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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.

 Cumulus clouds as simulated by ICON-LEM over Barbados

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.

Detecting plumes and downdrafts in 3D simulations

 2D slices of liquid water and vertical velocity through a 3D convective plume Convection (i.e. buoyancy driven vertical movements) occurs on scales commonly too small for global models to capture. The vertical transport of heat, moisture, and momentum via convection plays a critical role in the boundary layer, yet is difficult to determine how much of the boundary layer transport is caused by unstructured turbulence versus organized and structured convection. As a thesis a student would modify already existing code to detect such structures, evaluate the importance and sensitivity of various assumptions, and visualize their work in 3D. To discuss this topic feel free to contact Philipp Griewank.

Stochastic and scale-aware parameterization of atmospheric convection based on LES and satellite data

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 situation is often referred to as the “grey zone problem” of cumulus parameterization. Solving this problem requires a total scientific rethink of the design of convective parameterizations for next-generation weather- and climate models. A potential way forward is the development of Eddy Diffusivity Mass Flux (EDMF) parameterizations that are formulated in terms of cloud size densities. An advantage of these schemes is that they are inherently scale-aware, while stochastic behavior reflecting cloud population dynamics can easily be introduced through population statistics. In this project the student will work with an EDMF scheme that is currently being developed by the InScAPE group. We implemented it as a subgrid scheme in one of our Large-Eddy Simulation (DALES) codes. The work can involve the following activities:

  1. Derive simple stochastic relations for cloud number from high-resolution MODIS satellite images of cumulus cloud populations in the subtropical Atlantic (see image below).
  2. Develop and test a new population model based on predator-prey relations (Lotka-Volterra).
  3. Conduct microgrid LES experiments for selected convective cases to test the scheme.

To further discuss this topic please contact Roel Neggers. More information is also provided on the EDMF pages on the InScAPE website.

MODIS image of cloud populations in the Caribbean on 21 January 2019

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: 2019/04/03 17:53 by griewank