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91.
基于高分辨率格点数据集CN05.1和区域气候模式RegCM4对4个全球气候模式动力降尺度模拟(CdR、EdR、HdR、MdR),识别了观测和模拟的1981—2005年中国群发性高温事件(CHTE)。在此基础上,评估了模式对中国CHTE的模拟能力。结果表明:4个动力降尺度模拟以及多模式集合(MME)均能很好地模拟出中国CHTE频次、持续时间和累计强度的空间分布。不过,HdR模拟的CHTE发生次数在新疆地区略偏少,而其他3个模拟试验的CHTE次数在中国东南部略偏多。观测中CHTE持续时间、极端强度、累计强度、最大影响面积、平均影响面积、综合强度等的频率分布规律均能被合理再现。MME也能很好模拟观测揭示的CHTE综合强度以及频次、持续时间、强度、影响面积等单项指标的上升趋势。单模式成员亦可再现大多数指标的上升趋势,但也存在一定不足,如EdR模拟的CHTE综合强度呈减弱趋势,MdR模拟的CHTE频次和极端强度呈弱的下降趋势。  相似文献   
92.
基于CFS模式的中国站点夏季降水统计降尺度预测   总被引:6,自引:2,他引:4  
刘颖  范可  张颖 《大气科学》2013,37(6):1287-1296
本研究针对中国夏季站点降水,研制建立了基于Climate Forecast System(CFS)实时预测数值产品及观测资料的统计降尺度预测系统。此预测系统选取了CFS模式中当年夏季500 hPa高度场和观测资料中前一年秋、冬季海表面温度场作为预测因子,两因子的关键区分别为泛东亚地区和热带太平洋地区。统计降尺度模型对1982~2011年中国夏季降水的回报效果较CFS模式原始结果显著提高,空间距平相关系数由0.03提高到0.31,时间相关系数在中国大部分地区显著提高,最大可达0.6。均方根误差较CFS模式原始结果明显降低,同时,此降尺度模型较好的回报出2011年汛期降水的距平百分率的空间分布型。  相似文献   
93.
An effective statistical downscaling scheme was developed on the basis of singular value decomposition to predict boreal winter(December-January-February)precipitation over China.The variable geopotential height at 500 hPa(GH5)over East Asia,which was obtained from National Centers for Environmental Prediction’s Coupled Forecast System(NCEP CFS),was used as one predictor for the scheme.The preceding sea ice concentration(SIC)signal obtained from observed data over high latitudes of the Northern Hemisphere was chosen as an additional predictor.This downscaling scheme showed significantly improvement in predictability over the original CFS general circulation model(GCM)output in cross validation.The multi-year average spatial anomaly correlation coefficient increased from–0.03 to 0.31,and the downscaling temporal root-mean-square-error(RMSE)decreased significantly over that of the original CFS GCM for most China stations.Furthermore,large precipitation anomaly centers were reproduced with greater accuracy in the downscaling scheme than those in the original CFS GCM,and the anomaly correlation coefficient between the observation and downscaling results reached~0.6 in the winter of 2008.  相似文献   
94.
BP-CCA方法用于四川盆地夏季日降水量的可预报性研究   总被引:1,自引:0,他引:1  
基于BP-CCA方法,首先讨论了多个因子对四川盆地夏季降水降尺度模型的可预报性,然后选取最佳预报因子并进行集合,最终基于T639模式建立最优多因子降尺度预报模型.结果表明,分别以东亚夏季10m纬向风、700hPa纬向风和700hPa相对湿度为预报因子的降尺度模型对四川盆地夏季降水的预报技巧较高,而将三个因子集合的多因子降尺度预报模型具有更好的预报能力.进一步将该方法应用于T639模式预报的预报因子场,发现多因子降尺度模型对降水的预报效果要优于T639模式直接输出的结果.  相似文献   
95.
本文采用区域高分辨率海洋数值模型,将谱松弛动力降尺度方法应用于吕宋海峡及其邻近区域,对吕宋海峡黑潮流径的流型特征进行模拟与分析。实验结果显示,应用谱松弛法能够较好地改善区域模型的模拟效果:通过约束大尺度误差,不仅能直接约束区域内的大尺度海洋状态,也间接调整了小尺度过程的演变规律,改善了吕宋海峡黑潮流径的模拟效果。  相似文献   
96.
We downscaled atmospheric reanalysis data using linear regression and Bayesian neural network (BNN) ensembles to obtain daily maximum and minimum temperatures at ten weather stations in southern Quebec and Ontario, Canada. Performance of the linear and non-linear downscaling models was evaluated using four different sets of predictors, not only in terms of their ability to reproduce the magnitude of day-to-day variability (i.e., “weather,” mean absolute error between the daily values of the predictand(s) and the downscaled data) but also in terms of their ability to reproduce longer time scale variability (i.e., “climate,” indices of agreement between the predictand's observed annual climate indices and the corresponding downscaled values). The climate indices used were the 90th percentile of the daily maximum temperature, 10th percentile of the daily minimum temperature, number of frost days, heat wave duration, growing season length, and intra-annual temperature range.

Our results show that the non-linear models usually outperform their linear counterparts in the magnitude of daily variability and, to a greater extent, in annual climate variability. In particular, the best model simulating weather and climate was a BNN ensemble using stepwise selection from 20 reanalysis predictors, followed by a BNN ensemble using the three leading principal components from the aforementioned predictors. Finally, we showed that, on average, the first three indices presented higher skills than the growing season length, number of frost days, and the heat wave duration.  相似文献   

97.
Jia Liu  Michaela Bray  Dawei Han 《水文研究》2012,26(20):3012-3031
Accurate information of rainfall is needed for sustainable water management and more reliable flood forecasting. The advances in mesoscale numerical weather modelling and modern computing technologies make it possible to provide rainfall simulations and forecasts at increasingly higher resolutions in space and time. However, being one of the most difficult variables to be modelled, the quality of the rainfall products from the numerical weather model remains unsatisfactory for hydrological applications. In this study, the sensitivity of the Weather Research and Forecasting (WRF) model is investigated using different domain settings and various storm types to improve the model performance of rainfall simulation. Eight 24‐h storm events are selected from the Brue catchment, southwest England, with different spatial and temporal distributions of the rainfall intensity. Five domain configuration scenarios designed with gradually changing downscaling ratios are used to run the WRF model with the ECMWF 40‐year reanalysis data for the periods of the eight events. A two‐dimensional verification scheme is proposed to evaluate the amounts and distributions of simulated rainfall in both spatial and temporal dimensions. The verification scheme consists of both categorical and continuous indices for a first‐level assessment and a more quantitative evaluation of the simulated rainfall. The results reveal a general improvement of the model performance as we downscale from the outermost to the innermost domain. Moderate downscaling ratios of 1:7, 1:5 and 1:3 are found to perform better with the WRF model in giving more reasonable results than smaller ratios. For the sensitivity study on different storm types, the model shows the best performance in reproducing the storm events with spatial and temporal evenness of the observed rainfall, whereas the type of events with highly concentrated rainfall in space and time are found to be the trickiest case for WRF to handle. Finally, the efficiencies of several variability indices are verified in categorising the storm events on the basis of the two‐dimensional rainfall evenness, which could provide a more quantitative way for the event classification that facilitates further studies. It is important that similar studies with various storm events are carried out in other catchments with different geographic and climatic conditions, so that more general error patterns can be found and further improvements can be made to the rainfall products from mesoscale numerical weather models. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   
98.
气候影响评价中统计降尺度若干问题的探讨   总被引:14,自引:0,他引:14       下载免费PDF全文
全球气候模式是目前研究未来气候变化的重要工具,然而其较低的空间分辨率使其难以被直接用于区域尺度的气候影响评价中,统计降尺度常常被用于弥补这一不足。对统计降尺度的3种主要方法:转化函数法,天气分型法和天气发生器法的最新研究进展进行了归纳;论述了统计降尺度中的各种不确定性;总结了统计降尺度在中国的发展和应用。统计降尺度与动力降尺度的比较和结合、极端事件的降尺度以及统计降尺度的不确定性将成为未来的主要发展方向。  相似文献   
99.
以湄公河流域为研究区,采用区域气候模式RegCM3为模拟工具,以根系层土壤含水量为代表性指标,对A1B情景下未来研究区月尺度农业干旱进行了预估。基于地表能量平衡原理,系统分析了降水、蒸发、地表温度和根系层土壤含水量等农业干旱主要影响因素与区域气候模式模拟的大气环流、地表感热通量、地表潜热通量、地表净通量之间的联系和变化规律,从气陆间能量和水汽通量平衡角度,对农业干旱发生机理进行了识别。预估结果表明:从年内各月地表净通量和地表温度变化来看,未来春末(6月)和秋末(10月)湄公河流域温度增加明显,且土壤含水量减少也较为明显;同时,这两个时段蒸发旺盛和降水减少的趋势,有可能导致流域局部地区(尤其是非灌溉农业区)农业干旱的发生。  相似文献   
100.
利用空间分辨率为5km的广西智能网格降雨量预报产品以及桂南区域自动气象站降雨量实况资料,采用最邻近点法、双线性插值、双三次插值和统计降尺度方法,研究和评估空间分辨率在1km的格点降雨量插值预报释用技术。结果表明:(1)对于分辨率较高的智能网格预报产品,最邻近点法、双线性插值和双三次插值的预报效果无明显差异,其中最邻近点法的ETS评分和预报偏差略好于其它两种方法;(2)采用一元线性回归的统计降尺度方法比其它3种方法的降水预报能力高,并可以提高强降水的预报评分,对构造更高分辨率的网格预报产品具有一定参考作用。  相似文献   
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