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41.
As surface exchange processes are highly non-linear and heterogeneous in space and time, it is important to know the appropriate scale for the reasonable prediction of these exchange processes. For example, the explicit representation of surface variability has been vital in predicting mesoscale weather events such as late-afternoon thunderstorms initiated by latent heat exchanges in mid-latitude regions of the continental United States. This study was undertaken to examine the effects of different spatial scales of input data on modeled fluxes, so as to better understand the resolution needed for accurate modeling. A statistical procedure was followed to select two cells from the Southern Great Plains 1997 hydrology experiment region, each 20 km×20 km, representing the most homogeneous and the most heterogeneous surface conditions (based on soil and vegetation) within the study region. The NOAH-OSU (Oregon State University) Land Surface Model (LSM) was employed to estimate surface energy fluxes. Three scales of study (200 m, 2 and 20 km) were considered in order to investigate the impacts of the aggregation of input data, especially soil and vegetation inputs, on the model output. Model results of net radiation and latent, sensible and ground heat fluxes were compared for the three scales. For the heterogeneous area, the model output at the 20-km resolution showed some differences when compared with the 200-m and 2-km resolutions. This was more pronounced in latent heat (12% decrease), sensible heat (22% increase), and ground heat flux (44% increase) estimation than in net radiation. The scaling effects were much less for the relatively homogeneous land area with 5% increase in sensible heat and 4% decrease in ground heat flux estimation. All of the model outputs for the 2- and 20-km resolutions were in close agreement. The results suggested that, for this study region, soils and vegetation input resolution of about 2 km should be chosen for realistic modeling of surface exchange processes. This resolution was sufficient to capture the effects of sub-grid scale heterogeneity, while avoiding the data and computational difficulties associated with higher spatial resolutions.  相似文献   
42.
During strong ground motion it is expected that extended structures (such as bridges) are subjected to excitation that varies along their longitudinal axis in terms of arrival time, amplitude and frequency content, a fact primarily attributed to the wave passage effect, the loss of coherency and the role of local site conditions. Furthermore, the foundation interacts with the soil and the superstructure, thus significantly affecting the dynamic response of the bridge. A general methodology is therefore set up and implemented into a computer code for deriving sets of appropriately modified time histories and spring–dashpot coefficients at each support of a bridge with account for spatial variability, local site conditions and soil–foundation–superstructure interaction, for the purposes of inelastic dynamic analysis of RC bridges. In order to validate the methodology and code developed, each stage of the proposed procedure is verified using recorded data, finite‐element analyses, alternative computer programs, previous research studies, and closed‐form solutions wherever available. The results establish an adequate degree of confidence in the use of the proposed methodology and code in further parametric analyses and seismic design. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   
43.
The methodology for dealing with spatial variability of ground motion, site effects and soil–structure interaction phenomena in the context of inelastic dynamic analysis of bridge structures, and the associated analytical tools established and validated in a companion paper are used herein for a detailed parametric analysis, aiming to evaluate the importance of the above effects in seismic design. For a total of 20 bridge structures differing in terms of structural type (fundamental period, symmetry, regularity, abutment conditions, pier‐to‐deck connections), dimensions (span and overall length), and ground motion characteristics (earthquake frequency content and direction of excitation), the dynamic response corresponding to nine levels of increasing analysis complexity was calculated and compared with the ‘standard’ case of a fixed base, uniformly excited, elastic structure for which site effects were totally ignored. It is concluded that the dynamic response of RC bridges is indeed strongly affected by the coupling of the above phenomena that may adversely affect displacements and/or action effects under certain circumstances. Evidence is also presented that some bridge types are relatively more sensitive to the above phenomena, hence a more refined analysis approach should be considered in their case. Copyright @ 2003 John Wiley & Sons, Ltd.  相似文献   
44.
Nozzle‐type rainfall simulators are commonly used in hydrologic and soil erosion research. Simulated rainfall intensity, originating from the nozzle, increases as the distance between the point of measurement and the source is decreased. Hence, rainfall measured using rain gauges would systematically overestimate the rainfall received at the ground level. A simple model was developed to adjust rainfall measured anywhere under the simulator to plot‐wide average rainfall at the ground level. Nozzle height, plot width, gauge diameter and height, and gauge location are required to compute this adjustment factor. Results from 15 runs at different rain intensities and durations, and with different rain gauge layouts, showed that a simple average of measured rain would overestimate the plot‐wide rain by about 20 per cent. Using the adjustment factor to convert measured rainfall for individual gauges before averaging improved the estimate of plot‐wide rainfall considerably. For the 15 runs considered, overall discrepancy between actual and measured rain is reduced to less than 1 per cent with a standard error of 0·97 mm. This model can be easily tested in the ?eld by comparing rainfall depths of different sized gauges. With the adjustment factor they should all give very similar values. Copyright © 2003 John Wiley & Sons, Ltd.  相似文献   
45.
相关方法分析Nino3区SSTA和风应力的关系,发现前期风应力距平场与Nino3区SSTA有很好的相关关系,这种相关性超前8个月时就有所显现。影响Nino3区SSTA的主要风应力区域的位置随风应力超前的时间缩短均向中太平洋扩展。数值试验方法研究不同区域的风应力对热带太平洋SST作用的结果表明,强相关区域的风应力对形成和维持热带太平洋SST的气候场的作用不明显,而对SST的年际变率有重要贡献;相反,强相关区域以外的风应力对形成和维持热带太平洋SST的气候场起重要作用,但是对SST的年际变率所起的作用很不理想。  相似文献   
46.
南极海冰的年际变化对中国东部夏季降水的影响   总被引:8,自引:0,他引:8  
根据Hadley中心提供的1969—1998年的南极海冰再分析资料和其它多种观测资料,分析了南极海冰的年际和季节变化,指出南极海冰具有显著的年际变化,但与ENSO的关系则较为复杂。南极海冰维持了南半球高纬地区大气环流的季节持续性,因而对短期气候预测有较大帮助。相关分析和时间序列分析均证实中国东部夏季降水与南极海冰的年际变化有关,当北半球春夏季南极海冰增多时,华北降水增多而华南和东北降水减少。研究还表明,此种雨型分布与南极海冰变化引起的东亚夏季风环流变化有关。  相似文献   
47.
太平洋年代际振荡与中国气候变率的联系   总被引:77,自引:6,他引:77  
朱益民  杨修群 《气象学报》2003,61(6):641-654
利用 195 1~ 1998年的太平洋年代际振荡 (PDO)指数、全球海洋和大气分析资料及中国降水和气温站点观测资料 ,分析了太平洋年代际振荡在海洋中的特征及其与东亚大气环流和中国气候变率的联系。结果表明 ,PDO与东亚大气环流及中国气候年代际变化关系密切。对应于PDO暖位相期 (即中纬度北太平洋异常冷、热带中东太平洋异常暖 ) ,冬季 ,阿留申低压增强 ,蒙古高压也增强 (但东西伯利亚高压减弱 ) ,中国东北、华北、江淮以及长江流域大部分地区降水偏少 ,东北、华北和西北地区气温异常显著偏高 ,而西南和华南地区气温偏低 ;夏季 ,海平面气压在北太平洋的负异常较弱 ,而在东亚大陆的正异常较强 ,东亚夏季风偏弱 ,西太平洋副热带高压偏南 ,热带太平洋信风减弱 ,赤道西风增强 ,此时华北地区降水异常偏少而长江中下游、华南南部、东北和西北地区降水异常偏多 ,东北、华北及华南地区气温异常偏高 ,而西北、西南和长江中下游地区气温异常偏低。对应于PDO冷位相期 ,上述形势相反。结果还表明 ,处于不同阶段的ENSO事件对中国夏季气候异常的影响明显受到PDO的调制。在PDO冷位相期 ,当ENSO事件处于发展阶段 ,华南地区夏季降水偏少 ,东北地区夏季多低温 ,在其衰减阶段 ,华北地区和长江流域降水偏多 ,淮河地区降水偏少 ;  相似文献   
48.
49.
本文通过用树木年轮资料重建的祁连山地区5~7月份1310年以来的湿润指数序列,建立了一个反映该地区湿润指数年际变幅序列,对这两个序列分别进行了等级分类和干湿、强弱的时段分析,并用最大熵谱分析法对这两个序列的不同时段分别进行了周期分析。采用HK突变检验方法对这两个序列分别进行了突变分析,发现祁连山地区的湿润指数及其年际变幅存在明显的突变年份。  相似文献   
50.
The mapping of saline soils is the first task before any reclamation effort. Reclamation is based on the knowledge of soil salinity in space and how it evolves with time. Soil salinity is traditionally determined by soil sampling and laboratory analysis. Recently, it became possible to complement these hard data with soft secondary data made available using field sensors like electrode probes. In this study, we had two data sets. The first includes measurements of field salinity (ECa) at 413 locations and 19 time instants. The second, which is a subset of the first (13 to 20 locations), contains, in addition to ECa, salinity determined in the laboratory (EC2.5). Based on a procedure of cross-validation, we compared the prediction performance in the space-time domain of 3 methods: kriging using either only hard data (HK) or hard and mid interval soft data (HMIK), and Bayesian maximum entropy (BME) using probabilistic soft data. We found that BME was less biased, more accurate and giving estimates, which were better correlated with the observed values than the two kriging techniques. In addition, BME allowed one to delineate with better detail saline from non-saline areas.  相似文献   
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