Abstract
Abstract. Detailed measurements of ice crystals in cirrus clouds were used to compare with results from the Community Atmospheric Model Version 5 (CAM5) global climate model. The observations are from two different field campaigns with contrasting conditions: Atmospheric Radiation Measurements Spring Cloud Intensive Operational Period in 2000 (ARM-IOP), which was characterized primarily by midlatitude frontal clouds and cirrus, and Tropical Composition, Cloud and Climate Coupling (TC4), which was dominated by anvil cirrus. Results show that the model typically overestimates the slope parameter of the exponential size distributions of cloud ice and snow, while the variation with temperature (height) is comparable. The model also overestimates the ice/snow number concentration (0th moment of the size distribution) and underestimates higher moments (2nd through 5th), but compares well with observations for the 1st moment. Overall the model shows better agreement with observations for TC4 than for ARM-IOP in regards to the moments. The mass-weighted terminal fall speed is lower in the model compared to observations for both ARM-IOP and TC4, which is partly due to the overestimation of the size distribution slope parameter. Sensitivity tests with modification of the threshold size for cloud ice to snow autoconversion (Dcs) do not show noticeable improvement in modeled moments, slope parameter and mass weighed fall speed compared to observations. Further, there is considerable sensitivity of the cloud radiative forcing to Dcs, consistent with previous studies, but no value of Dcs improves modeled cloud radiative forcing compared to measurements. Since the autoconversion of cloud ice to snow using the threshold size Dcs has little physical basis, future improvement to combine cloud ice and snow into a single category, eliminating the need for autoconversion, is suggested.
Highlights
The parameterization of cloud microphysics plays a critical role in general circulation model (GCM) simulations of climate (e.g. Stephens, 2005)
The measurements were collected mainly in cirrus clouds, but the formation mechanisms generally differed between the TC4 and Atmospheric Radiation Measurements (ARM)-Intensive Operational Period (IOP) cases (Heymsfield et al, 2013)
The cirrus in TC4 were mainly anvils associated with deep convection while the cirrus from the ARM-IOP were in situgenerated
Summary
The parameterization of cloud microphysics plays a critical role in general circulation model (GCM) simulations of climate (e.g. Stephens, 2005). The parameterization of cloud microphysics plays a critical role in general circulation model (GCM) simulations of climate Mitchell et al, 2008; Zhao et al, 2013), since its parameterization strongly impacts the microphysical and radiative properties of ice clouds. It strongly affects mixedphase cloud properties, with impacts on precipitation formation and conversion of liquid to ice. Because traditional GCMs are unable to resolve smallerscale features that drive cloud processes, and because of the need for computationally efficiency for climate simulations, the parameterization of microphysics in these models has historically been highly simplified. To represent cloud–aerosol interactions and impacts on droplet and ice crystal sizes and radiative properties, additional complexity has been added to GCM microphysics schemes to prognose both mass and number
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