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SUBSURFACE OCEANS IN ICY SATELLITES
项目编号NNX15AQ88G S003
ISAMU MATSUYAMA
开始日期2015-07-23
结束日期2019-07-22
英文摘要The objective of this proposal is to improve the simulation and predictability of mixed-phase clouds and aerosol interactions in the Community Earth System Model (CESM) through comparisons with the ARM observations. There has been significant progress in the process understanding of mechanisms responsible for the formation and maintenance of mixed-phase clouds and roles of cloud microphysics, dynamics and radiation, through observational analyses and detailed cloud-resolving model (CRM)/large-eddy simulation (LES) modeling. However, the transfer of knowledge of our understanding to the improvement of representations in global climate models (GCMs) has been rather slow, due to (1) lack of long-term observation data on mixed-phase cloud properties for GCM evaluation; (2) crude GCM parameterizations/treatments hindering the realistic simulations of mixed-phase cloud dynamics/microphysics/radiation and interactions with aerosols; and (3) requirement of an integrated approach of testing and improving of parameterizations in GCMs, among others.    In this proposal, we aim to address the following science questions: (1) How are the mixed-phase clouds in the Arctic regions subject to the perturbations of seasonal varying aerosols acting as cloud condensational nuclei (CCN) and ice nuclei (IN)? (2) How does the prognostic treatment of IN (including its recycling and nucleation scavenging) in GCMs influence mixed-phase cloud occurrence, lifetime and precipitation? and (3) How does mixed-phase cloud parameterizations of ice microphysical processes/properties (e.g., ice nucleation, ice depositional growth, ice particle size distribution (PSD)) in GCMs affect their simulations of mixed-phase cloud properties and precipitation, through coupling with dynamics and radiation? To tackle these questions, we will run the Community Atmospheric Model version 5 (CAM5), the atmosphere component of CESM in the weather hindcast mode through the DOE Cloud-Associated Parameterizations Testbed (CAPT) and in the single-column model (SCM) mode, to facilitate the comparison with field campaign data and with detailed CRM/LES simulations. We will test several new treatments/parameterizations including (1) heterogeneous ice nucleation parameterization to explore the behavior of random (stochastic or time-dependent) and deterministic (surface-specific or time-independent) features of ice nucleation on the maintenance of mixed-phase clouds; (2) prognostic versus diagnostic treatment of IN to explore the importance of scavenging of IN; and (3) a modified shape parameter of ice PSD used in the bulk microphysics scheme in CAM5 to explore the impact on mixed-phase cloud properties through affecting the ice depositional growth rate and mass-weighted fall speed. The CAPT simulations will be run for a period of 2 years to compare with the long-term ARM data, and to examine the seasonal variability of mixed-phase clouds as well as their sensitivity to the aerosol perturbations. New treatments/parameterizations will also be tested in the free-running mode to examine their performance when large-scale atmospheric circulation feedbacks are included.     The observation data used in the testing include multi-sensor mixed-phase cloud retrievals from ARM sites. With the multi-sensor measurements at these sites, stratiform mixed-phase cloud properties, including droplet effective radius, droplet concentration and liquid water path for the liquid phase and ice concentration, ice effective radius and ice water path for the ice phase are retrieved. We will focus on the evaluation of modeled boundary layer mixed-phase clouds and interactions with aerosols (dust and biomass burning aerosols) at the NSA site, while retrievals at mid-latitude sites offer important data for mid-level mixed-phase cloud evaluation.
学科分类03 - 天文学;1107 - 航空航天工程;11 - 工程与技术
资助机构US-NASA
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/74140
推荐引用方式
GB/T 7714
ISAMU MATSUYAMA.SUBSURFACE OCEANS IN ICY SATELLITES.2015.
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