全文获取类型
收费全文 | 220篇 |
免费 | 55篇 |
国内免费 | 63篇 |
专业分类
测绘学 | 5篇 |
大气科学 | 127篇 |
地球物理 | 83篇 |
地质学 | 50篇 |
海洋学 | 23篇 |
综合类 | 8篇 |
自然地理 | 42篇 |
出版年
2024年 | 3篇 |
2023年 | 2篇 |
2022年 | 4篇 |
2021年 | 16篇 |
2020年 | 16篇 |
2019年 | 9篇 |
2018年 | 9篇 |
2017年 | 7篇 |
2016年 | 9篇 |
2015年 | 9篇 |
2014年 | 13篇 |
2013年 | 27篇 |
2012年 | 14篇 |
2011年 | 24篇 |
2010年 | 9篇 |
2009年 | 10篇 |
2008年 | 10篇 |
2007年 | 28篇 |
2006年 | 15篇 |
2005年 | 10篇 |
2004年 | 12篇 |
2003年 | 12篇 |
2002年 | 8篇 |
2001年 | 5篇 |
2000年 | 7篇 |
1999年 | 10篇 |
1998年 | 5篇 |
1997年 | 5篇 |
1996年 | 7篇 |
1995年 | 6篇 |
1994年 | 5篇 |
1993年 | 4篇 |
1992年 | 2篇 |
1990年 | 1篇 |
1989年 | 2篇 |
1987年 | 1篇 |
1984年 | 1篇 |
1980年 | 1篇 |
排序方式: 共有338条查询结果,搜索用时 515 毫秒
21.
Variables fields such as enstrophy, meridional-wind and zonal-wind variables are derived from monthly 500 hPa geopotential height anomalous fields. In this work, we select original predictors from monthly 500-hPa geopotential height anomalous fields and their variables in June of 1958 - 2001, and determine comprehensive predictors by conducting empirical orthogonal function (EOF) respectively with the original predictors. A downscaling forecast model based on the back propagation (BP) neural network is built by use of the comprehensive predictors to predict the monthly precipitation in June over Guangxi with the monthly dynamic extended range forecast products. For comparison, we also build another BP neural network model with the same predictands by using the former comprehensive predictors selected from 500-hPa geopotential height anomalous fields in May to December of 1957 - 2000 and January to April of 1958 - 2001. The two models are tested and results show that the precision of superposition of the downscaling model is better than that of the one based on former comprehensive predictors, but the prediction accuracy of the downscaling model depends on the output of monthly dynamic extended range forecast. 相似文献
22.
对商丘国家观象台1954--2005年月报表中挑取的符合暴雨日条件的142个样本分析,结果表明:商丘暴雨日具有明显的季节性,频发于7、8月份;暴雨日年平均2.73个;日暴雨量最大(193.3mm)不超过200mm;最长连续暴雨日数不超过2日;连续暴雨日降水量累计(223.9mm)不超过250mm;1h最大降水量不超过70mm。暴雨目的年代际变化特征明显,20世纪80年代后暴雨日出现较晚,60--90年代的暴雨日数递减,90年代后有增加趋势;大暴雨日数自60年代起有逐步增加趋势。暴雨日对月、年降水量有显著贡献,4—9月暴雨日对月降水量的贡献很大,且从4月到7月暴雨目的贡献呈递增趋势。一年内暴雨日出现5次时,当年的年雨量为偏多年份。 相似文献
23.
24.
亚洲夏季风系统成员与西太平洋副高的相关特征分析 总被引:9,自引:8,他引:9
利用500hPa月平均高度距平场派生出涡度变化、经向风切变、纬向风切变等变量场。从1958~2001年6月500hPa月平均高度距平场及其派生变量场中选取预报因子,并将各个场中的因子分别作EOF分解,得到浓缩了初选因子变量大部分信息的综合预报因子,用以建立同月的广西月降水量的BP神经网络预报模型。进而利用2002~2005年月动力延伸集合预报产品及其派生变量,对广西6月降水量作BP神经网络降尺度释用预报。作为对比试验,以相同的预报量,从1957~2000年5~12月及1958~2001年1~4月500hPa月平均高度距平场中选取预报因子,并作相同处理,建立前期综合因子的广西6月降水量BP神经网络预报模型。独立样本试验结果表明,利用同期综合因子建立的BP神经网络降尺度预报模型的拟合精度优于利用前期综合因子建立的预报模型,但预报效果依赖于月动力延伸集合预报产品。 相似文献
25.
选择我国华北地区若干流域,建立了三个月降水径流模型——统计模型、比利时模型和新安江模型。分析结果表明;统计模型能较好地反映流域输出对输入的响应,新安江模型(改进后)则能较好地描述半干旱地区流域的产汇流特性,模型拟合效果也较好,而比利时模型,经初步应用,拟合效果比新安江模型差。 相似文献
26.
A new single-station model (SSM) for monthly median values of the ionospheric parameters foF2 and M(3000)F2 has been developed. Fourier analysis provides a tool for decomposing the time-varying ionospheric parameters. The 12–month smoothed sunspot number R
12
was used as an external solar characteristic because of its availability and predictability. However, for the first time, the solar activity is described not only by R
12
, but also by the linear coefficient K
R
representing the tendency of the change of solar activity. A general non-linear approximation of the influence of the solar-cycle characteristics R
12
and K
R
and ionospheric parameters foF2 and M(3000)F2 was accepted. The new SSM is applied to several European stations and its statistical evaluation shows better results than the other two SSMs used in the paper. The approach described in the paper does not contradict the use of different synthetic ionospheric indices (as the T-index, MF2–index); the basic aim is to show only that using one additional new characteristic of the solar-cycle variations, such as K
R
, improves the monthly median model. 相似文献
27.
Rainfall prediction is of vital importance in water resources management. Accurate long-term rainfall prediction remains an open and challenging problem. Machine learning techniques, as an increasingly popular approach, provide an attractive alternative to traditional methods. The main objective of this study was to improve the prediction accuracy of machine learning-based methods for monthly rainfall, and to improve the understanding of the role of large-scale climatic variables and local meteorological variables in rainfall prediction. One regression model autoregressive integrated moving average model (ARIMA) and five state-of-the-art machine learning algorithms, including artificial neural networks, support vector machine, random forest (RF), gradient boosting regression, and dual-stage attention-based recurrent neural network, were implemented for monthly rainfall prediction over 25 stations in the East China region. The results showed that the ML models outperformed ARIMA model, and RF relatively outperformed other models. Local meteorological variables, humidity, and sunshine duration, were the most important predictors in improving prediction accuracy. 4-month lagged Western North Pacific Monsoon had higher importance than other large-scale climatic variables. The overall output of rainfall prediction was scalable and could be readily generalized to other regions. 相似文献
28.
ERA-Interim气温数据在中国区域的适用性评估 总被引:5,自引:0,他引:5
运用中国756个观测站点的逐月平均气温数据,对比分析了ERA-Interim再分析资料的误差。结果发现:ERA-Interim再分析资料能够很好地反映观测值的年际变化,相关性达到0.955~0.995。ERA-Interim在580个站点的冷偏差或暖偏差小于1℃,占站点总数的76.7%,可信度较高。64个站点的冷偏差或暖偏差大于5℃,可信度较低。ERA-Interim在东部地区的暖偏差多于西部地区,冷偏差的高值主要集中在西部地区的高海拔站点。海拔低于200 m的站点偏差最小,适用性好,多数海拔3 000 m以上的站点呈现较大冷偏差,适用性较差。通过回归分析发现,观测站点与ERA-Interim格点的高度差是导致误差的主要原因,因此通过高程校正能够有效降低误差,提高ERA-Interim适用性。 相似文献
29.
潘海 《中国海洋湖沼学报》1993,11(1):80-88
A stratification parameter ,defined as theamount of mechanical energy required to bring about vertical mixing, has been calculated for theYellow Sea using available data over the past ten years.T he monthly distributions of Log are obtained to explain the features of the Yellow Sea stratification.Fronts of the shallow shelf sea are often inseparably related with its stratifications. The front of the Yellow Sea in the warm half-year is generated in May and disappears in November. The shelf front moves shoreward and becomes strong in the heating season, but becomes weak in the cooling season upon return. 相似文献
30.
We demonstrate that there is significant skill in the GloSea5 operational seasonal forecasting system for predicting June mean rainfall in the middle/lower Yangtze River basin up to four months in advance.Much of the rainfall in this region during June is contributed by the mei-yu rain band.We find that similar skill exists for predicting the East Asian summer monsoon index(EASMI)on monthly time scales,and that the latter could be used as a proxy to predict the regional rainfall.However,there appears to be little to be gained from using the predicted EASMI as a proxy for regional rainfall on monthly time scales compared with predicting the rainfall directly.Although interannual variability of the June mean rainfall is affected by synoptic and intraseasonal variations,which may be inherently unpredictable on the seasonal forecasting time scale,the major influence of equatorial Pacific sea surface temperatures from the preceding winter on the June mean rainfall is captured by the model through their influence on the western North Pacific subtropical high.The ability to predict the June mean rainfall in the middle and lower Yangtze River basin at a lead time of up to 4 months suggests the potential for providing early information to contingency planners on the availability of water during the summer season. 相似文献