气候变化领域集成服务门户(CCPortal): Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model

CCPortal

DOI	10.1029/2020JD033802
	Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model
	Kramer S.J.; Kirtman B.P.
发表日期	2021
ISSN	2169897X
卷号	126 期号:7
英文摘要	Prediction of Saharan dust customarily requires complex aerosols models and observations. A previous study of the Miami, Florida dust record in conjunction to reanalysis data discovered a possible source of subseasonal predictability using a dust-transport-efficiency (DTE) index. Development of the Subseasonal Forecast Experiment (SubX) has expanded global forecast products; producing multi-model ensemble forecasts out to 45 days. Retrospective forecast data from the Community Climate System Model version 4.0 (CCSM4) is used in direct comparison to National Centers for Environmental Prediction (NCEP) reanalysis to evaluate the CCSM4 subseasonal forecast and DTE index prediction skill of weekly dust variability. Successful prediction of weekly dust transport using the DTE index is variable year-to-year. The DTE most successfully predicts dust when there is high variability in the tropical winds, likely due to a fluctuating subtropical high, and is not dependent on the overall mean flow or total dust mass transported. The CCSM4 SubX retrospective forecast well represents North Atlantic meteorology out to week-3 in both mean flow and variability. Dust transport can be predicted using the DTE index and CCSM4 SubX retrospective forecasts at week-1 leads to the same success as contemporaneous NCEP reanalysis. © 2021. American Geophysical Union. All Rights Reserved.
英文关键词	aerosol transport; CCSM4 Subseasonal Forecast Model (SubX); dust transport efficiency; predictability; Saharan dust; tropical Atlantic meteorology
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/185362
作者单位	Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, United States; Now at Sonoma Technology, Petaluma, CA, United States
推荐引用方式 GB/T 7714	Kramer S.J.,Kirtman B.P.. Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model[J],2021,126(7).
APA	Kramer S.J.,&Kirtman B.P..(2021).Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model.Journal of Geophysical Research: Atmospheres,126(7).
MLA	Kramer S.J.,et al."Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model".Journal of Geophysical Research: Atmospheres 126.7(2021).