Aerosol-cloud interactions have persistently remained the single greatest uncertainty in anthropogenic perturbations to the climate system. The associated radiative effects have traditionally been assessed by global general circulation models (GCMs), aiming to model the chain of microphysical processes from aerosols acting as cloud condensation via cloud microphysics to the global energy balance. However, this relies on a complete representation of a very complex process chain and has been shown to be subject to large and persistent uncertainties. Moreover, significant structural limitations remain, in particular related to the intrinsic sub-grid scale coupling of aerosols and clouds. The emergence of global km-scale models provides an opportunity to overcome some of these limitations and to explore previously unresolved aerosol phenomena explicitly, including aerosol-convection interactions. However, they remain insufficiently constrained by observations.

In this presentation, I will highlight the potential of global km-scale climate models to make progress on our understanding of cloud-aerosol interactions, with a particular focus on aerosol-convection interactions. Starting from regional km-scale simulations using ICON with idealised aerosol perturbations from the MACv2-SP plume model, we demonstrate the potential to extend this work to global kilometre-scale modelling. This work motivates our development of the reduced complexity aerosol model HAM-lite, suitable for long-term global km-scale modelling of aerosol-convection interactions using ICON. I will present novel approaches for the evaluation of km-scale models, including cloud tracking and machine learning. Their systematic application will provide the foundation for future observationally constrained assessments.

Prof. Philip Stier ist Professor für atmosphärische Physik im Department of Physics an der University of Oxford, UK. Weitere Details.

Svalbard is located within the major entry pathway of relatively warm, mid-latitude air masses into the polar region. The stable water isotope composition in atmospheric water vapour and precipitation is a sensitive indicator of the accumulated condensation history of air masses on their way into the Arctic. The progressive loss of heavy isotopes with precipitation results in the well-known latitude gradient of stable isotopes in precipitation. Here we evaluate how well a simulation with the isotope-enabled regional model COSMO-iso driven by ECHAM6 nudged to ERA5 reanalyses represents the increasing depletion with higher latitude measurement location. We thereby make use of a data set of time-resolved precipitation and vapour isotope measurements collected during the ISLAS campaigns from 2020 to 2022 using research aircraft and station measurements from Ny-Ålesund, Longyearbyen, Tromsø, Andøya, Bergen, and Finse, all located along the European entry pathway for mid-latitude air masses into the Arctic. Results show that the time variations are well represented at all three measurements sites. While the sub-Arctic and the mid-latitude sites show a small low-bias in the simulated isotope depletion for δ18O and δD in precipitation, the indicator for non-equilibrium fractionation d-excess shows a high bias of more than 10 permil. Comparison with measurements taken on Svalbard during the ISLAS campaigns show a substantial increase in scatter with no consistent bias for δ18O and δD, whereas the d-excess has a consistent low bias. Vapour measurements confirm the results the from precipitation comparison. An investigation of the thermodynamic environment within and below clouds from in-situ and remote sensing observations points to an important role of the saturation adjustment in the microphysics scheme that prevents highly ice super-saturated environments in clouds that are conducive to low values of the d-excess. The operational model AROME-Arctic allows for more wide-spread regions of ice super-saturation, but does currently not include water isotopes. We conclude that paired precipitation-vapour water isotope measurements are a valuable diagnostic for model evaluation for mixed-phase cloud microphysics in the Arctic.

Prof. Harald Sodemann ist Professor für Meteorologie (Numerical Modelling, Atmospheric Water Cycle) an der University of Bergen, Norway. Weitere Details.

"The skill of a numerical weather forecast is tightly linked to the observing network used to estimate the forecast's initial conditions. To optimize this observing network, forecast centers are continuously trying to estimate both the benefit of current observations as well as the potential benefit of adding new observations to the network. For ensemble forecast systems, both can be estimated computationally efficiently by assuming a linear relationship between ensemble deviations of the initial state and a forecast quantity of choice. An important aspect of these methods that has yet to receive much attention is that they need to be provided with estimates of signal propagation, i.e., how the impacts of observations spread through the atmosphere over time. In this talk, I will illustrate these methods, their potential, and the importance of signal propagation using a simplified 1D toymodel, and show results obtained from a 1000-member forecast ensemble."

Dr. Philipp Griewank arbeitet im Institut für Meteorologie und Geophysik, Universität Wien, und ist ehemaliger Wissenschaftler der Universität zu Köln, Institut für Geophysik und Meteorologie.

"We have often heard the quote “a picture is worth a thousand words”, the question then is: “which words  is it worth?”. In this talk, I will discuss research work in Data Visualization applied to the complex task of designing for spatio-temporal data in urban sciences. I will discuss its power of expression when faced with the challenge of diving through a sea of data when data are not only multidimensional but also multivariate in nature; as well as its limitations when faced with the challenges related to human interpretation. I will show the importance of research in human factors in visualization as a means and strength to create and develop new tools that enhance performances by leveraging human natural abilities."

Dr. Rita Borgo aus dem Department of Informatics, King's College London Strand, London, UK ist als Gastwissenschaftlerin unseres KPAs vom 20.August bis 20.September 2023 in Köln am Institut für Informatik in der Arbeitsgruppe Visualisierung und Visual Analytics tätig. 

Prof. Michael Felderer ist Direktor des DLR-Instituts für Softwaretechnik und W3-Professor für Softwaretechnik an der Universität zu Köln. Das DLR-Institut für Softwaretechnik bietet hochentwickelte Software- und Rechnerlösungen für anspruchsvolle technische und wissenschaftliche Anwendungen. Das Institut beschäftigt sich mit Software-Engineering und aktuellen Software-Technologien wie Quantencomputing, Digitale Zwillinge und KI. Der Direktor des Instituts, Michael Felderer, ist ein international anerkannter Forscher auf dem Gebiet der Softwaretechnik.