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Topics for master thesis projects in the experimental group on radiation and remote sensing

Cloud Modelling: Collisional Breakup in Lagrangian Cloud Models

To initiate precipitation in warm clouds, droplets need to grow large enough by diffusion, enabling them sediment and collide and coalesce with smaller droplets. Creating these so-called precipitation embryos is a well-known bottleneck in cloud microphysics. However, once a small number of very large drops are created by collision and coalescence, they might break up into several smaller ones. If these newly created droplets are large enough to collide and coalesce with other droplets, they may start a positive feedback that dissipates a cloud quickly by precipitation.

In this thesis, we want to implement a representation of collisional breakup in a Lagrangian microphysical model and evaluate its effects on the development of a cumulus cloud. This thesis can be split up into a numerical part, in which the implementation of collisional breakup will be developed and evaluated, as well as a part that will investigate the role of collisional breakup in clouds. Accordingly, this thesis is of interest to students interested in clouds, microphysics, and numerical modeling.

Responsible: Fabian Hoffmann

Cloud Modelling: Stratocumulus Liquid Water Steady States

Stratocumulus clouds play an essential role in the global radiation budget. Due to their high albedo, stratocumulus reflect large amounts of incident shortwave radiation back to space. This ability is predominantly determined by the stratocumulus liquid water path, the vertically integrated liquid water content.

While it is accepted that the stratocumulus liquid water path is a result of longwave radiative cooling and entrainment warming/drying, it is disputed whether this liquid water path is in a steady state, i.e., is constant in time. Based on a theoretical mixed-layer approach, we were able to determine analytical solutions for the steady-state liquid water path and the entrainment velocity in stratocumulus (Hoffmann et al. 2020). These analytical solutions have been compared successfully to a wide range of (idealized) large-eddy simulations.

In this thesis, we want to go a step further and compare the solutions to reanalysis data of the ECMWF or satellite measurements, covering a much wider range of realistic stratocumulus clouds, including their transition to cumulus convection. This thesis is of interest to students interested in clouds, climate, and dynamical systems theory.

Responsible: Fabian Hoffmann

Cloud Modelling: Entrainment in Stratocumulus

Stratocumulus clouds play an essential role in the global radiation budget. Due to their high albedo, stratocumulus reflect large amounts of incident shortwave radiation back to space. However, entrainment, i.e., the flux of warm and dry air from the free troposphere above, tends to dissipate this cloud type, with commensurate implications for the climate system.

The entrainment in stratocumulus is linked classically to the so-called cloud-top entrainment instability (CTEI). CTEI describes a positive feedback, which postulates ever-increasing entrainment rates in stratocumulus until the cloud is evaporated completely. However, this theory is primarily built upon thermodynamic arguments and neglects the impact of cloud microphysics, i.e., the number and size of droplets. Accordingly, in this thesis, we want to analyze the impact of cloud microphysics on CTEI, especially how CTEI changes with regard to the number concentration of cloud droplets.

This thesis requires highly detailed modeling of the involved processes and will begin with idealized parcel simulations and end with realistic large-eddy simulations. This thesis is of interest to students interested in clouds, dynamics, microphysics, and numerical modeling.

Responsible: Fabian Hoffmann

Radiative Transfer Modelling: Detection of biosignatures on exoplanets

The aim of this project is to investigate the detectability of biosignatures on exoplanets given the instrumentation currently available at VLT (Very Large Telescope) and in the near future at ELT (Extremely Large Telescope). Direct observations of Earth-like exoplanets in the solar neighbourhood will be most probably be gathered in the near future using e.g. the instruments HARPS and CRIRES.

Using the Monte Carlo radiative transfer model MYSTIC, which is developed at MIM, spectra in the near-infrared spectral region shall be simulated for planetary atmospheres with various different atmospheric compositions to answer the question, whether e.g. water vapor, oxygen, methane and ozone could be detected.

The project will be carried out in close collaboration with the European Southern Observatory (ESO) located in Garching.

Responsible: Claudia Emde

Air chemistry and aerosol modelling: Estimating and monitoring emissions of air pollutants using Lagragian modeling and inverse methods

Man-made air pollution is driven by emissions of trace gases and particles from traffic, industry, agriculture and households. But who is responsible for which fraction of the observed pollution? How accurate are current emission estimates for certain polluter categories? Can we monitor their emissions in quasi-realtime using observations and modelling? These are the science questions you would answer in your thesis.

Linking sources to observed air pollutant concentrations is a challenging task, and various methods exist to determine these contributions. One way would be to look at the amount of fuel sold, combine it with traffic counts and estimates of the emissions per kilometer driven to arrive at a map of traffic emissions, for example. This emission inventory is „bottom-up“, created through the combination of all known sources. However, there are a number of shortcomings with this approach - unknown sources, uncertain activity counts, incorrect emission estimates.

In this thesis you would pursue a different road and create a „top-down“ emission inventory. Instead of summing contributions from individual sources, you would use observations of pollution levels made by research aircraft during recent field campaigns and combine these with backtrajectory calculations to connect observations with source regions. Bayesian inversion, a statistical optimization procedure would then lead to an optimized emission inventory based on observations. Such an inventory is highly valuable for emissions monitoring and air pollution control, aids in estimating the quality of existing bottom-up inventories and will help in identifying the most active contributors to bad air quality.

As you can see from the topic description a fair amount of modelling / computer work is required, so I would expect you to have used a Linux computer before and are somewhat familiar with Python or a similar programming language.

Responsible Christoph Knote

Air chemistry and aerosol modelling: Development of a dust resuspension module in a chemistry-transport-model

Fine particulate matter („Feinstaub“) is a major air quality hazard, especially in urban settings like Munich. Numerical models have been developed to understand the sources and transformation of particles in the atmosphere, and to develop efficient mitigation strategies. These regional or global scale models are based on numerical weather prediction models (like WRF or COSMO) and were extended by a description of particulate matter and trace gases. Particulate matter, its size distribution and chemical composition, is a prognostic quantity in such models they hence describe its complete lifecycle from emission (think Diesel exhaust) to deposition on surfaces (the dirt on your window sill). Currently those models do not consider that the dust deposited might be resuspended (e.g. through traffic). In this work you would develop a module to consider the resuspension of dust depending on factors like wind speed, relative humidity, precipitation and location which could then be implemented in chemistry-transport-models like WRF-Chem. Depending on your interests you could evaluate your developments on the regional to continental scalem but also on the local scale to estimate the effect of this paramterization on curbside measurements of particulate matter concentrations.

Responsible: Christoph Knote

Air chemistry and aerosol modelling: Air quality impacts of wild fires

Wildfires are often responsible for episodes of severe air pollution and elevated levels of particulate matter ('Feinstaub') in diverse areas of the world - Southern Europe, North America, or Russia, to just name a few. What makes the burning of biomass burning so extraordinarily bad for air quality? Is the chemistry in biomass burning plumes responsible for high ozone episodes downwind? In the context of an upcoming field campaign you would use an existing Lagrangian trajectory modeling system to predict the dispersion of wild fire plumes in North America, and develop a method to estimate the emission source strength of these wild fires based on observations taken from research aircraft, ground observations and mobile sensors. Your work would require familiarity (or lack of fear to work) with Linux computers and reasonable programming skills, and interest in environmental modelling aspects.

Responsible: Christoph Knote

Radiation and weather modelling: Synthetic satellite images for improved aerosol forecasts

Some of today’s most important environmental concerns are related to the presence of aerosols in the atmosphere. Dust, sand, smoke and volcanic aerosols affect the safe operation of transport systems and the availability of power from solar generation and influence the formation of clouds and rainfall. Moreover, not only the increasing concentration of greenhouse gases but also changes in the aerosols affect climate change and the extent of the aerosol impact is still uncertain. Numerical weather prediction models have made significant progress in accurately predicting the transport of aerosols, changes in their composition, and their effects on the dynamics of the atmosphere. However, large uncertainties exist in the initial and boundary conditions. Often neither the initial aerosol distribution nor the strength of aerosol sources is well known. These problems can be addressed by assimilating more and better aerosol observations. Aerosol information with high spatial and temporal resolution and excellent coverage is contained in solar channel geostationary satellite images.

Only recently radiative transfer (RT) methods for the visible spectrum have been developed by our group that are sufficiently fast to use solar channels in operational data assimilation systems. So far, information about water and ice clouds has been be assimilated. An important challenge in extending these methods to include aerosols is that considerably more parameters are required to describe them, compared to clouds. To make a look-up table based RT method feasible for aerosols, the number of parameters has to be reduced. The aim of this master thesis is therefore to compute synthetic satellite images from model data including aerosols and to investigate the following questions:

These investigations will be an important step towards improved aerosol forecasts and a better understanding of the influence of aerosols on weather and climate.

Responsible Leonhard Scheck, Bernhard Mayer

Radiation and weather modelling: Hat Strahlung einen Einfluss auf konvektive Bewoelkung?

Die Antwort darauf ist eine klares „ja“: Konvention wird durch Absorption solarer Strahlung am Erdboden ausgeloest. Die Frage ist, welche Relevanz die einzelnen Prozesse (Absorption und Emission solarer und thermischer Strahlung am Boden und in der Atmosphaere) haben. Und diese Frage versuchen wir, in verschiedenen Projekten im Verbund mit externen Partnern zu beantworten, um mittelfristig die Vorhersage von Wetter und Klima zu verbessern. In dieser Arbeit sollen dazu Simulationen konvektiver Bewoelkung mit dem an der Uni installierten ICON-LES durchgefuehrt werden. ICON wird in Zukunft zur Basis der DWD Wettermodellierung. Dazu muessen die im Rahmen von zwei Doktorarbeiten (Klinger, Jakub) neu konzipierten Strahlungsroutinen auf das Dreiecksgitter des ICON-LES angepasst und getestet werden. Dies ist eine anspruchsvolle und sehr interessante Aufgabe, die unter anderem die Entwicklung eines statistischen Monte-Carlo-Modells auf einem Dreiecksgitter sowie einer einfachen deterministischen Loesung des thermischen Strahlungstransports umfasst. Die zugrunde liegenden Methoden sind bei uns etabliert, aber eben „nur“ auf einem Rechtecksgitter. Die Arbeit ist zentrales Thema des Lehrstuhls fuer Experimentelle Meteorologie und wuerde die Arbeitsgruppe massgeblich voranbringen.

Responsible Bernhard Mayer, Fabian Jakub

Radiation and climate modelling: Parameterization of sub-grid cloud-radiative effects in climate models

Clouds remain the largest source of uncertainty in climate models. This is mainly due to the fact that current climate model resolution of several tens of kilometers is too coarse to resolve clouds properly. Clouds are usually treated in terms of „cloud fraction“ only in climate models. A detailed, subgrid scale, description is not available. Radiation is usually calculated in simple 1D approximation. It was shown by our group that cloud shape has a distinct effect on solar and thermal radiation. E.g. absorption and emission of radiation at cloud edges can cause significant heating and cooling locally and thus changes in the development of shallow cloud fields (Klinger et al., 2017, Jakub and Mayer 2017). However, as climate models can not predict the size and distribution of clouds, these radiative effects cannot be calculated so far.

Shallow cloud field properties, such as the distribution of liquid water, cloud size, height and the distance between clouds have been found to show characteristic statistical behavior. Cumulus cloud size follows, for example, a power law. Based on these findings, Feingold et al., 2017 developed a heuristic model for shallow clouds (cumulus and stratocumulus). This fast, statistical model allows to simulated a variety of cloud fields.

Based on these cloud fields, we aim to find a statistical relationship of the heating and cooling rates of clouds which can then be included, along with the heuristic model of Feingold et al., 2017 in a climate model to solve the above explained sub-grid cloud disability of climate models.

The task for a master thesis would be: First, extend the heuristic model of Feingold et al. (2017) by another dimension (cloud distance). Second, perform a set of 1D and 3D radiative transfer calculations for the cloud fields of the heuristic model. Third, find a statistical relationship between cloud field properties (size, height, distance, liquid water content) and the heating/cooling rates as well as upwelling and downwelling fluxes.

Responsible Bernhard Mayer

Cloud remote sensing: Determine the Influence of Radiatively Induced Surface Inhomogeneities using High-Resolution Satellite Imagery

Current research efforts (Jakub and Mayer 2017) suggest that 3D effects of radiative heating may lead to convective organization resulting in the formation of cloud streets. The above mentioned study examines the cloud-radiative-surface feedback in an idealized enviroment without complex wind fields and surface heterogeneities.

A subsequent step is to investigate if this kind of organization can be found in the complex environment of earths' atmosphere. To this end, this master thesis aimes at a determination of a possible observable correlation between radiative heating and the organization of shallow and deep convection in the real world.

The thesis likely encompasses the tasks of

Responsible Fabian Jakub, Bernhard Mayer

Ground-based remote sensing: Cloud and aerosol properties from simple polarized observations

Aim of the thesis is to use an existing off-the-shelf camera system to determine the degree of polarization of sky and clouds and to study how much information about cloud cover, optical thickness, cloud phase, droplet size, width of the size distribution, etc. can be obtained from such observations. At MIM we have a digital camera equipped with a polarizer. This work is meant as a pre-study for the cloud spectrometer which could be equipped with polarization capabilities in the future. Raw data of the camera system has to be used to determine the degree of polarization. Advantage of this quantity - which is a ratio of several images - is that there is no need for absolute calibration of the camera pictures. Questions to be answered: How accurate is the derived degree of polarization? Can we detect the thermodynamic phase of clouds from polarization images of their flanks or bottoms? Can we derive aerosol optical thickness or aerosol type from the clear sky?

Claudia Emde, Tobias Zinner

Trace gases: Imaging DOAS

This project is about the interpretation of differential optical absorption spectroscopy (DOAS) measurements in an imaging setup in order to determine the horizontal and vertical distribution of NO2 concentrations in cities. DOAS uses differential absorption structures of different trace gases like ozone or NO2 to derive their concentrations from spectral measurements. The DOAS method can be applied in different setups, both in an active and a passive mode, depending on whether an artificial light source or the sun light which had been scattered and partly absorbed in the earth’s atmosphere is used. In this setup the telescope of the instrument can be pointed in different directions and can generate an image of so called slant column densities when scanning in two dimensions (called imaging DOAS). Slant column densities represent concentrations integrated along all possible light paths. Those light paths have to be simulated using a radiative transfer model in order to interpret the slant column densities derived for a given scene correctly. Since the measurement setup aims at measuring NO2 concentrations in cities, the 3D radiative transfer model has to be able to include the geometry of buildings and other objects within the field of view, so the model to be used, MYSTIC, has to be extended accordingly.

The project includes the following steps:

  1. Familiarization with the 3D radiative transfer model MYSTIC
  2. Extending the model to include vertical surfaces with a defined albedo
  3. Modeling the building forming the observed scene (e.g. the Hong Kong skyline) to include in the MYSTIC simulation
  4. Learn the basics of DOAS
  5. Retrieval of slant column densities of already existing DOAS measurements using standard DOAS software
  6. Combining the DOAS results with the model output to form a consistent image of concentrations.

Responsible: Mark Wenig and Claudia Emde

Estimation of visibility from image sequences

In this project image sequences have to be analyzed in order to derive visibility range information. Different landmarks at different distances from the camera, e.g. high-rise building or church spires, can be used to derive optical parameters that depend on the visibility. Those parameters could be the local variability or the difference of the intensity of the object compared to the view in the sky close to the object, and can be compared to aerosol optical depths that have been measured at the same time.

The project includes the following steps:

  1. Automatic adjustment of the images from the sequence in case the camera shifted
  2. Chose useful objects in the field of view
  3. Determine intensity differences between objects and the sky
  4. Derive local structure parameters, e.g. local variability
  5. Explore further optical parameters using digital image processing operators
  6. Analysis of the dependency of the derived parameters on aerosol optical depths measured independently
  7. Simulation of the optical parameters using a radiative transfer model and comparison with parameters derived from the image sequence
  8. Installation of more cameras and implementation of a real-time evaluation

Responsible: Mark Wenig

Cloud remote sensing: Simulation of cloudbow and glory for MSG/SEVIRI

Particular optical phenomena like the cloudbow and the glory can be exploited for the investigation of cloud properties that are usually not accessible using passive optical measurements. However, they probably require constant cloud optical properties over large areas or high spatial resolution measurements. The SEVIRI radiometer aboard the geostationary Meteosat Second Generation (MSG) satellite has a sampling distance of 3 km at the subsatellite point and has therefore a rather coarse spatial resolution.

Aim of this thesis is the realistic simulation of SEVIRI radiances for these special sun-satellite geometries in order to check whether cloud properties derived from SEVIRI are sensitive to these phenomena.

Responsible: Luca Bugliaro


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Januar 2018