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The Retrieval of Ice-Cloud Properties from Cloud Radar and Lidar Synergy

机译:从云雷达和激光雷达协同作用中获取冰云特性

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摘要

Clouds are an important component of the earth's climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L'Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE'98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.
机译:云是地球气候系统的重要组成部分。需要对它们的微物理性质进行更好的描述,以改善辐射传递计算。在地球,云,气溶胶和辐射探测器(EarthCARE)任务的框架内,由皮埃尔·西蒙·拉普拉斯(法国)研究所开发的雷达-雷达(RALI)机载系统可以用作机载示威者。本文提出了一种结合云雷达(94–95 GHz)和激光雷达数据来推导云的辐射和微物理特性的原始方法。它结合了雷达的视在后向散射反射率和激光雷达的视在后向散射系数。该算法的原理依赖于消光系数与雷达特定衰减之间的关系,该关系是从机载微物理数据和Mie散射计算得出的。为了在可以从两种仪器获得信号的云区域中求解雷达和激光雷达方程,必须知道某个参考范围z0处的消光系数。因为算法对于从范围z0到发射极的求反是稳定的,所以在激光雷达观察到的更远的云边界处选择z0。然后,假设消光系数和反向散射系数之间的关系,得出了整个消光系数,表观反射率,云物理参数,有效半径和冰水含量曲线。该算法适用于向下看的仪器的盲测,其中原始轮廓是从现场测量得出的。它也应用于真实的激光雷达和雷达数据,该数据是在1998年的“云激光雷达和雷达实验”(CLARE'98)实地项目中获得的,当时原型机载RALI系统飞行指向最低点。协同算法的结果与现场测量结果相当吻合。

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