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How nature's smallest clouds slow down large-scale circulations critical for climate

Periodic Reporting for period 4 - CloudBrake (How nature's smallest clouds slow down large-scale circulations critical for climate)

Reporting period: 2021-07-01 to 2022-06-30

The CloudBrake project set out to expose the coupling between winds and shallow convective clouds, which are frequently found in the midlatitudes and plentiful over subtropical oceans, which are known for the trade-winds. The trade-winds are important because they define the inflow branches of the Hadley circulation and influence air-sea coupling. To study relationships between clouds and wind, CloudBrake combined high-resolution simulations with the analysis of in-situ and remote sensing data collected at ground-based observatories. CloudBrake also carried out new wind measurements in areas where wind data is scarce using wind lidars on board aircraft and research vessels.

CloudBrake highlighed the importance of convective and mesoscale circulations in carrying momentum flux that can accelerate (not decelerate) winds near the surface and cloud tops. CloudBrake helped to elucidate how convective momentum transport contributes to a long-standing near-surface wind error in the ECMWF forecast model. CloudBrake also found that wind shear can play a role in setting the depth of convective clouds and the depth of the boundary layer, and that certain wind shear can help aggregate moisture and the growth of cumulus clouds into larger clusters. Finally, CloudBrake found suggestive evidence for the hypothesis that clouds may slow down the large-scale Hadley circulation by showing that convection helps veer the wind away from the region of lowest pressure, thereby reducing cross-isobaric friction-induced ageostrophic flow near the surface.
The first years of the project focused on the understanding of small-scale processes that are important for a coupling of clouds and winds as part of WP1, for which observational studies and high-resolution idealized simulations with the Dutch Atmospheric Large-Eddy Simulation (DALES) model were carried out, where the latter were successfully run on a local (super)computer purchased with the projects' budget, equivalent to ~1M core hours per year. In WP2, new datasets were collected through the CloudBrake flight campaign over Germany, featured in a TUD Story of Science ( and the deployment of wind lidars during the international EUREC4A field campaign over the North Atlantic ocean. The measurements collected aided WP1 and WP3 and were used to evaluate the leading European weather model the IFS through my collaboration with ECMWF as a fellow ( In WP3, EUREC4A observations and large-domain LES run in hindcast ('weather") mode were analyzed to evaluate the role of momentum transport processes on the mean large-scale wind and to reflect on its parameterization in models (See also the ECMWF science blog:
We aimed to collect even more wind measurements in a much more remote region, namely over the subtropical ocean east of Barbados, by deploying commercial wind lidar instrumentation on board a research vessel during the upcoming international EUREC4A field campaign in Jan-Feb 2020. These data offer a very new view on how winds over oceans are modified under the presence of clouds, and also allow us to evaluate whether our current satellite observing systems can measure the small-scale interactions that are important.

In the second phase of our project, we moved from smaller-scale towards larger scales. Using our insights into momentum transport from the high resolution simulations in idealized settings (LES) and high resolution simulations in realistic settings (hind-casts over the tropical Atlantic) we quantified the influence of convective momentum transport on winds and examined the treatments of momentum transport by cumulus parameterizations in global models, such as the ECMWF forecast model the IFS.
Turbulence measurements with DLR's Cessna aircraft within shallow cumulus cloud fields