Large scale simulations of cloud droplet growth in turbulent environments
Clouds play a fundamental role in the dynamics of the
atmosphere and the water on the earth. Our knowledge of
cloud dynamics is still so poor that it represents the cause
of a relevant uncertainty in climate predictions and
atmospheric circulation models.
Our project investigates the dynamics of liquid water drops
in warm clouds interacting with the surrounding turbulent
flow. These processes are difficult to capture because of
the multi-scale nature of the turbulent flows at the high
Reynolds numbers typical of a cloud. Although the
characteristic length scale of the droplets (microns) is
smaller than the smallest active turbulence scale
(Kolmogorov scale: millimeters), it is known that the
droplet size distribution is strongly affected by turbulence.
In particular, turbulence is responsible of the broadening of
the droplet-size spectra that promotes collisions between
droplets of different sizes and consequently rain formation.
Nowadays it is impossible to capture the complete
dynamics of a cloud both in laboratory experiments and
direct numerical simulation (DNS). In addition, it is also
impossible to measure directly these properties in a real
cloud because of the limited resolution and control of the
experimental devices. The aim of the project is to quantify
the water droplet dynamics in a small portion of a real
cloud (order meters) by means of direct numerical
simulation where the complete and full droplet-turbulence
interactions will be analyzed in details.
Direct Numerical Simulations (DNS) is a powerful
numerical technique able to solve turbulent flows in all
details, from the largest to the smallest scales without any
approximation. DNS have now been employed for almost
30 years and data are usually in perfect agreement with
theoretical predictions and experiments. This technique is
an "ideal experiment" as it gives access to instantaneous
and statistical quantities not possible to measure even with
the most modern and accurate instrumental systems.
Nevertheless, the DNS does have limitations:
need of huge numbers of grid points and of big supercomputers, long
simulation times and large data storages, possibility to
simulate cases with moderate-small turbulence levels
(Reynolds number). Owing to these limitations, our
simulations will be combined with upscale models to be
able to extend and interpret the results at the physical scale
of a real cloud, (characterized by higher Reynolds number).
A novel multi-scale methodology has been specifically
designed to give an accurate prediction of the droplet-size
spectra broadering induced by turbulence.
The DNS simulations will be performed by means of a
pseudo-spectral Navier-Stokes solver coupled with an
equation for the supersaturation field and a Lagrangian
solver for the droplet dynamics. The code is fully
parallelized to be efficiently used on supercomputing
infrastructures. The simulations we shall perform will
produce state of the art data of turbulent-droplets and
multiphase flow dynamics. The computational grid will
involve 1 billion grid points for the Eulerian fields (3
velocity and the supersaturation) and 1 billion of discrete
droplet trajectories will be integrated.