Summit Aerosol Cloud Experiment (SACE)

Lead Research Organisation: University of Leeds
Department Name: School of Earth and Environment

Abstract

Aerosols play a critical role in determining cloud formation and their resulting radiative properties by acting as cloud condensation nuclei (CCN), which provide seeding sites for available water vapor to condense onto, and ice nucleating particles (INP), which modulate the formation of ice in clouds. Yet, aerosol-cloud interactions, especially in regards to clouds that are comprised of both ice and supercooled liquid water (i.e., mixed-phase clouds), remain one of the greatest sources of uncertainty in weather and climate models despite the fact that decades of laboratory experiments, observations, modelling, and analysis have contributed to the state-of-the-art knowledge.

This project aims to reduce this uncertainty by exploring aerosol-cloud interactions in one of the remaining under-explored frontiers in atmospheric science. In this project, you will use advanced remote sensing technology (i.e. radar and lidar) in combination with a suite of other ground-based sensors based at Summit, Greenland (at the top of the Greenland Ice Sheet, hereafter GrIS) and state-of-the-art numerical weather and climate models to explore the role aerosol play in modulating the existence and properties of clouds over the GrIS. Using this new understanding, the impact of changes in aerosol over the GrIS in the past and future will be quantified.


The initial objectives of this project are as follows:

Objective 1. Using radar, lidar and other sensors located at Summit, Greenland, in conjunction with satellite observations, determine to what extent different aerosol properties cause significant changes in clouds over the GrIS.

Objective 2. Quantify the influence CCN and INP have on the surface energy balance of the GrIS through their alteration of cloud properties (i.e., quantify the role aerosols may have on the melting of the GrIS).

Objective 3. Evaluate regional and global numerical weather and climate model performance against the observations to identify the deficiencies in the model's physics that lead to biases in cloud occurrence, cloud thickness, and phase partitioning. Such inadequacies likely cause the observed longwave bias in cloud radiative effects over the GrIS in the summertime; develop, test and deliver new physical parameterizations to improve model fidelity. This synthesizing objective will be accomplished through an integrated analysis of the cloud and aerosol observations and process evaluations in Objectives 2 and 3 via modelling.

Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/S007458/1 31/08/2019 29/09/2027
2113846 Studentship NE/S007458/1 01/01/2019 30/11/2022 Heather Guy