Abstract. The ice phase in clouds is essential for precipitation formation over continents. The underlying processes for ice growth are still poorly understood, leading to large uncertainties in precipitation forecasts and climate simulations. One crucial aspect is the Wegener–Bergeron–Findeisen (WBF) process, which describes the growth of ice crystals at the expense of cloud droplets, leading to a partial or full glaciation of the cloud. In the CLOUDLAB project, we employ glaciogenic cloud seeding to initiate the ice phase in supercooled low-level clouds in Switzerland using uncrewed aerial vehicles with the goal of investigating the WBF process. An extensive setup of ground-based remote-sensing and balloon-borne in situ instrumentation allows us to observe the formation and subsequent growth of ice crystals in great detail. In this study, we compare the seeding signals observed in the field to those simulated using a numerical weather model in large-eddy mode (ICON-LEM). We first demonstrate the capability of the model to accurately simulate and reproduce the seeding experiments across different environmental conditions. Second, we investigate the WBF process in the model by comparing the simulated cloud droplet and ice crystal number concentration changes to in situ measurements. In the field experiments, simultaneous reductions in cloud droplet number concentrations with increased ice crystal number concentrations were observed, with periods showing a full depletion of cloud droplets. The model can reproduce the observed ice crystal number concentrations most of the time; however, it cannot reproduce the observed fast reductions in cloud droplet number concentrations. Our detailed analysis shows that the WBF process appears to be less efficient in the model than in the field. In the model, exaggerated ice crystal number concentrations are required to produce comparable changes in cloud droplet number concentrations, highlighting the inefficiency of the WBF process in the numerical weather model ICON.

中文翻译：

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利用 CLOUDLAB 项目的现场观测评估 ICON 中大涡模式下的韦格纳-伯杰龙-芬德森过程


摘要。云中的冰相对于大陆降水的形成至关重要。人们对冰生长的基本过程仍然知之甚少，导致降水预报和气候模拟存在很大的不确定性。一个关键方面是韦格纳-伯杰龙-芬德森（WBF）过程，该过程描述了以云滴为代价的冰晶生长，导致云的部分或全部冰川化。在 CLOUDLAB 项目中，我们利用无人驾驶飞行器在瑞士的过冷低层云中采用冰川造云来启动冰相，目的是研究 WBF 过程。大量的地面遥感和气球载现场仪器使我们能够非常详细地观察冰晶的形成和随后的生长。在这项研究中，我们将现场观察到的播种信号与使用大涡模式数值天气模型 (ICON-LEM) 模拟的信号进行了比较。我们首先展示了该模型在不同环境条件下准确模拟和重现播种实验的能力。其次，我们通过将模拟云滴和冰晶数浓度变化与原位测量进行比较来研究模型中的WBF过程。在现场实验中，观察到云滴数量浓度随着冰晶数量浓度的增加而同时减少，并且一段时间内显示云滴完全耗尽。该模型可以在大部分时间再现观测到的冰晶数浓度；然而，它无法重现观察到的云滴数量浓度的快速减少。 我们的详细分析表明，WBF 过程在模型中的效率似乎低于在现场的效率。在模型中，需要夸大的冰晶数浓度才能产生云滴数浓度的可比变化，这凸显了数值天气模型 ICON 中 WBF 过程的低效率。