气候变化领域集成服务门户(CCPortal): Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model

CCPortal

DOI	10.1029/2020MS002091
	Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model
	Tai S.-L.; Fast J.D.; Gustafson W.I.; Jr.; Chand D.; Gaudet B.; Feng Z.; Newsom R.
发表日期	2020
ISSN	19422466
卷号	12 期号:9
英文摘要	Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds. © 2020. The Authors.
语种	英语
scopus关键词	Atmospheric boundary layer; Atmospheric radiation; Boundary layer flow; Clouds; Optical radar; Population statistics; Radar stations; Remote sensing; Atmospheric radiation measurements; Boundary layer measurements; Cloud system-resolving models; Convective boundary layers; Environmental conditions; Statistical interpolation; U.S. Department of Energy; Weather research and forecasting models; Weather forecasting; aerosol; atmospheric convection; atmospheric modeling; boundary layer; cumulus; data assimilation; environmental conditions; field method; interpolation; lidar; observational method; radiosonde; simulation; weather forecasting; Great Plains; Kansas; Oklahoma [United States]; United States
来源期刊	Journal of Advances in Modeling Earth Systems
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156646
作者单位	Pacific Northwest National Laboratory, Richland, WA, United States
推荐引用方式 GB/T 7714	Tai S.-L.,Fast J.D.,Gustafson W.I.,et al. Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model[J],2020,12(9).
APA	Tai S.-L..,Fast J.D..,Gustafson W.I..,Jr..,Chand D..,...&Newsom R..(2020).Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model.Journal of Advances in Modeling Earth Systems,12(9).
MLA	Tai S.-L.,et al."Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model".Journal of Advances in Modeling Earth Systems 12.9(2020).