常见冰晶粒子散射特性的初步研究

在不考虑吸收情况下，利用光线跟踪法计算了卷云中经常存在的不同形状冰晶的散射相函数。计算结果显示实心柱状冰晶散射相函数的特征是存在２２°晕和４６°峰；空心柱状冰晶则在１２０°处可以见到另外一个峰；而子弹形冰晶在０°和２２°间出现一个附加峰。并用简单的几何分析解释了某些散射特性。     

星载微波散射计的在轨定标技术现状及展望

星载微波散射计通过测量海面不同方位向的后向散射系数反演出海面的风速和风向,为了满足测量精度要求,必须对其进行在轨定标.本文总结了现有微波散射计的在轨定标技术,包括有源定标器法、陆地自然目标法、海洋目标法和星星交叉定标法;然后分析了每种定标方法的优缺点;最后,描述了现有定标方法适用扇形波束体制散射计和笔形波束圆锥扫描体制散射计的特性.     

光静态散射测试系统的研究与实现

随着科学技术的发展,对粒子的大小、浓度及其他特性的探测已经发展成为一个专门的研究领域和现代测量学中的一个重要分支,而光散射法已经成为一种常用的粒子测量方法;为了满足应用需求,文中提出了一种基于C8051F500单片机的光静态散射测试系统方案,详细介绍了该测试系统的设计理论原理、硬件电路的设计依据、固件程序的设计思想和测试系统的具体实现;选取一定浓度的样品溶液,运用该系统进行光散射的角度依赖性测试,实际测量值与理论依据基本相符;在不同激光功率下,对同一角度的散射光强进行测试,将测量得到的数据分析,线性度良好,满足设计要求。     

微波湿度计探测青藏高原卷云和温湿度分布

鉴于青藏高原地区的气象站和探空数据观测数据非常有限,且其卷云和温湿度分布对全球气候有重要影响,提出联合风云三号卫星微波湿度计(FengYun-3C microwave humidity and temperature sounder,FY-3C MWHTS)在轨观测数据和欧洲中值预报中心发布的青藏高原地区再分析数据,采用改进的神经网络方法分析上对流层和低平流层大气卷云极化和散射信息敏感性,开发青藏高原地区大气卷云检测反演算法。进而利用在轨实时运行的FY-3C星微波湿温探测仪数据提取青藏高原地区全天候大气卷云信息,研究青藏高原区域卷云随季节的变化规律和分布特征。     

基于BRDF模型的玉米叶片散射特性分析

本文完成了对红光和近红外光源下的玉米不同叶位的散射光分布的测量.通过对测量结果进行计算分析得到了样本的BRDF值.并建立了相应的Cook-Torrance模型,定量计算分析了不同叶位样本在不同入射光下的散射特性.结果表明,用这种方法分析叶片的散射特性是可行和有效的.     

毫米波/亚毫米波冰云探测辐射计模型仿真

冰云对全球气候的显著影响,使得利用毫米波/亚毫米波辐射计探测冰云分布持续受到关注。为从辐射计亮温测量值中反演出冰云粒子参数,完善的辐射传输正演模型起到非常关键的作用。针对即将发射的冰云成像仪毫米波/亚毫米波星载辐射计,建立起了包含粒子散射在内的完整的辐射传输模型。传输模型读取大气廓线及云层粒子微观参数,仿真计算得到辐射计各通道的辐射亮温。给出了辐射传输模型的详细配置,并分析了不同通道对云层粒子的敏感性。结果表明：冰云成像仪各通道对冰云粒子、雪粒子均有很强的敏感性,但只有低频率通道能探测到水云粒子、雨粒子的变化。辐射计通道中,不同的中心频率对冰晶粒子敏感度不同,从而可使辐射计探测不同高度、不同特性的粒子。对于同一中心频率,不同频偏对应不同的大气透明度,使得辐射计可进一步探测到不同高度的云层信息。仿真工作将会为后续的毫米波/亚毫米波辐射计设计、反演算法研究等打下良好的基础。     

后向散射光法血糖检测方法的研究

基于对细胞微观散射进行的理论仿真计算,推导出血糖浓度与细胞后向散射光之间的近似数值关系,在此基础上提出了一种新的血糖浓度光学无创测量方法--后向散射光血糖浓度测量方法,根据以此方法为基本思想,设计了一个测量系统又加以验证.在对一系列被测者进行的测量实验中,测量数据能很好地反映出被测者的血糖浓度变化.     

馈电网络子结构三端口散射参数测量方法研究

从多模馈电网络子结构的特性出发,对可能获取子结构三端口散射参数的方法进行了分析、比较,在现有二端口矢量网络分析仪的基础上,考虑了端口的阻抗匹配,对馈电网络子结构的三端口散射参数测量进行了实验研究,并应用混合模式散射参数验证了测量方法的准确性,为整个多模馈电网络的设计和优化提供有力的支持。     

整体式惯性粒子分离器雷达散射特性数值仿真

为了探究整体式惯性粒子分离器(IPS)的雷达散射特性,利用物理光学迭代法(IPO),编制了整体式粒子分离器的RCS计算程序,发展了一种改进的高效遮挡关系判断算法,并对程序的计算精度进行了校验。对不同雷达波长下,不同构型整体式粒子分离器的前向雷达散射特性进行了计算和分析比较。结果表明,随着雷达波长的增大,IPS的雷达散射面积减小;IPS分流器径向位置对重点方位角度范围内的雷达散射面积(RCS)有一定影响,并为改善IPS的雷达散射特性提供了参考依据。     

基于相位测量的微波位移测量方法

为满足建筑结构全天候、高精度及低成本的位移监测要求,提出了基于相位测量的微波位移测量方法。该方法以微波作为全天候测量信号,利用高精度相位测量实现高精度位移监测,并采用低成本的标准频率器件搭建位移测量系统。实验结果表明:系统位移测量精度可达0.12 mm,并验证了系统具有全天候、高精度、低成本的位移监测特性。     

Passive microwave algorithms for sea ice concentration: A comparison of two techniques

The most comprehensive large-scale characterization of the global sea ice cover so far has been provided by satellite passive microwave data. Accurate retrieval of ice concentrations from these data is important because of the sensitivity of surface flux (e.g., heat, salt, and water) calculations to small changes in the amount of open water (leads and polynyas) within the polar ice packs. Two algorithms that have been used for deriving ice concentrations from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in winter but larger disagreements in the seasonal regions and in summer. In some areas in the Antarctic, the Bootstrap technique shows ice concentrations higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows ice concentrations lower by as much as 30%. The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher concentrations than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies.     

Studies of the Antarctic sea ice edge and ice extent from satellite and ship observations

Passive microwave-derived ice edge locations in the Antarctic are assessed against in situ observations from ships between 1989 and 2000. During the growth season (March-October), the ship data agrees with satellite data very well, with r² values of 0.99 and 0.97 for the Bootstrap and Team algorithms, respectively. During the melt season (November-February), the agreement is not so good with the passive microwave ice edge typically 1-2° of latitude south of the observations. This is due to the low concentration and saturated nature of the ice, and the r² values for this period are 0.92 and 0.80 for the Bootstrap and Team algorithms, respectively. Sensitivity studies show that such an offset in the summer ice edge location can cause significant errors in trend studies of the extent of sea ice cover in the Southern Ocean. The passive microwave ice concentration at the ice edge observed by ship varies greatly, averaging 14% for the Team algorithm and 19% for the Bootstrap. Comparisons between passive microwave data and SAR, Landsat and OLS data during the ice growth season show that while small-scale details in ice edge location are lost, the passive microwave data generally provide good and consistent representation of the higher resolution imagery.     

A Modeling and Rendering Method for Snow by Using Metaballs

The display of natural scenes such as mountains, trees, the earth as viewed from space, the sea, and waves have been attempted. Here a method to realistically display snow is proposed. In order to achieve this, two important elements have to be considered, namely the shape and shading model of snow, based on the physical phenomenon. In this paper, a method for displaying snow fallen onto objects, including curved surfaces and snow scattered by objects, such as skis, is proposed. Snow should be treated as particles with a density distribution since it consists of water particles, ice particles, and air molecules. In order to express the material property of snow, the phase functions of the particles must be taken into account, and it is well-known that the color of snow is white because of the multiple scattering of light. This paper describes a calculation method for light scattering due to snow particles taking into account both multiple scattering and sky light, and the modeling of snow.     

冰雪微波遥感研究进展

对微波冰雪遥感及应用研究作了概要的介绍,重点介绍了海冰遥感监测与相关数据的应用、分析和处理,同时,介绍了微波遥感在我国冰川积雪、冻土研究中的应用及成果,并对微波冰雪遥感研究的前景作了简要的分析和展望。     

Passive microwave signature observations of the Baltic Sea ice

Passive microwave signatures of various Baltic Sea ice types and open water leads were measured in the spring of 1995 and in March 1997 with airborne non‐imaging microwave radiometers (MWR) operating in the frequency range from 6.8 to 36.5?GHz. The MWR datasets were assigned by video imagery into open water leads and various ice type categories. The ground data provided further classification into dry, moist and wet snow sub‐categories. The datasets were used to study the behaviour of the brightness temperature and polarization ratio as a function of frequency and the degree of ice deformation; additionally, the dimensionality of multichannel datasets, classification of surface types, and suitability of the SSM/I and AMSR‐E data and NASA Team and Bootstrap ice concentration algorithms for the mapping of the Baltic Sea ice were examined. The results indicate that open water leads can be distinguished from sea ice regardless of the snow cover wetness, using even single‐channel MWR data. Classification of ice types is possible only under dry snow condition. Determination of the ice type concentrations from the coarse‐resolution space‐borne MWR data is not feasible, because the mean signatures for various ice types are very close to each other. The results also suggest that the SSM/I and AMSR‐E data and the NASA Team and Bootstrap algorithms can be used to map total ice concentration after modifications of open water and sea ice reference signatures.     

Assessment of WRF microphysics schemes in simulation of extreme precipitation events based on microwave radiative signatures

ABSTRACT

Passive microwave radiometric signatures are affected by microphysical properties and hydrometeor distributions. Various microphysical properties of hydrometeors assumed in numerical simulations of precipitating clouds cause the different emission and scattering signals. This study compares the radiometric signatures obtained from five microphysics (MP) schemes of the Weather Research and Forecasting (WRF) model during the simulation of eight typhoons with respect to Tropical Rainfall Measuring Mission Microwave Imager observations. The MP schemes include the Thompson (MP8), Morrison two moment (MP10), WRF Double Moment 6 Class (MP16), National Severe Storms Laboratory 2 moment (MP17), and Thompson aerosol-aware (MP28) schemes. The results show that most of the schemes produce insufficient emission/scattering signals from liquid/ice particles over the same rain rate compared to the observations. It was also confirmed that, depending on the schemes, the scattering signals appear to be more variable than the emission signals. In general, MP16 is more frequently identified as the scheme with the smallest biases in both low- and high-frequency channels for individual orbits. However, the results demonstrate that one scheme does not work best in all cases examined here. This suggests that the characteristics assumed in MP schemes should be carefully understood to simulate precipitating clouds. Moreover, comparisons of the radiometric signatures from simulations and observations might be used to understand the uncertainties caused by incorrect assumptions of the microphysical properties of precipitating clouds.     

SAR interferometry over Baltic Sea ice

SAR interferometry (InSAR) offers new interesting possibilities for research in sea ice radar scattering and sea ice mechanics. A case study of this is presented from the Baltic Sea in late March 1992. Interferometric coherence is mainly dependent of the temporal characteristics of the scattering sources in sea ice. Different areas with different scattering properties were examined and the present data indicates that more field data is necessary to fully understand the InSAR coherence over sea ice. However, some interesting features were noted. Over low-salinity ice, backscattering and coherence seems to be related, high backscatter areas are more unstable than low backscatter areas. Over areas with surface roughness scattering, the scattering is relatively stable and also that a snow cover seems to retain the coherence over such areas. Interferometric phase measurements are dependent on small deformations of the ice pack. Fast ice which is (nearly) stationary experiences small discontinuous slips and deformations. Interferometric phase measurements are very sensitive to these slips, displacements and deformations and will provide new insight into the rheology for fast ice and how the fast ice starts to move. How the fast ice starts to move is one of the major problems in sea ice mechanics research and there is not much earlier data on the subject. In the present case, the ice was nearly stationary as the stresses were below the yield limit under the low forcing conditions. Two ice floe compressions have been observed and the strains are believed to be viscous with a viscosity value at approximately 1013-1014kg (ms). Both the interferometric phase and the coherence measurements over ice are believed to be of great value in future backscattering models and sea ice mechanics models.     

On the classification of melt season first-year and multi-year sea ice in the Beaufort Sea using Radarsat-2 data

Interpreting satellite microwave sea ice data during the melt season is difficult. Warm temperatures allow for a greater presence of water in the liquid phase at the surface and within the ice, resulting in similar backscattering responses for first-year ice (FYI) and multi-year ice (MYI). Differentiating these ice types is important, especially during summer, in view of the higher presence of seasonal marine traffic, functioning of the ecosystem, and the Inuit use of the marine icescape in summer. In this article, we investigate the similarities between geophysical, thermodynamic, and dielectric characteristics of the late-season MYI and FYI, and discuss how this can lead to a false detection of MYI. The study uses Radarsat-2 data for ice detection during summer. This involves an analysis of co-polarization versus cross-polarization (HH vs. HV), various incident angles (20°, 35°, and 45°), and ice types (FYI vs. MYI). Statistical analyses of the measurements obtained in 2009 identify the difficulty in differentiating ice types during summer. The results show that the physical and electromagnetic properties of the ice surfaces are virtually identical with few differences in the scattering of microwave energy. We conclude with suggestions on how a more effective differentiation of MYI and FYI types in the summer season can be accomplished.