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Comparison of aircraft observations with ensemble forecast model results in terms of the microphysical characteristics of stratiform precipitation

机译:与集合预测模型的飞机观察的比较导致层状沉淀的微专用特征

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The prediction of the particle number concentration and liquid/ice water content of cloud is significant for many aspects of atmospheric science. However, given the uncertainties in the initial and boundary conditions and imperfections of microphysical schemes, the accurate prediction of these microphysical properties of cloud is still a big challenge. The ensemble approach may be a viable way to reduce forecast uncertainties. In this paper, a large-scale stratiform cloud precipitation process is studied by comparing results of a 10-member ensemble forecast model with aircraft observation data. By means of the ensemble average, the prediction of bulk parameters such as liquid water content and ice water content can be improved in comparison with the control member, but the particle number concentrations are still one to two orders of magnitude less than those from observations. Intercomparison of raindrop size spectra reveals a big distinction between observations and predictions for particles with a diameter less than 1000?μm.
机译:对于大气科学的许多方面,云颗粒浓度和液体/冰水含量的预测是显着的。然而,鉴于初始和边界条件的不确定性和微孔物理方案的缺陷,对这些云的这些微物理性质的准确预测仍然是一个很大的挑战。集合方法可能是减少预测不确定性的可行方式。在本文中,通过将具有飞机观察数据的10构件集合预测模型的结果进行了研究,研究了大规模的层状云沉淀过程。通过集合平均值,与控制构件相比,可以改善诸如液体含水量和冰含水含量的体积参数的预测,但粒子数浓度仍然比观察结果的少于1到两个数量级。雨滴尺寸光谱的相互熟悉揭示了直径小于1000Ωμm的颗粒的观察结果和预测之间的大小。

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