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Student projects

Studying cloud and total water statistics in high resolution models simulations

As part as our work developing pdf cloud parametrizations we use large amounts of high resolution simulations to test assumptions and evaluate performance (PDF cloud scheme). This work offers Students the chance to work with state of the art data while being able to choose from a wide range of themes to fit their interests. For example the Student could adapt our previous analyses to work on new small domain simulations conducted over Spitsbergen, Juelich, or the Zugspitze. Or the Student could expand on our previous analyses by implementing already published parametrizations, applying machine learning approaches, or developing and testing their own ideas. For more information get in contact with Philipp Griewank or Vera Schemann.

3D cloud structure in high resolution data

The shape and arrangement of clouds have a large effect on how clouds interact with radiation and therefore effect climate sensitivity. Recently run super-large domain simulations offer a unique glimpse into 3D cloud structures which are impossible to measure. As a thesis a Student could evaluate various aspects of the cloud structure in recently conducted super-large simulations over the tropical Atlantic and Germany. Possible topics are the relation of cloud fraction to total cloud cover or how cloud structure changes when the horizontal resolution changes from 600 to 150 meters. To discuss this topic feel free to contact Philipp Griewank or Vera Schemann.

Stochastic parameterization of convection using LES

Atmospheric convection and associated cloud processes are not resolved by most numerical models used for weather forecasting and climate prediction. As a result, their impact on the larger-scale flow and climate has to be represented through parameterization. Recently the ever increasing power and efficiency of supercomputers have for the first time allowed resolutions in Earth simulations at which convection is partially resolved. This problem requires a scientific rethink of convective parameterization. A potential way forward is to introduce stochastic behavior. In this project the student will perform tests with a new convection scheme as operational in one of our Large-Eddy Simulation (LES) codes. Simple relations for representing stochastic behavior will be implemented, and simulations will be performed to investigate their impact on the representation of cumulus convection. To further discuss this topic please contact Roel Neggers. More information is also provided on the EDMF pages on the InScAPE website.

Time variability vs. spatial variability - Testing Taylor's hypothesis of frozen turbulence in LES

Measurements are often taken at one point and then interpreted as a spatial variability by taking the wind into account. But how good is this approach? Can we find a strong correlation between the temporal and spatial variability? And does it depend on the synoptic situation? Or the environment? In this project the hypothesis will be tested in the model world by comparing temporal and spatial variability at different sides (e.g. JOYCE and Barbados) and under varying conditions. We will only look at model output - for spatial and temporal variability. Can we confirm the hypothesis in this clean and consistent model world? To discuss the topic or get more information please contact Vera Schemann

Other possible projects

(A full description will follow shortly)

  • Confronting fine-scale models with ACLOUD field campaign data on Arctic clouds (Vera Schemann, Jan Chylík, Roel Neggers)
  • How does changing microphysics change cloud formation? (Jan Chylík)
  • Comparing various cloud sampling approaches (Jan Chylík)
  • Analyze resolution dependency of eddy representation (Jan Chylík)
students.txt · Last modified: 2017/09/21 14:09 by schemann