Master thesis topics

External projects


Topics for master theses in the theory group

Bei Interesse an Masterarbeiten im Lehrstuhl für Theoretische Meteorologie bitte bei Prof. G. Craig, Prof. T. Birner, Priv.Doz. T. Janjic, Dr. C. Keil or Dr. J. Savre nachfragen. Nachfolgend eine Auswahl derzeit offener Themen:

Does the stochastic perturbation scheme PSP2 improve precipitation forecasts in summer 2021?

One of the key sources of uncertainty in state-of-the-art kilometric-scale NWP models comprises the model error. One approach to account for this uncertainty are stochastic schemes. The physically-based stochastic perturbation scheme, which has been developed at MIM in recent years, will be run in a parallel suite in the convection-permitting ICON-D2 ensemble at DWD for the summer 2021.

The aim of this project is to assess the performance of the PSP2 scheme in ICON-D2, both systematically over a season and in detail for high impact weather events.

For more detailed information please contact Christian Keil or George Craig.

Dynamics-transport coupling in the stratosphere

The stratospheric circulation is projected to change in response to a warming climate. A changing circulation can impact the transport of trace gases (ozone, water vapor and ozone destroying substances) in the middle and upper atmosphere. The project will focus on developing a better understanding of the dynamics-transport coupling in the stratosphere.

Changes in the large-scale stratospheric dynamics and transport of trace gases will be investigated using a combination of theory, observations and numerical modeling. Key topics of investigation will be the subseasonal to climatological impact of stratospheric dynamical processes on the global distribution of tracers in the stratosphere. A hierarchy of climate models will be used.

For more detailed information please contact Aman Gupta or Thomas Birner.

Large-scale impacts of convective clouds

Although convective clouds are much smaller than large-scale weather systems, they can be a major source of error in weather forecasts because errors grow rapidly. Studying this error growth requires large ensembles of forecasts to accurately represent the many ways that the weather situation can develop. The aim of this project is to develop a simple numerical model that can represent the error growth processes, but is inexpensive to run in large ensembles. Different model formulations will be designed, programmed in Python and evaluated using advanced verification measures.

For more detailed information please contact George Craig.

Stratosphere-troposphere and climate dynamics

Topics broadly in the area of stratosphere-troposphere and climate dynamics are available upon request. Recent research topics in our group include: variability and long-term trends in the width of the tropical belt, processes that govern the temperature structure of the tropical tropopause layer, the dynamics of sudden stratospheric warmings and their coupling to the troposphere, transport processes in the upper troposphere / lower stratosphere. Interested candidates are asked to look through research topics on our group's website, in particular our recent publications:

For more detailed information please contact Thomas Birner.

Assimilation of cloud information

The assimilation of cloud-related observations is challenging as traditional error metrics (e.g. RMS error) are not really suitable for the evaluation of intermittent fields as clouds or precipitation (double penalty problem). To overcome this deficiency, various feature-based scores have been developed for the verification of forecast precipitation fields, but these scores have not yet been applied in the context of data assimilation.

The goal of this thesis ist to test the use of feature-based metrics for the assimilation of cloud-affected satellite observations in the emsemble data assimilation system KENDA for the regional weather forecast model COSMO-DE. Different approaches shall be tested in an idealized setup of KENDA that is used by several people in the HErZ data assimilation group.

Contact: Leonhard Scheck

Applicability of lossy compression methods to meteorological applications

The storage space requirements for output of numerical weather and climate prediction is growing faster than the cost of storage space is decreasing. Model resolution is continuously increased to overcome issues with parameterized physical processes like convection. At the same time the ensemble size (e.g. the number of model runs performed to create one forecast) is also increased to improve the assessment of uncertainty within the forecast. Both in combination results in really big data sets that are not only difficult to process but also very expensive to store.

One way to reduce the amount of output is to rely more on online diagnostics and not to save large fractions of the output. While this approach appears promising in operational setups of weather services, it is only a partial solution in research. Visualization of arbitrary aspects of a model run would no longer be possible and experiments would have to be carried out again if changes are made to the online diagnostic.

Another way is to store model output with reduced precision. File formats currently in use support only lossless compression or if lossy compression is possible only spatial correlation between neighboring data points is used (e.g., JPEG compression). The temporal correlation is ignored. In contrast, video compression algorithms are essentially based on the temporal correlation between successive time steps. Without reducing the quality, this results in a compression ratio that is by one order of magnitude higher than that of individual images. Central ideas of video compression should be directly transferable to the compression of model output. Examples are differential coding (only differences between time steps are stored) and motion compensation (for unchanged but moved parts of an image only a displacement vector is stored). On the other hand, assumptions about the perception by the human eye are not applicable (e.g., changes in brightness and color are not equally important).

The following questions should be addressed in this thesis:
Which compression algorithms are best suited for meteorological model output? Candidates are video compression and general purpose algorithms. The plan is not to develop new algorithms, but to asses existing ones.
What are the characteristics of errors produced by the analyzed algorithms?
Which degree of compression is acceptable for a set of different meteorological applications?

Contact: Robert Redl

Understanding and modelling the initiation of convection by propagating cold pool fronts

WS 2023-2024

When convective clouds precipitate and rainfall evaporates before reaching the surface, the boundary layer may be sufficiently cooled to form a bubble of dense air spreading horizontally along the surface. The thermodynamic conditions at the centre of these so-called cold pools are generally not favorable to the further development of convective clouds, but the initiation of new clouds is facilitated along the propagating edges of these cold pools where warmer and moister air is lifted. Cold pools thus playing a considerable role in determining where convection occurs and how it organizes at the mesoscales, it is crucial to make sure that cold pools and, perhaps more importantly, their capacity to form new convective clouds are appropriately represented in Numerical Weather Prediction models.

The objective of this project is to use a series of very high-resolution (< 1 km) numerical simulations of an idealized convective day in the tropics to gain a better understanding of the processes and parameters controlling the initiation of convection along cold pool fronts. In this project, we will particularly focus on two aspects of the problem:
1) how is convective initiation affected by the model's horizontal resolution?
2) how do surface conditions impact convective initiation?
Answering these questions will contribute to the development of new methods/parameterizations aiming at improving the representation of convective initiation in operational weather models.

To successfully complete this project, you will be expected to carry out numerical simulations using the high-resolution model mentioned previously, and analyse the model outputs to relate convective initiation to various key atmospheric parameters. Identifying the true processes influencing convective initiation will require the use of advanced association metrics and statistical tests.

Contact: Julien Savre

The organization of tropical convection with and without parameterized shallow clouds

WS 2023-2024

Convective clouds over the tropical Oceans do not occur randomly in space but generally tend to self-organise thus forming mesoscale clusters of clouds. This process, known as convective self-aggregation, is driven by feedbacks between atmospheric moisture and the clouds themselves: convection tends to dry (by subsidence) the atmosphere in regions where the convective activity is weak or absent, while the atmosphere is moistened where convection takes place. The result is that the moist convective region becomes even more favorable to the development of convective clouds, whereas convection becomes effectively suppressed in the dry environment, thereby reinforcing the situation.

Self-aggregation is known to occur in models when the domain size is sufficiently large to accommodate mesoscale cloud clusters and their dry environment, and when the horizontal grid spacing is coarse enough (> 1 km). One way to explain the dependency of convective aggregation on horizontal resolution is through the misrepresentation of shallow clouds in coarse models: these clouds are indeed too small to be explicitly represented at kilometer-scale resolutions but they are ubiquitous over the tropical Oceans and have a significant influence on moisture transport and the overall cloud scale circulation inside and just above the boundary layer.

In this project, the exact role of shallow clouds on the development and maintenance of a self-aggregated state of convection will be explored. To that end, idealized numerical simulations of the tropical atmosphere in equilibrium will be performed under conditions favouring self-aggregation (large enough domain, coarse enough resolution). A simple parameterization representing the impact of shallow convection on the atmosphere will then be implemented and the simulations repeated to understand how the dynamics associated with these shallow clouds affects the emergence of convective self-aggregation.

Contact: Julien Savre

Further themes are possible, please talk to Prof. G. Craig, Prof. T. Birner, Priv.Doz T. Janjic, Dr. C. Keil or Dr. J. Savre.