Aim of IC-IRIM:
This project aims to improve the model representation of polar mixed-phase clouds by integrating theoretical knowledge acquired from laboratory experiments and small-scale models into a climate model. Clouds are a key component of our climate system due to their ability to modulate radiation balance by reflecting the incoming solar radiation and trapping the longwave radiation emitted from the Earth’s surface. The cloud net radiative effect in the polar regions is warming, thus clouds play a critical role in the melting of the surface ice. Despite their significant impact on climate, mixed-phase clouds are poorly represented in climate models.
Background:
The most common cloud type in the polar regions are mixed-phase clouds, which consist of both liquid and ice. An accurate description of these clouds in models requires solid knowledge about their occurrence and properties, including the amount and distribution of both liquid and ice water content. Both ice crystal formation and liquid drop formation require an aerosol particle to be present known as ice nucleating particles (INP) and cloud condensation nuclei (CCN), respectively. However, enhanced ice crystal number concentrations (ICNCs) are frequently observed in polar clouds, which are orders of magnitude higher than the observed INP concentrations. This is particularly surprising since the polar regions are relatively clean and aerosols there are sparse. Secondary Ice Processes (SIP) have been suggested as the cause behind these enhanced ICNCs; these are ice multiplication processes that produce new ice crystals in the presence of pre-existing ice, without requiring the action of an INP. However, their relative importance and even the exact mechanisms remain highly uncertain. Currently, there is no coherent SIP representation in climate models.
Methods:
The project is organized in three main work packages (WPs). During WP1 existing laboratory measurements and small-scale models, that accurate resolve atmospheric thermodynamics and include detailed ice microphysics, will be used to quantify the impact of cloud dynamics, INP and CCN on SIP. During WP2 a mathematical framework that encompasses the results of WP1 will be developed. During WP3 this parameterization will be implemented in a climate model and evaluated against in-situ polar observations. Finally 50-year climate simulations will be performed to quantify the impact of SIP on the future climate state.
Significance:
In the 5th phase of the Climate Model Intercomparison Project, clouds were by far the largest source of intermodel spread in equilibrium climate sensitivity, revealing that an improved representation of cloud processes consists a prerequisite for more accurate climate projections. Accurately simulating clouds and their radiative effects has been a long-standing challenge for climate modeling, largely because clouds depend on small-scale physical processes that cannot be explicitly represented by coarse climate model grids. The treatment of ice particle formation remains among the sub-grid scale processes that are most poorly understood and hence poorly represented. With this project, by implementing an accurate description of cloud ice processes in a climate model, we aim to reduce the magnitude of uncertainty related to clouds, their radiative feedbacks and precipitation.
Project outcomes:
The developed model codes will be shared through: https://github.com/geosot86/IC-IRIM. Data management will be handled within the Bolin Centre database framework.
Principal Investigator: Dr. Georgia Sotiropoulou (MISU)
Participants: Prof. Annica Ekman (MISU), Prof. Athanasios Nenes (LAPI-EPFL)
Project No.: 201801760, funded by FORMAS research council
