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Connecting the level of cloud organization to the hydrologic and aerosol cycles in the Amazon (CLOUDORG)


The physical aspects of clouds, such as their horizontal and vertical extents, largely determine their role in the water and energy cycles in the Amazon. In this region, the locally driven diurnal convection cycle has a pulsating aspect, with the formation of the so-called shallow cumulus cloud field in the late morning, followed by a peak of activity in the afternoon due to deep convective cloud formation that then dissipates in the late afternoon. Historically, climate models fail to reproduce the growth of shallow convective clouds into deeper systems (i.e., the shallow-to-deep convective transition), triggering deep convection too early. This results in too early (2-3 hours) rainfall peaks within the daily cycle. Additionally, recent studies have shown that deep convective clouds play a major role in the new particle formation process in the Amazon. It has been proposed that clouds transport biogenic gases to the upper troposphere where they grow by condensation and are later transported to the boundary layer by downdrafts, replenishing the aerosol population that was removed by washout. In a context of a changing climate, it is essential that we achieve accurate reproduction of Amazonian cloud field evolution in order to better predict the future rainfall and aerosol regimes in the region. In this context, we propose an objective analysis to quantify the shallow-to-deep convective transition using high-resolution models and new observations at the ATTO (Amazon Tall Tower Observatory) tower region. The quantification will involve the determination of the level of cloud aggregation in the cloud fields, which dictates whether it is dominated by many small clouds (low level of aggregation) or by a few large clusters (high level of aggregation). The typical convective daily cycle in the Amazon is expected to evolve from the former towards the latter. Therefore, we propose a novel way to quantify the shallow-to-deep transition by tracking the evolution of the cloud aggregation levels. This information is intrinsically linked to the rainfall spatiotemporal variability and aerosol cycle because larger clusters produce more rainfall and transport more mass vertically than shallower and spread-out clouds. We propose that an index of cloud aggregation is an important factor to transition high-resolution model and observational results into parameterizations in climate models. (AU)

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