DOI: 10.1016/j.atmosenv.2015.09.034
Scopus记录号: 2-s2.0-84941945866
论文题名: Spatial and temporal correlation length as a measure for the stationarity of atmospheric dust aerosol distribution
作者: Schepanski K ; , Klüser L ; , Heinold B ; , Tegen I
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 122 起始页码: 10
结束页码: 21
语种: 英语
英文关键词: Correlation length
; COSMO-MUSCAT
; Dust forecast
; Dust transport
; Mediterranean
; Mineral dust
Scopus关键词: Aerosols
; Atmospheric aerosols
; Atmospheric chemistry
; Forecasting
; Marine applications
; Minerals
; Satellites
; Statistical methods
; Time series analysis
; Correlation lengths
; COSMO-MUSCAT
; Dust transport
; Mediterranean
; Mineral dust
; Dust
; aerosol composition
; atmospheric deposition
; atmospheric modeling
; correlation
; COSMOS
; desert
; dust
; forecasting method
; IASI
; optical depth
; satellite imagery
; spatiotemporal analysis
; time series
; aerosol
; Article
; atmosphere
; Consortium for Small scale Modelling
; controlled study
; environmental monitoring
; geographic distribution
; mineral dust
; MultiScale Chemistry Aerosol Transport Model
; North Africa
; priority journal
; simulation
; Southern Europe
; Spain
; statistical analysis
; time series analysis
; Mediterranean Region
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Fields of dust aerosol optical depth (AOD) from numerical models and satellite observations are widely used data sets for evaluating the actual distribution of atmospheric dust aerosol. In this study we investigate the use of estimates of spatial and temporal correlation lengths (CLs) calculated from simulations using the regional model system COSMO-MUSCAT (COSMO: Consortium for Small-scale Modelling; MUSCAT: MUltiScale Chemistry Aerosol Transport Model) to characterize the spatial and temporal variability of atmospheric aerosol distribution, here mineral dust, and to provide an estimate on the temporal model output interval required in order to represent the local evolution of atmospheric dustiness. The CLs indicate the scales of variability for dust and thus provide an estimate for the stationarity of dust conditions in space and time. Additionally, CLs can be an estimate for the required resolution in time and space of observational systems to observe changes in atmospheric dust conditions that would be relevant for dust forecasts. Here, two years of dust simulations using COSMO-MUSCAT are analyzed. CLs for the individual years 2007 and 2008 are compared to the entire two-year period illustrating the impact of the length of time series on statistical analysis. The two years are chosen as they are contrasting with regard to mineral dust loads and thus provide additional information on the representativeness of the statistical analysis. Results from the COSMO-MUSCAT CL analysis are compared against CL estimates from satellite observations, here dust AOD inferred from IASI (Infrared Atmospheric Sounding Interferometer), which provides bi-daily information of atmospheric dust loading over desert land and ocean. Although CLs estimated from the satellite observations are at a generally lower level of values, the results demonstrate the applicability of daily observations for assessing the atmospheric dust distribution. Main outcomes of this study illustrate the applicability of CL for characterizing the spatio-temporal variability in atmospheric dustiness. This is in particular of interest for determining time intervals at which for example dust forecasts need to be provided. Results from this study further demonstrate that bi-daily satellite dust observations are sufficient for assessing the dust distribution over regions such as the Mediterranean region that are far from the dust sources. © 2015 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81340
Appears in Collections: 气候变化事实与影响
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作者单位: Leibniz Institute for Tropospheric Research, Leipzig, Germany; German Aerospace Center, German Remote Sensing Datacenter, Oberpfaffenhofen, Germany
Recommended Citation:
Schepanski K,, Klüser L,, Heinold B,et al. Spatial and temporal correlation length as a measure for the stationarity of atmospheric dust aerosol distribution[J]. Atmospheric Environment,2015-01-01,122