一种痕量氦氖氢的检测方法及其化探效果

通过反吹原理,在保护分子筛色谱柱的前提下,利用气相色谱法设计了一套可以检测痕量氦、氖、氢的技术方法.该方法具有测量范围宽,灵敏度高,分析时间短,使用寿命长,操作简单等优点,具有较好的应用前景.利用该方法检测出黄桥氦气田上方土壤中的非烃气异常,取得了较好的验证效果.     

GPS地面段平稳过渡测试验证方案研究与思考

简要介绍了GPS系统地面段的发展历程,重点阐述了地面段平稳过渡期间测试验证的流程设计和测试验证系统的方案设计,明确了GPS地面段从系统研制到在线运行各个阶段的测试验证过程,深入分析了其设计思想和成功经验。通过总结归纳得到启示,对我国北斗卫星导航系统地面段升级换代测试验证方案设计有一定的借鉴意义。     

星载高级合成孔径雷达波模式算法及其反演数据精度验证

搭载在欧洲环境卫星(ENVISAT)上的高级合成孔径雷达(Advanced Synthetic Aperture Radar,ASAR)二级波模式数据提供了诸多海浪信息包括有效波高、波向、波长和二维海浪谱等,在海浪预报模式中具有重要作用。本文拟利用浮标观测数据对ASAR波模式算法及其反演数据精度进行对比验证。由于SAR卫星在海面的特殊成像机制,不同海况下会有不同的测量结果,通过与美国国家浮标中心(NDBC)的浮标数据对比,显示ASAR有效波高在高海况下低估和在低海况下高估的现象,在中等海况下的测量结果较优。通过研究ASAR数据集中对应的海浪谱,按照能量与方向分布可分为四种类型:单一方向海浪谱(Ⅰ类谱),180°方向模糊海浪谱(Ⅱ类谱),海浪两个方向且能量分布杂乱(Ⅲ类谱),多个传播方向且谱型杂乱海浪谱(Ⅳ类谱)。探究在不同类型下的海浪参数的精度,结果表明在单一波向正常海浪谱情况下,有效波高、波向与浮标数据一致性较好,存在180°方向模糊的对称海浪谱仅有效波高精度较高,谱型杂乱的海浪谱海浪有效波高和波向反演结果均较差。     

基于Lasso回归模型的青岛海洋经济和海洋产业分析

为促进青岛海洋产业结构优化和海洋经济高质量发展,文章构建评价指标体系,采用Lasso回归模型分析对青岛海洋经济发展产生重要影响的海洋产业,并提出发展建议。研究结果表明：青岛海洋经济发展水平评价指标体系包括海洋渔业、海洋化工业、海洋进出口总额、海洋环境、海洋交通运输业和滨海旅游业6个大类和20个特征变量;采用10折交叉验证确定调节系数的最优取值,并通过求解Lasso回归系数最终筛选10个特征变量进入回归模型;根据回归系数估计值,国内旅客数量的重要性最强,海洋渔业产值的重要性较强,而货物吞吐量的重要性较弱;Lasso回归模型的预测准确率、模型泛化能力和可信度均较高,属于稳健的稀疏模型;未来青岛应进一步发挥滨海旅游业和海洋渔业等的产业优势,着力发展海洋交通运输业,保护海洋生态环境以及加大海洋科技研发投入。     

激电中梯和激电测深在吉林和龙市石马洞钼矿的应用

为了在吉林东部覆盖较厚地区寻找深部隐伏矿体,在和龙市石马洞钼矿勘查中利用中间梯度装置激发极化法扫面,发现了极化率为2.00%～5.18%、电阻率≤2 000Ω.m的高极化率低阻异常。异常体上对称四极装置激电测深结果表明：11勘查线极化体顶面埋深15～30 m,底面埋深〉500 m;经钻探工程验证,钼矿体的形态、产状、顶...     

粘土心墙坝漫顶溃坝过程离心模型试验与数值模拟

利用作者研制成功的溃坝离心模型试验系统,对粘土心墙坝漫顶溃决过程进行了试验研究,结果发现粘土心墙坝与均质坝溃决机理与溃口发展规律明显不同,随着漫坝水流对下游坝壳冲蚀程度的增加,粘土心墙发生剪断破坏,溃口洪水流量迅速增大.基于上述试验结果,提出了一个描述粘土心墙坝漫顶溃坝过程的数学模型,并建议了相应的数值计算方法.该模型...     

MODIS气溶胶光学厚度在长江三角洲地区适用性分析

利用太湖、浙江林学院和千岛湖站点AERONET数据对MODIS气溶胶光学厚度适用性进行验证表明,长江三角洲地区MODIS气溶胶光学厚度反演精度具有较大的地域差异,太湖站点显著偏高,达到MODIS精度设计范围(±0.05±0.15τ)的数据仅占30.0%左右,不具有显著适用性,地表反射率估计不足是造成太湖MODIs反演误...     

ArcGIS支持下高分辨率遥感影像解译效率提高方法

探讨了在Arc GIS支持下提高人机交互解译生产效率的方法和关键技术,包括多用户并发编辑和协同验证的遥感影像解译系统、双重编码策略、基于要素模板的属性自动赋值、拓扑错误避免和批处理。通过2013年全国水土流失动态监测遥感影像解译检验了其合理性和高效性,为提高遥感影像人机交互解译生产效率提供了生产经验。     

An improved wind speed algorithm for “Jason-1” altimeter under tropical cyclone conditions

Rain effect and lack of in situ validation data are two main causes of tropical cyclone wind retrieval errors. The National Oceanic and Atmospheric Administration＇s Climate Prediction Center Morphing technique （CMORPH） rain rate is introduced to a match-up dataset and then put into a rain correction model to remove rain effects on ＂Jason-1＂ normalized radar cross section （NRCS）; Hurricane Research Division （HRD） wind sPeed, which integrates all available surface weather observations, is used to substitute in situ data for establishing this relationship with ＂Jason-l＂ NRCS. Then, an improved ＂Jason-l＂ wind retrieval algorithm under tropical cyclone conditions is proposed. Seven tropical cyclones from 2003 to 2010 are studied to validate the new algorithm. The experimental results indicate that the standard deviation of this algorithm at C-band and Ku-band is 1.99 and 2.75 m/s respectively, which is better than the existing algorithms. In addition, the C-band algorithm is more suitable for sea surface wind retrieval than Ku-band under tropical cyclone conditions.     

一个区域海洋——海冰——大气耦合模式中的北极气候偏差：年结果检验

The Coupling of three model components, WRF/PCE （polar climate extension version of weather research and forecasting model （WRF））, ROMS （regional ocean modeling system）, and CICE （community ice code）, has been implemented, and the regional atmosphere-ocean-sea ice coupled model named WRF/PCE- ROMS-CICE has been validated against ERA-interim reanalysis data sets for 1989. To better understand the reasons that generate model biases, the WRF/PCE-ROMS-CICE results were compared with those of its components, the WRF/PCE and the ROMS-CICE. There are cold biases in surface air temperature （SAT） over the Arctic Ocean, which contribute to the sea ice concentration （SIC） and sea surface temperature （SST） biases in the results of the WRF/PCE-ROMS-CICE. The cold SAT biases also appear in results of the atmo- spheric component with a mild temperature in winter and similar temperature in summer. Compared to results from the WRF/PCE, due to influences of different distributions of the SIC and the SST and inclusion of interactions of air-sea-sea ice in the WRF/PCE-ROMS-CICE, the simulated SAT has new features. These influences also lead to apparent differences at higher levels of the atmosphere, which can be thought as responses to biases in the SST and sea ice extent. There are similar atmospheric responses in feature of distribution to sea ice biases at 700 and 500 hPa, and the strength of responses weakens when the pressure decreases in January. The atmospheric responses in July reach up to 200 hPa. There are surplus sea ice ex- tents in the Greenland Sea, the Barents Sea, the Davis Strait and the Chukchi Sea in winter and in the Beau- fort Sea, the Chukchi Sea, the East Siberian Sea and the Laptev Sea in summer in the ROMS-CICE. These differences in the SIC distribution can all be explained by those in the SST distributions. These features in the simulated SST and SIC from ROMS-CICE also appear in the WRF/PCE-ROMS-CICE. It is shown that the performance of the WRF/PCE-ROMS-CICE is determined to a l