A novel method for ground-based remote sensing of profiles of cloud microphysical properties

在这个项目中，我们开发和应用一种新的，基于地面的被动和主动遥感方法相结合的对流云微物理参数的垂直廓线反演。深层对流对气候起着至关重要的作用，因为它对太阳辐射收支以及全球水循环有很大的影响。深对流云系的云滴沿云廓线的沿着生长和气溶胶吸收的相互作用影响着云系的寿命和持续时间。由于空间遥感应用通常只能观测云顶，因此对云面的地面遥感可以成为调查云滴增长的重要工具。由于经典的，被动检索的云滴大小通常是基于一维辐射传输计算，他们失败时，面对复杂的云几何形状的高空间分辨率。在我们的项目中，我们调查的影响，一个不均匀的云的几何形状的云液滴轮廓的遥感，并考虑不同的三维性质的对流云广泛的三维辐射传输计算。作为该项目的重要组成部分，我们将被动光谱仪与主动云雷达结合成一个同步测量系统。基于被动光谱仪和主动云雷达的观测数据，我们发展了一种具有几何特征的云微物理反演。根据这一建议，我们提供了第一个资助期的中期报告，并为博士候选人申请额外一年的时间，以使他能够成功完成该项目并获得博士学位。在这额外的一年中，为光谱成像仪和云雷达开发的方法将被结合到云微物理学的几何感知检索中。然后将对这种检索进行测量测试，并使用HDCP 2现场活动期间收集的现场数据进行验证。

In this project we develop and apply a novel, ground-based combined passive and active remote sensing method to retrieve vertical profiles of microphysical parameters of convective clouds. Deep convection plays an essential role for climate since it has a large influence on the solar radiation budget as well as on the global water cycle. The lifetime and albedo of deep convective clouds are influenced by the interactions between the cloud droplet growth along the cloud profile and the aerosol uptake. As remote sensing applications from space usually can only observe cloud tops, the ground-based remote sensing of cloud sides can be an essential tool for the investigation of cloud droplet growth. Since classical, passive retrievals of the cloud droplet size are commonly based on 1D radiative transfer calculations they fail when faced with complex cloud geometries on a high spatial resolution. In our project we investigate the implications of a inhomogeneous cloud geometry for the remote sensing of cloud droplet profiles and consider the distinct threedimensional nature of convective clouds by extensive 3D radiative transfer calculations. As an essential part of this project we are combining a passive spectrometer with an active cloud radar into a synchronous measurement system. Based on data measured with the passive spectrometer and active cloud radar, we develop a geometry-aware retrieval of cloud microphysics. With this proposal we provide an interim report of the first funding period and apply for one additional year for the PhD candidate in order to enable him to successfully complete this project and to obtain his doctorate degree. In this additional year the methods developed for the spectral imager and the cloud radar will be combined into a geometry-aware retrieval of cloud microphysics. This retrieval will then be tested on measurements and validated with in-situ data gathered during the HDCP2 field campaign.