Evaluating Biases in Aerosol-Cloud Interaction Metrics using ARM Data and Models

Abstract

Shallow liquid clouds are a poorly quantified component of the climate system and one of the greatest sources of uncertainty for climate prediction. The problem encompasses fundamental understanding of these clouds, how they are affected by the thermodynamic structure of the atmosphere, how they might change in a warmer world, how they are influenced by the atmospheric aerosol, and how all of these components are represented in climate models. The problem is exacerbated by the large range of spatiotemporal scales involved: aerosol-cloud interaction processes need to be understood and resolved at the scale of centimeters, while cloud fields and their organization are driven by larger scale circulations at scales of 100s to 1000s of kms. For example, aerosol-cloud interactions acting at small scales can lead to fundamental changes in the radiative state of a cloud system by changing the cloud albedo, cloud fraction, and spatial distribution of condensate, in some cases quite significantly, e.g., in the case of transitions from closed-to open-cell stratocumulus. It is imperative that we make progress on quantification of aerosol-cloud radiation interactions if we are to have more confidence in our projections of climate change.

A major challenge is identifying the relationship between meteorological conditions and important cloud radiative properties such as albedo. This necessitates understanding of the role of aerosol particles in modifying cloud fields through both changes in cloud micro- and macro-structure. We propose to address the topic by combining surface observations, satellite remote sensing, reanalysis, regional modeling, and large eddy simulation to understand the key parameters that control cloud albedo and cloud albedo susceptibility to aerosol perturbations. To this end, we will identify the meteorological conditions that generate clouds that are most susceptible to aerosol perturbations in shallow marine cloud systems. In other words, we will identify and quantify the frequency of occurrence of the meteorological and aerosol conditions in which we expect to see strong radiative effects in response to aerosol perturbations.