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Published February 16, 2017 | Published + Supplemental Material
Journal Article Open

Assessment of an atmospheric transport model for annual inverse estimates of California greenhouse gas emissions

Abstract

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.

Additional Information

© 2017 American Geophysical Union. Received 13 MAY 2016; Accepted 16 JAN 2017; Accepted article online 19 JAN 2017; Published online 2 FEB 2017. We thank Dave Field, Dave Bush, Edward Wahl, Ken Reichl, Toby Walpert, and particularly Jon Kofler for assistance with measurements at WGC; John Lin, Christoph Gerbig, Steve Wofsy, Janusz Eluszkiewicz, and Thomas Nehrkorn for sharing the STILT code and advice; Paul Novelli for CO measurements used to estimate the CO background; Ying-Kuang Hsu, Bart Croes, Jorn Horner, Abhilash Vijayan, Vernon Hughes, and Webster Tassat for sharing CARB CO emission maps; and Krishna Muriki for assistance running the WRF-STILT models on the LBNL-Lawrencium cluster. Mixtli Campos-Pineda thanks a UC MEXUS-CONACYT Doctoral Fellowship. The measured and predicted CO data used in the analysis are shown in Figures 4-7 by season, and CO emission maps were obtained from the California Air Resources Board. This study was supported by the California Air Resources Board Research Division and the Natural Gas Research Program of the California Energy Commission under U.S. Department of Energy contract DE-AC02-05CH11231.

Attached Files

Published - Bagley_et_al-2017-Journal_of_Geophysical_Research__Atmospheres.pdf

Supplemental Material - jgrd53615-sup-0001-supplementary.pdf

Files

jgrd53615-sup-0001-supplementary.pdf
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Additional details

Created:
August 22, 2023
Modified:
October 25, 2023