AMPlifying the Simulation of Clouds and Precipitation

University Of California-Davis, Davis CA

Investigators

Abstract

Properly simulating clouds is critical for accurate prediction of clouds and rainfall in weather and climate models. There are two common ways in which small-scale cloud processes are represented in atmospheric models; these are known as bin microphysics schemes and bulk microphysics schemes. Bulk schemes are simple models that execute quickly while bin schemes are much more complex but run slowly – in fact, too slowly to be used in weather forecasting or climate prediction. This project will use a new model, called the Arbitrary Moment Predictor (AMP), which benefits from the accuracy and flexibility of bin schemes to improve bulk schemes. AMP acts as a lens. It allows a weather model to see a bin scheme as though it were a bulk scheme. By changing the view, it will become possible to understand how best to implement bulk schemes in models for the first time. The results have the potential to lead to a major shift in the design and development of future weather and climate models. AMP predicts size distribution moments of cloud droplets and rain drops like existing bulk schemes, but the process parameterizations are identical to those used by a bin scheme. It is flexible in that it can predict mass mixing ratio and one or two additional arbitrary distribution moments. There will be two major parts of the work. 1) Large eddy simulations of warm phase stratocumulus clouds with two bin schemes and with two versions of AMP corresponding to each bin scheme will be compared to assess fundamental limitations of bulk schemes. Such a direct comparison between bin and bulk schemes has not been possible before. 2) Additional simulations will be run using AMP with alternative combinations of predicted moments. Simulations will be rigorously assessed with available observations to explore the possibility that nonstandard moment combinations should be used to improve simulation of clouds and precipitation. Such a possibility has been suggested based on observational evidence but has not been tested in 3D simulations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.