Articles | Volume 11, issue 1
Geosci. Model Dev., 11, 305–319, 2018
https://doi.org/10.5194/gmd-11-305-2018
Geosci. Model Dev., 11, 305–319, 2018
https://doi.org/10.5194/gmd-11-305-2018
Development and technical paper
23 Jan 2018
Development and technical paper | 23 Jan 2018

Errors and improvements in the use of archived meteorological data for chemical transport modeling: an analysis using GEOS-Chem v11-01 driven by GEOS-5 meteorology

Karen Yu et al.

Related authors

Glyoxal yield from isoprene oxidation and relation to formaldehyde: chemical mechanism, constraints from SENEX aircraft observations, and interpretation of OMI satellite data
Christopher Chan Miller, Daniel J. Jacob, Eloise A. Marais, Karen Yu, Katherine R. Travis, Patrick S. Kim, Jenny A. Fisher, Lei Zhu, Glenn M. Wolfe, Thomas F. Hanisco, Frank N. Keutsch, Jennifer Kaiser, Kyung-Eun Min, Steven S. Brown, Rebecca A. Washenfelder, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 17, 8725–8738, https://doi.org/10.5194/acp-17-8725-2017,https://doi.org/10.5194/acp-17-8725-2017, 2017
Short summary
Sensitivity to grid resolution in the ability of a chemical transport model to simulate observed oxidant chemistry under high-isoprene conditions
Karen Yu, Daniel J. Jacob, Jenny A. Fisher, Patrick S. Kim, Eloise A. Marais, Christopher C. Miller, Katherine R. Travis, Lei Zhu, Robert M. Yantosca, Melissa P. Sulprizio, Ron C. Cohen, Jack E. Dibb, Alan Fried, Tomas Mikoviny, Thomas B. Ryerson, Paul O. Wennberg, and Armin Wisthaler
Atmos. Chem. Phys., 16, 4369–4378, https://doi.org/10.5194/acp-16-4369-2016,https://doi.org/10.5194/acp-16-4369-2016, 2016
Short summary

Related subject area

Atmospheric sciences
Simulations of aerosol pH in China using WRF-Chem (v4.0): sensitivities of aerosol pH and its temporal variations during haze episodes
Xueyin Ruan, Chun Zhao, Rahul A. Zaveri, Pengzhen He, Xinming Wang, Jingyuan Shao, and Lei Geng
Geosci. Model Dev., 15, 6143–6164, https://doi.org/10.5194/gmd-15-6143-2022,https://doi.org/10.5194/gmd-15-6143-2022, 2022
Short summary
A daily highest air temperature estimation method and spatial–temporal changes analysis of high temperature in China from 1979 to 2018
Ping Wang, Kebiao Mao, Fei Meng, Zhihao Qin, Shu Fang, and Sayed M. Bateni
Geosci. Model Dev., 15, 6059–6083, https://doi.org/10.5194/gmd-15-6059-2022,https://doi.org/10.5194/gmd-15-6059-2022, 2022
Short summary
TransClim (v1.0): a chemistry–climate response model for assessing the effect of mitigation strategies for road traffic on ozone
Vanessa Simone Rieger and Volker Grewe
Geosci. Model Dev., 15, 5883–5903, https://doi.org/10.5194/gmd-15-5883-2022,https://doi.org/10.5194/gmd-15-5883-2022, 2022
Short summary
A description of the first open-source community release of MISTRA-v9.0: a 0D/1D atmospheric boundary layer chemistry model
Josué Bock, Jan Kaiser, Max Thomas, Andreas Bott, and Roland von Glasow
Geosci. Model Dev., 15, 5807–5828, https://doi.org/10.5194/gmd-15-5807-2022,https://doi.org/10.5194/gmd-15-5807-2022, 2022
Short summary
Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022,https://doi.org/10.5194/gmd-15-5787-2022, 2022
Short summary

Cited articles

Allen, D. J., Rood, R. B., Thompson, A. M., and Hudson, R. D.: Three-dimensional radon 222 calculations using assimilated meteorological data and a convective mixing algorithm, J. Geophys. Res., 101, 6871–6881, 1996. a, b
Bacmeister, J. T. and Stephens, G.: Spatial statistics of likely convective clouds in CloudSat data, J. Geophys. Res.-Atmos., 116, D04104, https://doi.org/10.1029/2010JD014444, 2011. a
Bacmeister, J. T., Suarez, M. J., and Robertson, F. R.: Rain reevaporation, boundary layer-convection interactions, and Pacific rainfall patterns in an AGCM, J. Atmos. Sci., 63, 3383–3403, 2006. a
Balkanski, Y. J., Jacob, D. J., Gardner, G. M., Graustein, W. C., and Turekian, K. K.: Transport and residence times of tropospheric aerosols inferred from a global three-dimensional simulation of 210Pb, J. Geophys. Res.-Atmos., 98, 20573–20586, 1993. a, b, c
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res.-Atmos., 106, 23073–23095, 2001. a, b
Download
Short summary
Global simulations of atmospheric chemistry are generally conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it is unable to reproduce the GCM transport exactly. We investigate the cascade of errors associated with the off-line approach using the GEOS-5 GCM and GEOS-Chem CTM and discuss improvements in the use of archived meteorology.