地表水与地下水相互作用的温度示踪与模拟研究进展

刻画地表水与地下水的相互作用过程及精确计算二者的交换量始终是个挑战,而新兴的温度示踪方法对于这方面的研究具有独特优势。重点介绍了地表水与地下水相互作用的温度示踪方法原理、应用及相关模拟的研究进展。温度示踪方法的数据获取成本低且温度适宜密集与连续监测,可对地表水与地下水相互作用过程进行精细刻画;在进行地表水与地下水相互作用的水-热耦合模拟时,温度数据可用于进一步校正模型,降低模型的不确定性,以提高交换量的计算精度。监测河水温度和河床沉积物内的水温,运用温度示踪方法研究河水与地下水的相互作用过程,并将水流及热运移数值模型相耦合,利用多源数据进行模型校正,可精细刻画地表水与地下水的交换量、相互作用带内的水流途径、流速及其变化趋势和控制因素,为地表水与地下水相互作用研究提供新的模型与方法。     

航空伽马能谱测量地形影响改正实现方法

航空伽马能谱测量受地形因素影响较大,采用常规高度改正方法对复杂地形条件下的航空伽马能谱数据进行改正,会造成结果失真。笔者结合航测动态测量特点,论述了利用航测过程中获得的地形数据,对作用带内的地形进行细化,应用点状辐射体辐射场理论,采用地形校正系数对航空伽马能谱数据进行地形影响改正的具体实现方法;通过实测的航空伽马能谱数据对该方法进行检验,并与地面异常查证的结果对比,表明该地形改正方法效果较好,基本能消除地形起伏对测量结果产生的影响。     

频域航空电磁法地形影响及校正研究

为研究起伏地形对航空电磁响应的影响,利用二维频域交错网格有限差分方法( FDFD) 计算模型中电磁场分布情况,并且用不完全乔里斯基预处理的双共轭梯度法求解大型稀疏复线性代数方程组。设计山脊和山谷两种起伏地形,同时改变坡度大小,比较不同坡度对电磁响应的影响程度。在此基础之上,提出线性校正方法,该方法具有简单快速的优点,弥补了耗时巨大的带地形的反演方法的不足。任意地形下的地形校正后的结果表明,该方法可以准确指示地下异常的存在。     

基于地面耦合的TM影像的大气校正——以珠江口为例

该文应用1998年的LANDSAT5 TM影像，对原始数据进行定标、辐射校正，求得地物的行星反射率，在简单的大气校正理论模型的基础上，根据山区阴影处植被的反射率求取大气向上垂直的透过率，反求大气光学厚度和太阳入射方向上的大气向下的透过率，从而确定大气校正的各项参数。并对大气校正前后的图像进行比较，发现校正过的影像中的典型地物的反射率和其标准的反射率值较为吻合。     

一种检测溢油的快速分类辅助鉴别方法

用气相色谱法和气相色谱-质谱法分析了原油样品的正构烷烃和甾萜烷生物标志物。针对在仪器分析过程中由各种因素带来的采集点漂移的现象,利用相关系数校正方法对保留时间进行了校正。实验结果表明,保留时间校正后大大提高了采集点的重合性。采用欧氏距离方法对校正后的色谱数据进行聚类分析,基于色谱数据的聚类分析对于降解油和非降解油的分类效果良好;而基于校正后甾、萜烷生物标志物数据的聚类分析结果能很好的将溢油样品与溢油源样品聚为一类,而与其他不相干油田的样品区分开来,聚类分析结果更能真实反映样品的真实信息。相关系数校正与快速聚类分析方法相结合为溢油来源的判断提供了一种快速分类辅助鉴别方法。     

浅析不同基准面处理对资料解释的影响

基准面是资料处理时在一个工区选用的参考面,它直接影响时深转换速度的求取和反射波层位的标定。本文通过实际资料解释,分析了不同基准面对时深转换速度以及资料解释精度的影响,为以后资料处理时正确选取基准面提供参考。     

基于机理模型的不同空间分辨率影像提取湖面面积的误差研究

本文提出了一种湖面面积误差机理模型。首先,以椭圆形(或圆形)、三角形、六边形的面状地物为例,推算不同空间分辨率遥感影像提取面积间的关系,据此推测不同空间分辨率影像提取的湖面面积之间存在着较为固定的函数关系,且函数的系数与湖面的几何形状有关。然后,构建了不同空间分辨率影像的湖面面积间的误差模型,并用多组不同影像提取了艾比湖、阿雅克库木湖面积数据验证其有效性和适应性。结果表明:误差机理模型成功模拟了低空间分辨率影像提取的湖面面积与高空间分辨率影像提取的湖面面积之间的误差关系,可在一定程度上估计误差的具体数值并予以校正。因此,该模型具有校正低分辨率影像提取的湖面面积的能力,为在大区域范围准确地提取湖面面积创造条件。     

风云气象卫星数据处理算法的若干创新

This study introduces some innovations in the data processing algorithm for Chinese FY meteorological satellites. Issues about satellite image navigation, radiation calibration, and data assimilation are discussed.
A time series of the earth＇s disk center-line count provides information on the orientation of the satellite spin axis. With this information, the altitude parameters of the satellite and then the earth disk location in the south-north direction may be solved. In each spin cycle, the satellite views the sun and the earth. Given the satellite position and altitude, the angle （β） subtended at the satellite by the sun and the earth can be calculated and predicted. Thus, the earth＇s disk location in the east-west direction is fixed. Based on this principle, we derived an automatic image navigation algorithm for FY2 geosynchronous meteorological satellites with an accuracy approaching pixel level.
The FY2 meteorological satellite traveling in a geostationary orbit suffers a large amount of radiation from the sun. The radiation varies on both diurnal and annual scales, which causes radiation responses in the thermal infrared （IR） bands wherein the wavelengths greater than 3.5 μm vibrate periodically on scales of hours to years. These vibrations must be precisely calibrated. First, based on the accurate estimation of the radiant contribution from the front-optics, the variation characteristics of the calibration parameters are obtained on a temporal scale of hours from the space-borne inner-blackbody （IBB） measurement results. Second, the in-orbit measured radiation of the lunar surface is referenced and utilized to correct the sys- tematic bias of the IBB calibration from daily to annual scales. By using such algorithms, we achieved a calibration accuracy of the FY2 satellite＇s IR imagery of less than 1 K.
The on-orbit satellite instrument parameters play an important role in data quality; however, they may be mis-measured due to limitations in the measurement conditions or may be     

Bias-Corrected Short-Range Ensemble Forecasts for Near-Surface Variables during the Summer Season of 2010 in Northern China

A running mean bias （RMB） correction ap- proach was applied to the forecasts of near-surface variables in a seasonal short-range ensemble forecasting experiment with 57 consecutive cases during summer 2010 in the northern China region. To determine a proper training window length for calculating RMB, window lengths from 2 to 20 days were evaluated, and 16 days was taken as an optimal window length, since it receives most of the benefit from extending the window length. The raw and 16-day RMB corrected ensembles were then evaluated for their ensemble mean forecast skills. The results show that the raw ensemble has obvious bias in all near-surface variables. The RMB correction can remove the bias reasonably well, and generate an unbiased ensemble. The bias correction not only reduces the ensemble mean forecast error, but also results in a better spreaderror relationship. Moreover, two methods for computing calibrated probabilistic forecast （PF） were also evaluated through the 57 case dates： 1） using the relative frequency from the RMB-eorrected ensemble; 2） computing the forecasting probabilities based on a historical rank histogram. The first method outperforms the second one, as it can improve both the reliability and the resolution of the PFs, while the second method only has a small effect on the reliability, indicating the necessity and importance of removing the systematic errors from the ensemble.     

恒温带取值与简易测温温度校正的统计分析法

在煤田地质勘探的工作中,钻井测温工作具有很重要的意义,正确的测温数据能为下一步工作顺利进行提供帮助。但是,在测温工作中,如何处理恒温带观测资料和确定简易测温孔的孔底平衡温度,是常遇到的两大棘手问题。运用统计分析法,可有效解决这两个问题。