气候变化领域集成服务门户(CCPortal): Predicting Vertical Concentration Profiles in the Marine Atmospheric Boundary Layer With a Markov Chain Random Walk Model

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DOI	10.1029/2020JD032731
	Predicting Vertical Concentration Profiles in the Marine Atmospheric Boundary Layer With a Markov Chain Random Walk Model
	Park H.J.; Sherman T.; Freire L.S.; Wang G.; Bolster D.; Xian P.; Sorooshian A.; Reid J.S.; Richter D.H.
发表日期	2020
ISSN	2169897X
卷号	125 期号:19
英文摘要	In an effort to better represent aerosol transport in mesoscale and global-scale models, large eddy simulations (LES) from the National Center for Atmospheric Research (NCAR) Turbulence with Particles (NTLP) code are used to develop a Markov chain random walk model that predicts aerosol particle profiles in a cloud-free marine atmospheric boundary layer (MABL). The evolution of vertical concentration profiles are simulated for a range of aerosol particle sizes and in a neutral and an unstable boundary layer. For the neutral boundary layer we find, based on the LES statistics and a specific model time step, that there exist significant correlation for particle positions, meaning that particles near the bottom of the boundary are more likely to remain near the bottom of the boundary layer than being abruptly transported to the top, and vice versa. For the unstable boundary layer, a similar time interval exhibits a weaker tendency for an aerosol particle to remain close to its current location compared to the neutral case due to the strong nonlocal convective motions. In the limit of a large time interval, particles have been mixed throughout the MABL and virtually no temporal correlation exists. We leverage this information to parameterize a Markov chain random walk model that accurately predicts the evolution of vertical concentration profiles. The new methodology has significant potential to be applied at the subgrid level for coarser-scale weather and climate models, the utility of which is shown by comparison to airborne field data and global aerosol models. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	aerosol transport; atmospheric modeling; large eddy simulation (LES); random walk; sea spray generation; upscaled modeling
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/185732
作者单位	Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN, United States; FTS International, LLC, Dulles, VA, United States; Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN, United States; Institute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, Brazil; U.S. Naval Research Laboratory, Monterey, CA, United States; Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, United States
推荐引用方式 GB/T 7714	Park H.J.,Sherman T.,Freire L.S.,et al. Predicting Vertical Concentration Profiles in the Marine Atmospheric Boundary Layer With a Markov Chain Random Walk Model[J],2020,125(19).
APA	Park H.J..,Sherman T..,Freire L.S..,Wang G..,Bolster D..,...&Richter D.H..(2020).Predicting Vertical Concentration Profiles in the Marine Atmospheric Boundary Layer With a Markov Chain Random Walk Model.Journal of Geophysical Research: Atmospheres,125(19).
MLA	Park H.J.,et al."Predicting Vertical Concentration Profiles in the Marine Atmospheric Boundary Layer With a Markov Chain Random Walk Model".Journal of Geophysical Research: Atmospheres 125.19(2020).