Bony Sandrine, Schulz Hauke, Vial Jessica, Stevens Bjorn
LMD/IPSL, CNRS, Sorbonne University Paris France.
Max Planck Institute for Meteorology Hamburg Germany.
Geophys Res Lett. 2020 Apr 16;47(7):e2019GL085988. doi: 10.1029/2019GL085988. Epub 2020 Mar 26.
Trade-wind clouds exhibit a large diversity of spatial organizations at the mesoscale. Over the tropical western Atlantic, a recent study has visually identified four prominent mesoscale patterns of shallow convection, referred to as flowers, fish, gravel, and sugar. We show that these four patterns can be identified objectively from satellite observations by analyzing the spatial distribution of infrared brightness temperatures. By applying this analysis to 19 years of data, we examine relationships between cloud patterns and large-scale environmental conditions. This investigation reveals that on daily and interannual timescales, the near-surface wind speed and the strength of the lower-tropospheric stability discriminate the occurrence of the different organization patterns. These results, combined with the tight relationship between cloud patterns, low-level cloud amount, and cloud-radiative effects, suggest that the mesoscale organization of shallow clouds might change under global warming. The role of shallow convective organization in determining low-cloud feedback should thus be investigated.
信风云在中尺度上呈现出多种多样的空间组织形式。在热带西大西洋上空，最近的一项研究通过视觉识别出了浅对流的四种显著中尺度模式，分别称为花型、鱼型、砾石型和砂糖型。我们表明，通过分析红外亮温的空间分布，可以从卫星观测中客观地识别出这四种模式。通过将这种分析应用于19年的数据，我们研究了云模式与大尺度环境条件之间的关系。这项调查揭示，在日尺度和年际尺度上，近地表风速和对流层低层稳定性的强度区分了不同组织模式的出现。这些结果，再加上云模式、低云量和云辐射效应之间的紧密关系，表明浅云的中尺度组织可能会在全球变暖的情况下发生变化。因此，应该研究浅对流组织在确定低云反馈中的作用。
