A multi-scale model evaluation data set of small cumulus

Description

Shallow cumulus convection has been increasingly recognized as important to radiative forcing and climate sensitivity. Clouds of small size present a challenge for representation in global-scale models, and process-level models have shown sensitivity in simulating these clouds to model resolution and domain size. Additionally, little is known about aerosol effects on this cloud type due to difficulties in sampling aerosol collocated with cloud and cloud 3D radiative effects. Comprehensive evaluation data sets for small cumulus are needed but lacking. Observations also present a challenge as cloud sizes are typically much smaller than the pixel size of commonly used satellite remote sensors and ground-based and in situ observations can be biased due to directional sampling issues. The scale of observation may bias results substantially. We present an approach for a model evaluation data set of shallow cumulus clouds using available observational platforms from SGP, including ground-based observations, in situ airborne observations, and satellite-based remote sensing at a wide range of scales. We will examine this wide range of measurement scales and approaches in the context of model evaluation with the intent to provide information needed for improving simulations of this important cloud type.