DOI: 10.1002/2016JD026021
论文题名: Forecasting ultrafine particle concentrations from satellite and in situ observations
作者: Crippa P. ; Castruccio S. ; Pryor S.C.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2017
卷: 122, 期: 3 起始页码: 1828
结束页码: 1837
语种: 英语
英文关键词: ARMAX
; expectation maximization
; ultrafine particle prediction
Scopus关键词: aerosol
; algorithm
; atmospheric modeling
; concentration (composition)
; forecasting method
; in situ measurement
; optical property
; remote sensing
; solar radiation
; trace gas
; North America
英文摘要: Recent innovations in remote sensing technologies and retrievals offer the potential for predicting ultrafine particle (UFP) concentrations from space. However, the use of satellite observations to provide predictions of near-surface UFP concentrations is limited by the high frequency of incomplete predictor values (due to missing observations), the lack of models that account for the temporal dependence of UFP concentrations, and the large uncertainty in satellite retrievals. Herein we present a novel statistical approach designed to address the first two limitations. We estimate UFP concentrations by using lagged estimates of UFP and concurrent satellite-based observations of aerosol optical properties, ultraviolet solar radiation flux, and trace gas concentrations, wherein an expectation maximization algorithm is used to impute missing values in the satellite observations. The resulting model of UFP (derived by using an autoregressive moving average model with exogenous inputs) explains 51 and 28% of the day-to-day variability in concentrations at two sites in eastern North America. ©2017. The Authors. 资助项目: 1517365
; 1517365
; NNX16AG31G
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62686
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
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作者单位: COMET, School of Civil Engineering and Geosciences, Newcastle University, Newcastle Upon Tyne, United Kingdom; School of Mathematics and Statistics, Newcastle University, Newcastle Upon Tyne, United Kingdom; Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, United States
Recommended Citation:
Crippa P.,Castruccio S.,Pryor S.C.. Forecasting ultrafine particle concentrations from satellite and in situ observations[J]. Journal of Geophysical Research: Atmospheres,2017-01-01,122(3)