Abstract. Ice and mixed phase clouds play a key role in our climate system, because of their strong controls on global precipitation and radiation budget. Their microphysical properties have been characterized commonly by polarimetric radar measurements. However, there remains a lack of robust estimates of microphysical properties of concurrent pristine ice and aggregates, because larger snow aggregates often dominate the radar signal and mask contributions of smaller pristine ice crystals. This paper presents a new method that separates the scattering signals of pristine ice embedded in snow aggregates in scanning polarimetric radar observations and retrieves their respective abundances and sizes for the first time. This method, dubbed ENCORE-ice, is built on an iterative stochastic ensemble retrieval framework. It provides number concentration, ice water content, and effective mean diameter of pristine ice and snow aggregates with uncertainty estimates. Evaluations against synthetic observations show that the overall retrieval biases in the combined total microphysical properties are within 5 %, and that the errors with respect to the truth are well within the retrieval uncertainty. The partitioning between pristine ice and snow aggregates also agrees well with the truth. Additional evaluations against in-situ cloud probe measurements from a recent campaign for a stratiform cloud system are promising. Our median retrievals have a bias of 98 % in total ice number concentration and 44 % in total ice water content. This performance is generally better than the retrieval from empirical relationships. The ability to separate signals of different ice species and to provide their quantitative microphysical properties will open many research opportunities, such as secondary ice production studies and model evaluations for ice microphysical processes.

中文翻译：

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使用极化雷达观测检索同时存在的原始冰雪的微物理特性

摘要。冰和混合相云在我们的气候系统中发挥着关键作用，因为它们对全球降水和辐射收支有着强大的控制。它们的微物理特性通常通过极化雷达测量来表征。然而，仍然缺乏对并发原始冰和聚集体的微物理特性的可靠估计，因为较大的雪聚集体通常主导雷达信号并掩盖较小原始冰晶的贡献。本文提出了一种新方法，该方法在扫描极化雷达观测中分离嵌入雪团块中的原始冰的散射信号，并首次反演它们各自的丰度和大小。这种被称为 ENCORE-ice 的方法建立在迭代随机集成检索框架上。它提供了数字集中，冰水含量，以及具有不确定性估计的原始冰雪聚集体的有效平均直径。对综合观察的评估表明，组合总微物理特性的总体检索偏差在 5% 以内，并且与真相相关的错误完全在检索不确定性范围内。原始冰雪聚集体之间的划分也很符合事实。对最近的层状云系统活动中的原位云探测测量进行的额外评估很有希望。我们的中值检索在总冰数浓度和总冰水含量方面有 98% 的偏差和 44%。这种性能通常优于从经验关系中检索。