SOC

SOC

Southern Ocean Clouds

ABOUT SOC

Project Duration

Southern Ocean Clouds will run from 1/2/2020 – 31/1/2024.

Project Aims

Summary

The biases observed in climate models over the Southern Ocean in surface radiation and sea surface temperature are the largest anywhere in the world. They have a fundamental impact on the ability of these models to predict global climate. Evidence suggests that errors in the representation of the mixed phase clouds found over the high latitudes of the Southern Ocean are responsible for these biases. Southern Ocean Clouds (SOC) Is a major project that aims to investigate high latitude mixed phase clouds and their representation in climate models by:

i) Investigate the source and composition of the cloud forming nuclei responsible for these clouds

ii) Investigate the cloud microphysical processes –such as secondary ice production –that are important in these mixed phase clouds

iii) Use the new observations to identify and partition the various sources of aerosols found in this region

iv) In conjunction with our new field data, develop new microphysical parameterisations for use in climate models

v) Conduct a series of global-scale model experiments, using our new microphysical parameterisations, to assess the impact of Southern Ocean clouds on the global climate system and so reduce the climate sensitivity due to clouds.

Objectives

To address our overall aims, we have a number of specific objectives:

  1. Identify the composition and sources of cloud-forming nuclei that play a major role in the formation of clouds in the Southern Ocean.
  2. Identify the detailed processes involved in secondary ice production (SIP) in clouds over the Southern Ocean and the role that SIP [EB3] [EB4] plays in cloud formation.
  3. Use the detailed observations of aerosols made during this project to validate and improve models of aerosol production over the Southern Ocean.
  4. Improve the representation of clouds in climate models of the Southern Ocean by developing and evaluating parameterizations based on our observational findings.
  5. Evaluate the impact of these new parameterizations on model simulations of the climate system.

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