Our approach – University of Copenhagen

Forward this page to a friend Resize Print Bookmark and Share

Atmospheric complexity > Research > Our approach

Our approach

Stating the problem

Rayleigh-Bénard convection is a classical problem in complex systems science: When a fluid is placed in between two horizontal plates and the lower one is heated relative to the upper, so-called convective rolls will eventually appear. These rolls constitute a form of symmetry breaking, by which some areas see locally rising, others locally sinking fluid parcels.

 

Basic schematic of Rayleigh-Bénard convection.

  

 

 

 

 

 

 

 

 

The dynamics of the atmosphere can be modeled as a fluid for many practical purposes. 

However, in contrast to classical convection, that of the atmosphere arises due to a fluid containing varying phases: The water vapor contained in the air can condense to produce cloud droplets, thereby releasing latent heat. Further, when rain falls to the ground by the action of gravity, latent heat is redistributed vertically. These are processes that can act to break the initially rising motion of moist air parcels, thereby - in a sense - destroying convective rolls. 

 

LES image

The dynamics of moisture (top view) for a region of 100 km x 100 km in the horizontal, as simulated by our group.

Tackling the challenge

State-of-the-art global climate models are still far from capable of resolving scales of convective clouds througout the extended periods needed for climate simulations (at least 100 years). Yet, for short periods and smaller areas, so-called large-eddy simulations (see left column) can resolve turbulent processes down to tens or hundreds of meters. We use such simulations, which also represent simplifications of the real atmosphere, but do allow us to extract processes responsible for the organization of the atmosphere through convection and intensification of precipitation extremes.

 

Radar image of convective-type precipitation as observed over Germany in summer.

  

 

 

 

 

 

 

 

 

 

 

 

 

While simulations are convenient in accessing processes, the most direct way to study convection is through meteorological observations of the atmosphere. The atmospheric state consists of a large array of variables, e.g. temperature, moisture, wind speed and pressure, just to name a few. Precipitation, however, is the quantity that most directly affects the living environment, e.g. humans. As it plays a crucial role in re-distributing energy and moisture within the climate system, and occurs as an intermittant process, it is particularly important to gather detailed, high-resolution observations on it. Some observations we currently use are those from ground-based stations, radar reflectivity and satellite observations.

Conceptual modeling

Simulations and observations can tell us a whole lot about convective transport of moisture and energy. However, there is always a risk of taking a realistic simulation as meaning that the system is "understood". The more complex the simulation output, and perhaps the more it is visually compatible with observations or intuition, the less we actually grasp the abstract processes behind the formation and organization of clouds in the atmosphere.

We use methods from physics of complex systems to describe the self-organization of convective clouds. Requiring simplified models we can re-enact, at least qualitatively, some of the emergent phenomena seen in observations or simulations. We leave out some of the complexity — leading to better understanding and sometimes inspiring new predictions for future climate change.

Cartoon image of two precipitating convective clouds. When precipitation evaporates near the ground, areas of dense air form, spreading laterally. Where they collide, new precipitation events can be set-off.

Cartoon image of two precipitating convective clouds. When precipitation evaporates near the ground, areas of dense air form, spreading laterally. Where they collide, new precipitation events can be set-off.

 

 

Beyond this, simplified models can be more universal, describing similarities of disparate fields, such as atmospheric science and biology or even social science, fields that are also explored at Niels Bohr Institute.