Johanna Mayer
Dr
Research Fellow
Biography
During my Master studies in Theoretical and Mathematical Physics at the TU and LMU Munich, I developed an interest in climate science. This led to a PhD at the German Aerospace Center (DLR) with a focus on atmospheric physics. I specialised in satellite remote sensing of clouds and their thermodynamic phase. As clouds are a fascinating topic and their understanding is highly relevant for the further development of climate models, I continue my research on clouds at the ESA Science Hub. The newly launched EarthCARE satellite, a joint venture between ESA and JAXA, offers unprecedented opportunities to study clouds and aerosols in detail. I am using EarthCARE data to study the interactions of aerosols with clouds and the consequences for the radiative effect of clouds.
Research
Interactions between aerosols and clouds have a potentially large effect on the Earth’s radiative budget. Despite sustained efforts by the atmospheric community to better understand aerosol-cloud interactions (ACIs), the uncertainty of their effects is still very large (Bellouin et al., 2020). In fact, the uncertainty in ACIs dominates the total uncertainty in future climate projections (Gordon, Glassmeier and McCoy, 2023). One difficulty is that changes in aerosol concentrations lead to a variety of different adjustments in cloud properties that are difficult to disentangle in observations (McCoy 2020).
The new EarthCARE satellite mission offers unprecedented opportunities to simultaneously measure aerosol properties, cloud properties and radiation, all on the same platform. This is a significant advance in the information available to constrain and disentangle the various ACI processes. I will use these measurements to study ACIs, in a first step through case studies of aerosol events, coupling aerosol and cloud profiles with the temporal coverage of the geostationary MTG satellite. In a second step, when larger amounts of EarthCARE data are available, I will apply the statistical methodology of causal inference to disentangle complex ACI processes. The aim is to quantify the different adjustments in cloud properties induced by aerosols and to assess their radiative impact. A better understanding of these ACI processes can help to improve the representation of clouds and aerosols in climate models and reduce the associated uncertainties in future climate projections.