Cloud-Wave Coupling (Minerva Fast Track RG)

Satellite images frequently show mesoscale arc-shaped cloud lines with a spacing of several tens of kilometers (Fig. 1, second from left). These shallow clouds form in the layer adjacent to the ocean surface (the mixed boundary layer). Unlike other mesoscale cloud line phenomena, such as horizontal convective rolls, these cloud lines do not align with the wind direction but form roughly at a 90° angle to the near-surface wind [2]. We showed that the formation of this pattern has a similar cause as the formation of ripples in water flowing over pavement (Fig. 2).
 

Convection Waves

Idealized simulations have shown decades ago that shallow clouds may generate gravity waves of small horizontal scales (of the order of 10 km). We investigate if under certain atmospheric background conditions, these waves can become trapped inside the troposphere and influence the development of clouds. For a 2.5-km simulation with a domain covering the Atlantic, we showed that the coupling between shallow clouds and trapped waves is sufficiently strong to be detected [3]. With knowledge of the large-scale atmospheric state, wave theory can reliably predict the regions and times where cloud-wave feedbacks become relevant to convective organization.

Our current research extends these model-based results to observations. When clouds are present, the imprint of the waves can easily be seen in visible satellite imagery (Fig. 3).

We have recently developed a new method that allows us to detect such waves automatically in satellite imagery without relying on the presence of clouds. With the large amount of data made available by this new method, we are trying to answer how much of an active role these short waves play in shaping the properties of convection.

The statistical properties of cloud fields are defined on scales of several tens to hundreds of kilometers and are thus linked to vertical motion on these scales. Although the magnitude of the mean vertical motion averaged over such length scales is tiny compared to that of horizontal motions, it is key for distributing water vapor and for determining the likelihood of clouds to form. Observing the vertical ascent or descent of air averaged over areas of a few hundred kilometers diameter (which we call the mesoscale) is a great challenge and such observations are scarce. We analyzed data from two field campaigns for which suitable observations existed [4, 5, 2]. The results imply that atmospheric gravity waves of all scales greater than the considered area play an important role in defining the magnitude of mesoscale vertical motions. This underlines the importance of studying convection in global simulations, rather than in domains of limited area.

Further information:

• Field study EUREC⁴A
• Why and how do clouds form in particular locations?

Not only may waves affect mesoscale convection, but convection may also affect mesoscale vertical motion. In recent years, an emerging class of atmospheric circulation models has been developed that enables global simulations where deep convection is resolved (Fig. 4). We investigate how sensitive the energy spectra of horizontal and vertical motions are to the simulated convection and how the properties of resolved convection affect the relationship between horizontal and vertical spectra.

Further information:

• DYAMOND

As part of the DataWave project, we collaborate with an international group of atmospheric and data scientists to design new approaches for better representing gravity waves in climate models. We combine very high-resolution position, temperature, pressure, and wind observations taken by super-pressure balloons with kilometer-scale model simulations to constrain gravity wave sources, propagation and breaking. To achieve computationally feasible representations of gravity waves, we use machine learning to compute the gravity wave momentum deposition (Fig. 5).