Understanding the Formation and Impacts of Pockets of High Ice Crystal Concentrations in Mixed-Phase Layer Clouds

University of Manchester

Department of Earth and Environmental Sciences

Project Description

This PhD project aims to understand how small-scale heterogeneity observed within clouds so called “pockets of high ice crystal number density” – affect mixed-phase layer clouds (see Lloyd et al, 2015).

Mixed-phase layer clouds are characterised as having a large horizontal, but small vertical extent in which super cooled liquid drops and ice particles co-exist (e.g. Barrett et al. 2017). In Earth’s atmosphere, this can occur at temperatures below 0 °C and higher than 35°C, where liquid droplets can exist in a super-cooled state.

The importance of mixed-phase clouds for weather and climate has become increasingly evident. We now know that the majority of precipitation reaching Earth’s surface originates from ice particles forming in mixed-phase clouds (Mülmenstädt et al, 2015). But the way that mixed-phase clouds are altered in a warmer climate remains one of the largest uncertainties in understanding climate sensitivity (Lohmann et al. 2018).

We urgently need to address the following questions:

  1. What is the role of slow, stochastic ice nucleation (Westbrook et al. 2013) throughout the lifetime of mixed-phase layer clouds?
  2. How do secondary ice production pathways (Field et al. 2016) act under different conditions within mixed-phase layer clouds?
  3. How uncertain are heterogeneous ice nucleating particles to the glaciation of mixed-phase clouds?;
  4. How important is small-scale heterogeneity in both cloud and ice crystal concentrations to the life cycle of mixed-phase clouds?

A starting hypothesis is that a new paradigm in the way models represent cloud particles is needed to understand the effects of small-scale heterogeneity within the clouds, which is called super-particles (Grabowski et al. 2019). This represents a marked shift from the more traditional approaches. During the project the super-particle technique will be explored in a cloud-resolving model. This will be compared to more traditional model descriptions that are currently used in operational weather forecasting models in addition to more research-grade model representations to understand what level of detail is necessary to reproduce observations.

The project structure will be to take both existing and emerging observational case studies of mixed-phase layer clouds, including Arctic clouds and mid-latitude Altocumulus clouds, and model their development with a cloud-resolving model exploring questions 1-4. The project also offers scope for the PhD candidate who may also be interested in supplementing their numerical modelling studies with laboratory measurements of stochastic ice nucleation (e.g. Emersic et al. 2015; Connolly et al. 2009) using the University of Manchester Ice Nucleation Cold Stage.

The nature of a research project means that exact outcomes are subject to change; however, we expect that there will be a number of exciting publications from this work. During the course of your PhD both you and your supervisors will map out a program where you can learn and develop a range of techniques, including hard skills, and transferrable skills that will serve you well in either in academia or in industry.

Funding Information

This is a self funded project.


Lloyd, G., T. W. Choularton, K. N. Bower, J. Crosier, H. Jones, J. R. Dorsey, M. W. Gallagher, P. Connolly, A. C. R. Kirchgaessner, and T. Lachlan-Cope. 2015. “Observations and Comparisons of Cloud Microphysical Properties in Spring and Summertime Arctic Stratocumulus Clouds during the ACCACIA Campaign.” Atmospheric Chemistry and Physics 15 (7): 3719-37. https://doi.org/10.5194/acp-15-3719-2015.
Barrett, Andrew I., Robin J. Hogan, and Richard M. Forbes. 2017. “Why Are Mixed-Phase Altocumulus Clouds Poorly Predicted by Large-Scale Models? Part 2. Vertical Resolution Sensitivity and Parameterization.” Journal of Geophysical Research: Atmospheres 122 (18): 9927-44. https://doi.org/10.1002/2016JD026322.
Mülmenstädt, Johannes, O. Sourdeval, J. Delanoë, and J. Quaas. 2015. “Frequency of Occurrence of Rain from Liquid-, Mixed-, and Ice-Phase Clouds Derived from A-Train Satellite Retrievals.” Geophysical Research Letters 42 (15): 6502-9. https://doi.org/10.1002/2015GL064604.
Lohmann, Ulrike, and David Neubauer. 2018. “The Importance of Mixed-Phase and Ice Clouds for Climate Sensitivity in the Global Aerosol-Climate Model ECHAM6-HAM2.” Atmospheric Chemistry and Physics 18 (12): 8807-28. https://doi.org/10.5194/acp-18-8807-2018.
Westbrook, C. D., and A. J. Illingworth. 2013. “The Formation of Ice in a Long-Lived Supercooled Layer Cloud.” Quarterly Journal of the Royal Meteorological Society 139 (677): 2209-21. https://doi.org/10.1002/qj.2096.
Field, P. R., R. P. Lawson, P. R. A. Brown, G Lloyd, C. Westbrook, D. Moisseev, A. Miltenberger, et al. 2016. “Chapter 7. Secondary Ice Production – Current State of the Science and Recommendations for the Future.” Meteorological Monographs, November, AMSMONOGRAPHS-D-16-0014.1. https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0014.1.
Grabowski, Wojciech W., Hugh Morrison, Shin-Ichiro Shima, Gustavo C. Abade, Piotr Dziekan, and Hanna Pawlowska. 2019. “Modeling of Cloud Microphysics: Can We Do Better?” Bulletin of the American Meteorological Society 100 (4): 655-72. https://doi.org/10.1175/BAMS-D-18-0005.1.
Emersic, C, P J. Connolly, S Boult, M Campana, and Z Li. 2015. “Investigating the Discrepancy between Wet-Suspension and Dry-Dispersion Derived Ice Nucleation Efficiency of Mineral Particles.” Atmospheric Chemistry and Physics Discussions 15 (1): 887-929. https://doi.org/10.5194/acpd-15-887-2015.
Connolly, P.~J., O Möhler, P.~R. Field, H Saathoff, R Burgess, T Choularton, and M Gallagher. 2009. “Studies of Heterogeneous Freezing by Three Different Desert Dust Samples.” Atmos. Chem. Phys. 9: 2805-24. https://doi.org/10.5194/acp-9-2805-2009.

To apply for this PhD, please use the following application link: https://www.manchester.ac.uk/study/postgraduate-research/admissions/