顶湿延迟转换为大气可降水量的关键参数,针对青藏高原地区海拔高、地形起伏大、水汽高度分布复杂的特点,本文利用2010—2014年GGOS Atmosphere Tm格网数据和地表高程数据建立Tm垂直递减率函数,进而建立一种顾及Tm垂直递减率变化的适合青藏高原地区的新模型(QTm模型)。此外,利用2015年青藏高原地区14个探空站和GGOS Atmosphere Tm格网数据评估模型精度和适用性。试验结果表明,与GGOS Atmosphere Tm相比,QTm模型的年均Bias和RMSE分别为0.29和2.49 K,相对于GPT2w-1和GPT2w-5模型,RMSE分别提升了38.97%、67.06%;与探空数据相比,QTm模型的年均Bias和RMSE分别为0.16和2.90 K,相对于GPT2w-1和GPT2w-5模型分别提升了31.12%、39.46%。新模型的构建为青藏高原地区提供了可靠的Tm值,进而提供实时、高精度GNSS水汽信息。  相似文献   
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