Improving our understanding of cloud phase-partitioning using long-term cloud-resolving simulations of Svalbard

• Main Author: Kiszler, Theresa
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: 2024
• Subjects: ddc:550; Arctic; Svalbard; Ny-Ålesund; Climate change; Ny Ålesund
• Online Access: https://kups.ub.uni-koeln.de/72722/; https://kups.ub.uni-koeln.de/72722/1/Kiszler_Theresa_Dissertation_20231218.pdf

Clouds cover a large part of the Earth and are relevant for the hydrological cycle and the Earth’s radiative budget. Clouds are very frequent in the Arctic, where they warm the surface most of the year in contrast to the rest of the globe. Low-level clouds are especially common in the Arctic and frequently contain supercooled liquid and frozen water simultaneously. The cloud’s composition and radiative properties depend on the aerosols available for droplet or ice particle formation and the microphysical processes that drive the hydrometeor growth and interactions between the hydrometeors. Changes in the composition of clouds due to climate change can affect the cloud’s radiative properties. Such changes can impact the larger climate system and amplify or dampen the warming. However, it is not fully clear what effect the changes in cloud properties and occurrence will have in the future. These uncertainties in models are due to several challenges, and one of the main ones is the representation of subgrid-scale microphysical processes in clouds. These processes, as well as the availability of aerosols, must be parameterised. These microphysical parameterisations inherit the knowledge gaps which still exist related to microphysical processes. With inaccurate parameterisations, models cannot correctly capture the radiative properties of clouds, and climate models can hardly quantify the impact of clouds in a warmer climate. To address this issue, this thesis evaluates cloud-resolving simulations performed for a region of Svalbard, centred at Ny-Ålesund. Ny-Ålesund offers a variety of long-term measurements which are used as a reference. This location further provides a complex topography to challenge the model. As the chosen model was the ICON (ICOsahedral Nonhydrostatic) model, which was developed for Germany, the first goal is to evaluate the model’s overall performance. It is shown that the model can capture large-scale features such as the wind flow and temperature profiles well. Compared to the observations, ...