DOI: 10.1002/2016JD025361
论文题名: Assessment of an atmospheric transport model for annual inverse estimates of California greenhouse gas emissions
作者: Bagley J.E. ; Jeong S. ; Cui X. ; Newman S. ; Zhang J. ; Priest C. ; Campos-Pineda M. ; Andrews A.E. ; Bianco L. ; Lloyd M. ; Lareau N. ; Clements C. ; Fischer M.L.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2017
卷: 122, 期: 3 起始页码: 1901
结束页码: 1918
语种: 英语
英文关键词: atmospheric transport
; carbon monoxide
; greenhouse gas
; meteorology
Scopus关键词: atmospheric gas
; atmospheric modeling
; atmospheric transport
; boundary layer
; carbon monoxide
; complex terrain
; emission
; error analysis
; greenhouse gas
; inverse analysis
; meteorology
; mixing ratio
; profiler
; uncertainty analysis
; wind velocity
; California
; Central Valley [California]
; United States
英文摘要: Atmospheric inverse estimates of gas emissions depend on transport model predictions, hence driving a need to assess uncertainties in the transport model. In this study we assess the uncertainty in WRF-STILT (Weather Research and Forecasting and Stochastic Time-Inverted Lagrangian Transport) model predictions using a combination of meteorological and carbon monoxide (CO) measurements. WRF configurations were selected to minimize meteorological biases using meteorological measurements of winds and boundary layer depths from surface stations and radar wind profiler sites across California. We compare model predictions with CO measurements from four tower sites in California from June 2013 through May 2014 to assess the seasonal biases and random errors in predicted CO mixing ratios. In general, the seasonal mean biases in boundary layer wind speed (< ~ 0.5 m/s), direction (< ~ 15°), and boundary layer height (< ~ 200 m) were small. However, random errors were large (~1.5–3.0 m/s for wind speed, ~ 40–60° for wind direction, and ~ 300–500 m for boundary layer height). Regression analysis of predicted and measured CO yielded near-unity slopes (i.e., within 1.0 ± 0.20) for the majority of sites and seasons, though a subset of sites and seasons exhibit larger (~30%) uncertainty, particularly when weak winds combined with complex terrain in the South Central Valley of California. Looking across sites and seasons, these results suggest that WRF-STILT simulations are sufficient to estimate emissions of CO to up to 15% on annual time scales across California. ©2017. American Geophysical Union. All Rights Reserved. 资助项目: DE-AC02-05CH11231
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62699
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: Lawrence Berkeley National Laboratory, Berkeley, CA, United States; California Institute of Technology, Pasadena, CA, United States; Department of Chemistry and Air Pollution Research Center, University of California, Riverside, CA, United States; ESRL, NOAA, Boulder, CO, United States; Department of Meteorology and Climate Science, San Jose State University, San Jose, CA, United States
Recommended Citation:
Bagley J.E.,Jeong S.,Cui X.,et al. Assessment of an atmospheric transport model for annual inverse estimates of California greenhouse gas emissions[J]. Journal of Geophysical Research: Atmospheres,2017-01-01,122(3)