Clouds, Precipitation and Modelling

Clouds are an important element of the atmosphere.

  • They are  essential for precipitation,
  • They modify the transfer of radiation from and to space,
  • By moving, they transport water or ice from one place to another,
  • Phase changes (vapour – liquid – solid) in the cloud modify the temperature of the surrounding air,
  • They are used to describe weather and climate.
Clouds over the ice of Atka Bay, Antarctica (Photo: Thomas Hollands)

In the Polar Regions, most of the mass added to the ice sheets comes from precipitation.

Because there are only few observations of clouds in the Polar Regions, model simulations help us in gaining knowledge about the distribution and composition of clouds in the Arctic and in the Antarctic.

In our group, we work on research of single cloud processes in idealized models and on comparison of forecast model results with observations.

Treatment of clouds in a model

bin approach

bin cloud microphysics

The model keeps track of how many drops of a certain size there are and simulates their interactions.

Modelling of the evolution of clouds and precipitation is done by either the microphysical ('bin') approach or by the bulk approach. The bin approach catches many details therefore is computationally time consuming. The bulk approach is numerically, efficient but describes only the effect of the micorphysical processes on the macroscale state.

Hence, for many atmospheric models (for example weather predicition), only the bulk approach is viable.

Read more on the treatment of clouds in models.

bulk approach

bulk cloud microphysics

The model keeps track of the total number of drops or the total mass of drops, but does not know about individual drops.

Drop growth by coagulation

Drops collide due to their different motions. If the colliding drops merge, a new drop is formed. This process is called coagulation.

Velocity fluctuations in the turbulent medium air enhance the probability of drop collisions. The speed-up of formation of larger drops is investigated by modelling studies.

Read more on the influence of turbulence on drop growth.

Observations and Modelling

ceilometer (cloud laser) (Photo: Gert König-Langlo, AWI)

In the Polar Regions, manned research stations are widely scattered. In order to obtain region-wide information on the distribution of clouds, the observations have to be supplemented by atmospheric model simulations.

Left and right are a typical view for cloud observations at the meteorological observatory at the Neumayer Station. In the foreground are a ceilometer (cloud laser, left) and the roof of the station (right). The observations can be used for verification of local model results.

The figure shows the simulated condensate mass close to Neumayer station together with measurements of cloud base height (dots) in December 2011 for 3 data sets for topography.

The model is the Weather Research and Forecast model (WRF) in its polar-modified version.The basic features of ceilometer cloud base heights and the lower boundary of noteworthy condensate amount agree reasonably well in phases of clouds rich in condensate. The correlation is worse in case of thin clouds, when it is difficult to define a cloud base.

Publications

Parts of the research were supported by Priority Research Programm 1276 'MetStröm', funded by the Deutsche Forschungsgemeinschaft, grant WA-1334/8.

Riechelmann, T. , Wacker, U. , Beheng, K. D. , Etling, D. and Raasch, S. (2015) Influence of turbulence on the drop growth in warm clouds, Part II: sensitivity studies with a spectral bin microphysics and a Lagrangian cloud model <http://epic.awi.de/37722/>  ,Meteorologische Zeitschrift . doi:10.1127/metz/2015/0608 <http://dx.doi.org/10.1127/metz/2015/0608> 

Ziemer, C. and Wacker, U. (2014):  A Comparative Study of B-, Γ- and Log-Normal Distributions in a Three-Moment Parameterization for Drop Sedimentation, Atmosphere, 5 (3), pp. 484-517. doi: 10.3390/atmos5030484

Ziemer, C. , Jasor, G. , Wacker, U. , Beheng, K. D. and Polifke, W. (2014): Quantitative Comparison of Presumed-Number-Density and Quadrature Moment Methods for the Parameterisation of Drop Sedimentation, Meteorologische Zeitschrift, 23 (4), pp. 411-423. doi: 10.1127/0941-2948/2014/0564

Jasor, G. , Wacker, U. , Beheng, K. D. and Polifke, W. (2014): Modeling artifacts in the simulation of the sedimentation of raindrops with a Quadrature Method of Moments, Meteorologische Zeitschrift, 23 (4), pp. 369-385. doi: 10.1127/0941-2948/2014/0590

Siewert, C. , Bordás, R. , Wacker, U. , Beheng, K. D. , Kunnen, R. P. , Meinke, M. , Schröder, W. and Thévenin, D. (2014): Influence of turbulence on the drop growth in warm clouds, Part I: comparison of numerically and experimentally determined collision kernels, Meteorologische Zeitschrift, 23 (4), pp. 397-410. doi: 10.1127/0941-2948/2014/0566

Ziemer, C. and Wacker, U. (2012): Parameterisation of the Sedimentation of Raindrops with Finite Maximum Diameter, Monthly Weather Review., 140 (5), pp. 1589-1602. doi: 10.1175/MWR-D-11-00020.1