The Chance of Freezing – Parameterizing temperature dependent freezing including randomness of INP concentrations
Ice nucleating particle (INP) concentrations can spread over several orders of magnitude at any given temperature. However, this variability is rarely accounted for in heterogeneous ice nucleation parameterizations. We developed a scheme for immersion freezing where the INP concentration is drawn fr...
| Main Authors: | , , , , , |
|---|---|
| Format: | Text |
| Language: | English |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://doi.org/10.5194/acp-2022-696 https://acp.copernicus.org/preprints/acp-2022-696/ |
| Summary: | Ice nucleating particle (INP) concentrations can spread over several orders of magnitude at any given temperature. However, this variability is rarely accounted for in heterogeneous ice nucleation parameterizations. We developed a scheme for immersion freezing where the INP concentration is drawn from a relative frequency distribution of cumulative INP concentrations. At each temperature, this distribution describing the INP concentrations is expressed as a log-normal frequency distribution. The new parameterization scheme does not require aerosol information from the driving model to represent the heterogeneity of INP concentrations. The scheme's performance is tested in a large-eddy simulation of an Arctic stratocumulus. We find that it leads to reasonable ice masses in the cloud. The scheme is sensitive to the median of the frequency distribution and highly sensitive to the standard deviation of the distribution. Generally, larger probability to draw high INP concentrations leads to substantially more ice in the simulated cloud. |
|---|