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
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
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
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
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
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
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?
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:
Responsible: Mark Wenig and Claudia Emde
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:
Responsible: Mark Wenig
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
Januar 2018