科研之友
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摘要
Ice and mixed-phase cloud representation and simulation in global climate models are challenging with large uncertainties and biases. Sharing similar growth paths, no distinct separation exists in nature between cloud ice and snow. Different from conventional microphysics schemes separating cloud ice from snow, a single prognostic category is used to represent the whole spectrum of solid hydrometeors. Instead of using fixed physical properties for separate ice classes, e.g., the mass, area, and fall velocity, we consider the particle shape and riming impacts on ice properties. This approach simplifies several icerelated microphysical processes and eliminates the ambiguity and uncertainty associated with parameterizing cloud ice to snow conversion. The modifications were implemented in the Morrison-Gettelman (MG08) scheme and tested in Community Atmosphere Model. Evaluation using single column simulations indicated that the new approach increased the ice water content (IWC) in high clouds during dry period, which is improved compared to available retrievals. Global atmospheric simulations using the new approach give an overall comparable mean climate with notable improvement in terms of clouds and their radiative forcing. Both longwave and shortwave cloud forcing are closer to observations due to more realistic IWC, liquid water content, and cloud top height. Furthermore, the new approach yields slightly better representation of mixed-phase clouds when a smaller capacitance for nonspherical particles is used in the ice depositional growth parameterization. Overall, the physically based single-ice approach is a promising direction for future GCM microphysics development given its simplified representation of microphysical processes and flexible description of ice particle properties.
- 出版日期2017-9
- 单位清华大学
