Tropical Cirrus in Global Storm-Resolving Models: 2. Cirrus Life Cycle and Top-of-Atmosphere Radiative Fluxes

Cirrus clouds of various thicknesses and radiative characteristics extend over much of the tropics, especially around deep convection. They are difficult to observe due to their high altitude and sometimes small optical depths. They are also difficult to simulate in conventional global climate models, which have coarse grid spacings and simplified parameterizations of deep convection and cirrus formation. We investigate the representation of tropical cirrus in global storm-resolving models (GSRMs), which have higher spatial resolution and explicit convection and could more accurately represent cirrus cloud processes. This study uses GSRMs from the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project. The aggregate life cycle of tropical cirrus is analyzed using joint albedo and outgoing longwave radiation (OLR) histograms to assess the fidelity of models in capturing the observed cirrus cloud populations over representative tropical ocean and land regions. The proportions of optically thick deep convection, anvils, and cirrus vary across models and are portrayed in the vertical distribution of cloud cover and top-of-atmosphere radiative fluxes. Model differences in cirrus populations, likely driven by subgrid processes such as ice microphysics, dominate over regional differences between convectively active tropical land and ocean locations. Plain Language Summary Cirrus (ice) clouds vary in thickness and so have a wide range of impacts on Earth's energy budget. Unlike other clouds, thin cirrus reduce the amount of energy escaping to space, slightly warming the Earth. It is important to understand the differences in tropical cirrus cloud life cycles between models because tropical cirrus are a major source of uncertainty in the prediction of future climates. Cirrus clouds cover a large area in space and can last up to several days, yet they are difficult to measure with satellites and ground-based instruments. We instead use computer models to simulate tropical cirrus, specifically global storm-resolving models (GSRMs) which are able provide a level of detail not possible through observations. Unfortunately, most models have large biases in cloud properties. These differences arise from the imperfect representation of ice in the models. Our goal is to understand the model differences in representation of ice clouds using statistical analysis of the life cycle of cirrus in each model.

Automated summary

This study investigates the representation of tropical cirrus in global storm-resolving models, which have higher resolution and explicit convection. Model differences in cirrus populations dominate over regional differences, likely driven by subgrid processes. Understanding these model differences is essential in predicting future climates accurately.