Fresh clouds: A parameterized updraft method for calculating cloud densities in one-dimensional models
Fresh clouds: A parameterized updraft method for calculating cloud densities in one-dimensional models
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新鲜云：计算一维模型中云密度的参数化上升气流方法
DOI：
10.1016/j.icarus.2014.09.042
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发表时间：
2015
期刊：
影响因子：
3.2
通讯作者：
K. Mihalka
中科院分区：
文献类型：
--
作者：
M. Wong;S. Atreya;W. Kuhn;P. Romani;K. Mihalka
行星大气热力学平衡下的云凝结模型之所以有用，有几个原因。这些平衡云凝结模型 (ECCM) 计算湿绝热递减率，确定凝结物质的饱和限制混合比，计算潜热释放和分子量分层的稳定效果，并定位云底水平。许多 ECCM 的传承可追溯到 Lewis (Lewis, J.S. [1969]. Icarus 10, 365–378) 以及 Weidenschilling 和 Lewis (Weidenschilling, S.J., Lewis, J.S. [1973]. Icarus 20, 465–476)。这些模型中大气结构和气体混合比的计算是正确的。我们通过首先计算云密度率来解决影响这些模型中云密度计算的误差：云密度随上升气流长度尺度的变化。上升气流长度尺度参数化了形成云的上升气流的强度，并将来自 ECCM 的云密度率转换为云密度。通过与陆地云数据的比较，该方法得到了验证。我们的参数化上升气流方法给出了“新鲜”云中云密度的一阶预测，其中凝结是主要的微物理过程。更古老的演化云可以通过另一种一维方法更好地近似，即扩散-降水 Ackerman 和 Marley（Ackerman, A.S., Marley, M.S. [2001]. Astrophys. J. 556, 872–884）模型，该模型代表了湍流扩散产生的降水和水蒸气凝结之间的稳态平衡。我们重新评估伽利略观测到的云密度探测器入口点（Ragent, B. et al. [1998]. J. Geophys. Res. 103, 22891–22910），并表明在~0.5和~3棒处观测到的上部和下部云分别与饱和氨和水蒸气条件下的弱（卷云状）上升气流一致。观测到的最密集的云，接近 1.3 巴，需要出乎意料的强大上升气流条件，或更高的云密度率。该层中的云密度率可以通过具有非NH 4 SH组分（可能包括吸附的NH 3 ）的组合物来增强。
Models of cloud condensation under thermodynamic equilibrium in planetary atmospheres are useful for several reasons. These equilibrium cloud condensation models (ECCMs) calculate the wet adiabatic lapse rate, determine saturation-limited mixing ratios of condensing species, calculate the stabilizing effect of latent heat release and molecular weight stratification, and locate cloud base levels. Many ECCMs trace their heritage to Lewis (Lewis, J.S. [1969]. Icarus 10, 365–378) and Weidenschilling and Lewis (Weidenschilling, S.J., Lewis, J.S. [1973]. Icarus 20, 465–476). Calculation of atmospheric structure and gas mixing ratios are correct in these models.We resolve errors affecting the cloud density calculation in these models by first calculating a cloud density rate: the change in cloud density with updraft length scale. The updraft length scale parameterizes the strength of the cloud-forming updraft, and converts the cloud density rate from the ECCM into cloud density. The method is validated by comparison with terrestrial cloud data.Our parameterized updraft method gives a first-order prediction of cloud densities in a “fresh” cloud, where condensation is the dominant microphysical process. Older evolved clouds may be better approximated by another 1-D method, the diffusive–precipitative Ackerman and Marley (Ackerman, A.S., Marley, M.S. [2001]. Astrophys. J. 556, 872–884) model, which represents a steady-state equilibrium between precipitation and condensation of vapor delivered by turbulent diffusion.We re-evaluate observed cloud densities in the Galileo Probe entry site (Ragent, B. et al. [1998]. J. Geophys. Res. 103, 22891–22910), and show that the upper and lower observed clouds at ∼0.5 and ∼3 bars are consistent with weak (cirrus-like) updrafts under conditions of saturated ammonia and water vapor, respectively. The densest observed cloud, near 1.3 bar, requires unexpectedly strong updraft conditions, or higher cloud density rates. The cloud density rate in this layer may be augmented by a composition with non-NH4SH components (possibly including adsorbed NH3).