Investigating secondary ice production in a deep convective cloud with a 3D bin microphysics model: Part I - Sensitivity study of microphysical processes representations

IF 4.5 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES Atmospheric Research Pub Date : 2024-11-08 DOI:10.1016/j.atmosres.2024.107774
Pierre Grzegorczyk , Wolfram Wobrock , Antoine Canzi , Laurence Niquet , Frédéric Tridon , Céline Planche
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Abstract

Secondary ice production (SIP) is a crucial phenomenon for explaining the formation of ice crystal clouds, especially when addressing the discrepancies between observed ice crystal number concentrations and ice nucleating particles (INPs). In this study, we investigate parameterizations of three SIP processes (Hallett-Mossop, fragmentation of freezing drops, and fragmentation due to ice–ice collision) by simulating a deep convective cloud observed during the HAIC/HIWC campaign with the 3D bin microphysics scheme DESCAM (DEtailed SCAvening and Microphysics model). The simulated mean cloud properties, including particle size distributions and ice crystal number concentration are compared with in situ probe observations obtained during the campaign. Simulation excluding SIP shows a large underestimation of small ice crystals (< 1 mm diameter) for temperatures warmer than 30C. In our results, incorporating Hallett-Mossop and fragmentation due to ice–ice collision processes leads to ice crystal number concentrations close to observed values, thereby reducing discrepancies by two orders of magnitude. Our simulations also indicates that fragmentation of freezing drops affect minimally the properties of the cloud at its mature stage. Furthermore, we investigate the impact of fragments sizes resulting from SIP processes and show that the size of fragments generated from fragmentation due to ice–ice collision significantly influences the shape of ice particle size distribution. Employing various parameterizations of the ice crystal sticking efficiency reveals a notable impact on cloud properties. This study shows that SIP mechanisms are important and have to be considered for cold and mixed-phase clouds. However their parameterization lack reliability, highlighting the need for better quantifying these mechanisms. The companion paper, investigates the effects of SIP processes on the formation and the evolution of the deep convective system.
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利用 3D bin 微物理模型研究深对流云中的二次产冰:第一部分--微物理过程表征的敏感性研究
二次产冰(SIP)是解释冰晶云形成的一个关键现象,尤其是在解决观测到的冰晶数量浓度与冰核粒子(INPs)之间的差异时。在本研究中,我们利用三维 bin 微物理方案 DESCAM(DEtailed SCAvening and Microphysics model)模拟了 HAIC/HIWC 活动期间观测到的深对流云,研究了三个 SIP 过程(Hallett-Mossop、冰冻水滴碎裂和冰-冰碰撞导致的碎裂)的参数化。将模拟的平均云特性(包括粒径分布和冰晶数量浓度)与活动期间获得的现场探测观测结果进行了比较。在温度高于-30∘C 时,不包括 SIP 的模拟结果表明对小冰晶(直径为 1 毫米)的估计不足。在我们的研究结果中,将 Hallett-Mossop 和冰-冰碰撞过程导致的碎裂考虑在内,使冰晶数量浓度接近观测值,从而将差异减少了两个数量级。我们的模拟还表明,冰冻水滴的破碎对成熟阶段云的性质影响很小。此外,我们还研究了 SIP 过程产生的碎片大小的影响,结果表明冰-冰碰撞产生的碎片大小极大地影响了冰粒大小分布的形状。采用不同的冰晶粘滞效率参数会对云的特性产生显著影响。这项研究表明,SIP 机制非常重要,必须在冷云和混合相云中加以考虑。然而,它们的参数化缺乏可靠性,因此需要更好地量化这些机制。配套论文研究了 SIP 过程对深对流系统的形成和演变的影响。
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来源期刊
Atmospheric Research
Atmospheric Research 地学-气象与大气科学
CiteScore
9.40
自引率
10.90%
发文量
460
审稿时长
47 days
期刊介绍: The journal publishes scientific papers (research papers, review articles, letters and notes) dealing with the part of the atmosphere where meteorological events occur. Attention is given to all processes extending from the earth surface to the tropopause, but special emphasis continues to be devoted to the physics of clouds, mesoscale meteorology and air pollution, i.e. atmospheric aerosols; microphysical processes; cloud dynamics and thermodynamics; numerical simulation, climatology, climate change and weather modification.
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Editorial Board Improving long-term prediction of terrestrial water storage through integration with CMIP6 decadal prediction Relative Impact of Assimilation of Multi-Source Observations using 3D-Var on Simulation of Extreme Rainfall Events over Karnataka, India Recent impact of reduced arctic sea-ice on the winter North Atlantic jet stream and its quantitative contributions compared to pre-industrial level Investigating secondary ice production in a deep convective cloud with a 3D bin microphysics model: Part I - Sensitivity study of microphysical processes representations
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