Using passive and active observations at microwave and sub-millimetre wavelengths to constrain ice particle models

Abstract

Satellite microwave remote sensing is an important tool for determining the distribution of atmospheric ice globally. The upcoming Ice Cloud Imager (ICI) will provide unprecedented measurements at sub-millimetre frequencies, employing channels up to 664 GHz. However, the utilization of such measurements requires detailed data on how individual ice particles scatter and absorb radiation, i.e. single scattering data. Several single scattering databases are currently available, with the one by Eriksson et al. (2018) specifically tailored to ICI. This study attempts to validate and constrain the large set of particle models available in this database to a smaller and more manageable set. A combined active and passive model framework is developed and employed, which converts CloudSat observations to simulated brightness temperatures (TBs) measured by the Global Precipitation Measurement (GPM) Microwave Imager (GMI) and ICI. Simulations covering about 1 month in the tropical Pacific Ocean are performed, assuming different microphysical settings realized as combinations of the particle model and particle size distribution (PSD). Firstly, it is found that when the CloudSat inversions and the passive forward model are considered separately, the assumed particle model and PSD have a considerable impact on both radar-retrieved ice water content (IWC) and simulated TBs. Conversely, when the combined active and passive framework is employed instead, the uncertainty due to the assumed particle model is significantly reduced. Furthermore, simulated TBs for almost all the tested microphysical combinations, from a statistical point of view, agree well with GMI measurements (166, 186.31, and 190.31 GHz), indicating the robustness of the simulations. However, it is difficult to identify a particle model that outperforms any other. One aggregate particle model, composed of columns, yields marginally better agreement with GMI compared to the other particles, mainly for the most severe cases of deep convection. Of the tested PSDs, the one by McFarquhar and Heymsfield (1997) is found to give the best overall agreement with GMI and also yields radar dBZ–IWC relationships closely matching measurements by Protat et al. (2016). Only one particle, modelled as an air–ice mixture spheroid, performs poorly overall. On the other hand, simulations at the higher ICI frequencies (328.65, 334.65, and 668.2 GHz) show significantly higher sensitivity to the assumed particle model. This study thus points to the potential use of combined ICI and 94 GHz radar measurements to constrain ice hydrometeor properties in radiative transfer (RT) using the method demonstrated in this paper.