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| Improved Representation of Cloud-Aerosol Interactions in the Community Earth System Model: A New Sectional Cloud Model that Interacts with Modal and Sectional Aerosol Models | |
| 项目编号 | 2114638 |
| Owen Toon | |
| 项目主持机构 | University of Colorado at Boulder |
| 开始日期 | 2021-07-15 |
| 结束日期 | 06/30/2024 |
| 英文摘要 | Clouds have a profound effect on the energy balance of the Earth, by reflecting sunlight to space and blocking outgoing infrared radiation. Earth's climate is thus sensitive to all the processes, collectively referred to as cloud microphysics, that govern the formation and growth of cloud particles and their removal through evaporation and precipitation. For example, as climate warms the abundance of ice particles in clouds decreases in favor of liquid droplets, which makes the clouds more reflective and thus has a counteracting effect on the warming (a negative feedback). Liquid clouds also tend to last longer as they are less effective in generating precipitation, which could further enhance the negative feedback of the shift from ice particles to droplets. The sensitivity of climate to cloud microphysics poses a challenge for climate research, particularly as climate models must represent the full global climate system while much of the microphysics takes place over distances less than a millimeter. Global models use parameterizations to represent the bulk effects of cloud microphysics but these parameterizations are necessarily crude given the need to perform long and computationally intensive simulations. One concern with microphysics parameterizations is that they use nonphysical parameters to adjust the behavior of the clouds, and these parameters have a direct effect on important climate system behaviors such as the sensitivity of global temperature to greenhouse gas increases. A case in point is autoconversion, a parametric representation of the processes through which cloud particles interact to form precipitation. Autoconversion summarily converts some portion of a cloud's frozen and liquid water into raindrops or snowflakes according to externally imposed threshold criteria. The choice of threshold values for autoconversion affects cloud lifetimes and thus affects the top-of-atmosphere energy balance, thus giving the nonphysical thresholds an outsized effect on the simulated climate. Work performed here develops an alternative cloud microphysics model in which autoconversion and other one-step approximations are replaced by a more detailed formulation in which cloud particles are represented in terms of a size distribution, meaning the model partitions droplets and ice particles into a set of size bins, also referred to as sections of the size distribution, and keeps track of the abundance of particles in each bin. Microphysics is then represented through interactions between bins, for instance if small droplets grow bigger as water vapor condenses on them they are transferred from a bin for small droplets to a bin for larger ones. An advantage of the scheme is that the more explicit representation of cloud microphsyics eliminates many of the nonphysical parameters found in simpler schemes. The scheme is too computationally intensive for use in century-scale climate simulations but is practical for decadal simulations and can be used to inform development of simpler fast schemes. The cloud microphysics model is based on CARMA, the Community Aerosol and Radiation Model for Atmospheres, which uses a size bin scheme to represent the chemistry and microphysics of aerosols. Here the bin scheme is adapted to represent the microphysics of liquid cloud droplets and cloud ice, with the ability to represent the transfer of water between droplet bins and ice particle bins through freezing and thawing. The versions of CARMA used to represent aerosols and clouds are referred to as CARMA-aerosol and CARMA-cloud, respectively, and they are used together to represent the effects of aerosols on cloud particles. This award continues development of CARMA under previous support, most recently through AGS-1640903. Once developed, the model is used to address several issues in cloud physics and climate dynamics. In particular the model is used to consider the effect of cloud microphysics on climate change through simulations in which carbon dioxide concentration is instantaneously doubled, a standard way to assess the sensitivity of simulated climate to greenhouse gas increases. Motivation for the simulations comes from the increased climate sensitivity found in the latest generation of climate models contributing to the Climate Model Intercomparison Project (CMIP), which has been ascribed to changes in cloud microphysics. The work has societal relevance through its effort to improve understanding of the role of cloud microphysics in climate change. Cloud microphysics is a particular concern as clouds are frequently called out as the greatest source of uncertainty in model projections of future climate change used for decision support. The work also benefits the worldwide community of researchers who use and develop CESM. The project has educational value through the development of a stand-alone version of CARMA-cloud model which is suitable for classroom use, and through the support and training of a graduate student. 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. |
| 资助机构 | US-NSF |
| 项目经费 | $658,934.00 |
| 项目类型 | Standard Grant |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/210918 |
| 推荐引用方式 GB/T 7714 | Owen Toon.Improved Representation of Cloud-Aerosol Interactions in the Community Earth System Model: A New Sectional Cloud Model that Interacts with Modal and Sectional Aerosol Models.2021. |
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