CloudBrake, funded by the ERC, strives to expose the coupling of clouds and the vertical structure of wind, thereby aiding
development of parameterizations for improved numerical weather prediction, climate modeling, and wind energy design.

To study the causality behind relationships between clouds and wind in tropical and midlatitude weather systems, CloudBrake combines high-resolution modeling with the analysis of measurements from ground and from aircraft. New lidar techniques aboard aircraft are exploited to collect high-resolution wind profiles and turbulence data, and to validate low-level winds measured by the wind lidar aboard ESA's Aeolus satellite, launched in 2018. By combining Aeolus data with space-borne remote sensing of clouds and rain, we can trace evidence of a coupling between winds and clouds on global scales. New insights obtained by CloudBrake will be used to constrain models of momentum transport by shallow convection, and the impact of momentum transport on circulations will be tested in a general circulation model. Read more about the research strategy and the scientific background below.

Project Output

The below is a list of output of the different work packages in CloudBrake, including scientific pulications and collected datasets:

1. Cloud-wind interaction in Large-Eddy Simulation:

  • Helfer, K.C., Nuijens, L., De Roode, S.R. and Siebesma, A.P. (2020): How wind shear affects trade-wind cumulus convection (2020). Journal of Advances in Modeling Earth Systems, 12, e2020MS002183. [link]
  • Saggiorato, B., Nuijens, L., Siebesma, A. P., de Roode, S., Sandu, I. and Papritz, L. ( 2020). The influence of convective momentum transport and vertical wind shear on the evolution of a cold air outbreak. Journal of Advances in Modeling Earth Systems, 12, [link]
  • Dixit, V.V., Nuijens, L., Helfer, K.C. (2021): Counter-gradient momentum transport through subtropical shallow convection in ICON-LEM simulations. Journal of Advances in Modeling Earth Systems , 13, e2020MS002352. [link]
  • Helfer, K.C. and Nuijens, L. (2021): The morphology of simulated trade-wind convection and cold pools under wind shear. Journal of Geophysical Research: Atmospheres, 126, e2021JD035148. [link]
  • 2. Field studies and new data:

  • Koning, A.M., Nuijens, L., Bosveld, F.C., Siebesma, A.P., van Dorp, P.J., Jonker, H.J.J. (2021): Surface-Layer wind shear and momentum transport from clear-sky to cloudy weather regimes over land. Journal of Geophysical Research: Atmospheres , 126, e2021JD035087. [link]
  • Koning, A.M., Nuijens, L., Mallaun, C. (2022): Momentum fluxes from airborne wind measurements in three cumulus cases over land. Atmos. Chem. Phys., 22, 7373–7388 [link]
  • Ship-borne wind lidar measurements on board the RV Merian and RV Meteor preceding and during EUREC4A [Meteor Cruise report]
  • Ship-borne wind lidar measurements on board the RV Sonne (pre-BOW-TIE) cruise
  • 3. The momentum budget of the trades:

  • Helfer, K.C., Nuijens, L., Dixit, V.V. (2021): The role of shallow convection in the momentum budget of the trades from large-eddy-simulation hindcasts. QJR Meteorol Soc. 2021; 147: 2490– 2505. [link]
  • Nuijens, L., Savazzi, A.C.M., de Boer, G., Brilouet, P-E., George, G., Lothon, M., Zhang, D. (2022): The frictional layer in the observed momentum budget of the trades. Quarterly Journal of the Royal Meteorological Society. [link]
  • 4. Representation of winds in global models:

  • Savazzi, A.C.M., Nuijens, L., Sandu, I., George, G., Bechtold, P. (2022): The representation of the trade winds in ECMWF forecasts and reanalyses during EUREC4A. Atmos. Chem. Phys., 22, 13049–
  • Sandu, I., Bechtold P., Nuijens, L., Beljaars, A. and Brown, A. (2020) What controls the systematic forecast biases in near-surface wind direction over the oceans? (ECMWF Technical Memo no 866 ) [link]
  • Background

    For many centuries clouds have informed us how and where the winds are blowing. Even today, satellite observations of clouds are assimilated in numerical weather prediction models to improve the prediction of wind patterns. But clouds may not just simply drift along with the mean wind: they can modulate winds themselves. One way to do so is by transporting air with a certain momentum (wind speed) away from the surface to higher levels in the atmosphere, and transporting air with a different momentum from higher levels to the surface. This vertical mixing of clouds can influence the vertical profile of wind, and CloudBrake postulates that this process is critical for larger-scale circulations (Fig. 1).

    The focus of CloudBrake is on shallow convective clouds. Momentum transport by shallow clouds is studied even less than that for deeper clouds, yet shallow clouds dominate the subtropical and tropical oceans (between 5º - 30º north and south of the Equator) in regions that are known for their strong near-surface easterly winds: the trades. The trade-winds are important because they define convergence patterns in the tropics, where the ascending branch of the Hadley circulation produces the majority of tropical rainfall (Fig. 1). Furthermore, the trade-winds modulate ocean currents and upwelling, sea surface temperatures and turbulent fluxes at the ocean surface. Because the trade-winds are not only strong, but also relatively steady, they have a large (unexploited) wind energy potential. Shallow clouds are also frequent in the mid-latitudes as part of storm systems (frontal systems and cold air outbreaks) or during fair-weather conditions (spring and summer days).

    The coupling of clouds to winds (circulations) has been highlighted by the World Climate Research Program as a Grand Challenge for developing a better understanding of the Earth System and its sensitivity to global warming. This coupling may occur through the interactions of clouds with temperature, moisture and radiative fluxes, but also more directly through momentum transport. The goal of CloudBrake is to better understand such dynamical motions that also define convection and clouds, and which have received relatively little attention since pioneering studies in the trades, in which clouds were always viewed in light of changes in the profile of horizontal wind (Fig.2).

    Figure 1: Clouds and momentum transport within the large-scale overturning circulation

    Illustration of the large-scale overturning Hadley circulation and its clouds along a typical trade-wind trajectory. The black arrows indicate the profile of wind with easterlies within the cloud layer, and westerlies above. The blue arrows illustrate convective momentum transport (CMT).

    Figure 2: An illustration of the simultaneous evolution of winds and clouds in the trades

    Joanne Malkus and her colleagues were among the first to study how cloud patterns within the trades evolved over longer periods of time. Most illustrations in Malkus' published work showed the simultaneous evolution of clouds and the horizontal wind.