Characterizing the Variation and Covariation of Cloud Microphysical Properties and Implications for Simulation of Subgrid-Scale Warm-Rain Processes in Earth System


Principal Investigator

Zhibo Zhang — University of Maryland - Baltimore County


Low-level liquid-phase clouds located in the marine boundary layer constitute an important component in the global climate system. The water budget, radiative effects, and lifetime of these clouds are all influenced by the precipitations (so-called warm rain) in these clouds. Unfortunately, because of the relatively coarse effective grid resolution of the current generation of climate models, the variety of cloud microphysical processes occurring inside a climate model grid cell are often oversimplified or unconstrained by observations. We propose a combined observational and modeling study to explore the impacts of subgrid-scale variability on the representation of warm, low-cloud processes relevant for climate models. The proposed work emphasizes developing innovative, process-level scientific insights to better understand the factors controlling the formation of precipitation formation in warm boundary-layer clouds. The research also directly aligns with the objectives of Atmospheric System Research of seeking methods to improve cloud parameterizations in climate models.

In climate models, the initialization of warm rain is usually parameterized as nonlinear functions of grid-mean cloud properties. Because of the nonlinear nature of these functions, neglecting variability within the climate model grid volume can lead to substantial biases in precipitation production, cloud cover, and surface radiative fluxes. In state-of-the art climate models, the influence of subgrid-scale variability is represented as an enhancement factor coefficient to the autoconversion and accretion rates calculated from the model variables. However, enhancement factor is typically taken to be a constant or even used as a knob to tune model cloud properties to match observations, an ad hoc approach that may yield a desired cloud outcome yet introduce compensating errors. In this proposal we argue for a systematic evaluation of this factor. The overarching goal of the proposed research is to characterize and understand subgrid-scale variations and co-variations of cloud microphysical properties and use the results to evaluate and improve the representation of subgrid warm-rain processes in climate models. Our proposal has two coordinated research thrusts in order to accomplish this goal:

  1. Characterizing the subgrid-scale variations and co-variations of cloud and precipitation microphysical properties, and exploring their dependence on environmental factors, horizontal scale and in-cloud height.
  2. Evaluating the uncertainty associated with the treatments of microphysical enhancement factors for warm-rain processes in the context of current-generation climate models and developing pathways to improve how climate models represent the influence of subgrid-scale variability on microphysical processes.

To accomplish these research efforts, we propose a combined observational and modeling study based on in-situ observations collected during the recent Aerosol and Cloud Experiments in the Eastern North Atlantic field campaign, routine surface-based observations on Graciosa Island, and a start-of-the-art large-eddy simulation model. Expected outcomes of the research are 1. a thorough and physically-based determination of the variability of cloud properties and the processes that govern that variability; 2. an evaluation of the uncertainties in the current warm-rain processes in climate models; and 3. vital improvements to the representation of low-cloud variability that can be directly implemented in the newly developed Energy Exascale Earth System Model.