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通过CloudSat观测并由多尺度建模框架模拟的亚马逊深对流核心的微物理变率

Microphysical variability of Amazonian deep convective cores observed by CloudSat and simulated by a multi-scale modeling framework.

作者信息

Dodson J Brant, Taylor Patrick C, Branson Mark

机构信息

Science Systems and Applications, Inc., Hampton, VA, USA.

Climate Science Branch, NASA Langley Research Center, Hampton, VA, USA.

出版信息

Atmos Chem Phys. 2018 May;18(9):6493-6510. doi: 10.5194/acp-18-6493-2018. Epub 2018 May 8.

Abstract

Recently launched cloud observing satellites provide information about the vertical structure of deep convection and its microphysical characteristics. In this study, CloudSat reflectivity data is stratified by cloud type, and the contoured frequency by altitude diagrams reveal a double-arc structure in deep convective cores (DCCs) above 8 km. This suggests two distinct hydrometeor modes (snow versus hail/graupel) controlling variability in reflectivity profiles. The day-night contrast in the double arcs is about four times larger than the wet-dry season contrast. Using QuickBeam, the vertical reflectivity structure of DCCs is analyzed in two versions of the Superparameterized Community Atmospheric Model (SP-CAM) with single-moment (no graupel) and double-moment (with graupel) microphysics. Double-moment microphysics shows better agreement with observed reflectivity profiles; however, neither model variant captures the double-arc structure. Ultimately, the results show that simulating realistic DCC vertical structure and its variability requires accurate representation of ice microphysics, in particular the hail/graupel modes, though this alone is insufficient.

摘要

最近发射的云层观测卫星提供了有关深对流垂直结构及其微物理特征的信息。在本研究中,CloudSat反射率数据按云类型分层,等高线频率随高度图揭示了8公里以上深对流核心(DCC)中的双弧结构。这表明两种不同的水凝物模式(雪与冰雹/霰)控制着反射率剖面的变化。双弧中的昼夜对比度比干湿季对比度大约大四倍。使用QuickBeam,在具有单矩(无霰)和双矩(有霰)微物理的两个版本的超参数化社区大气模型(SP-CAM)中分析了DCC的垂直反射率结构。双矩微物理与观测到的反射率剖面显示出更好的一致性;然而,两种模型变体都没有捕捉到双弧结构。最终结果表明,模拟现实的DCC垂直结构及其变化需要准确表示冰微物理,特别是冰雹/霰模式,尽管仅靠这一点是不够的。

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