Articles | Volume 9, issue 5
https://doi.org/10.5194/gmd-9-1959-2016
https://doi.org/10.5194/gmd-9-1959-2016
Development and technical paper
 | 
27 May 2016
Development and technical paper |  | 27 May 2016

Sensitivity of biogenic volatile organic compounds to land surface parameterizations and vegetation distributions in California

Chun Zhao, Maoyi Huang, Jerome D. Fast, Larry K. Berg, Yun Qian, Alex Guenther, Dasa Gu, Manish Shrivastava, Ying Liu, Stacy Walters, Gabriele Pfister, Jiming Jin, John E. Shilling, and Carsten Warneke

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Cited articles

Andreae, M. and Crutzen, P. J.: Atmospheric Aerosols: Biogeochemical Sources and Role in Atmospheric Chemistry, Science, 276, 1052–1058, https://doi.org/10.1126/science.276.5315.1052, 1997.
Arneth, A., Niinemets, Ü., Pressley, S., Bäck, J., Hari, P., Karl, T., Noe, S., Prentice, I. C., Serça, D., Hickler, T., Wolf, A., and Smith, B.: Process-based estimates of terrestrial ecosystem isoprene emissions: incorporating the effects of a direct CO2-isoprene interaction, Atmos. Chem. Phys., 7, 31–53, https://doi.org/10.5194/acp-7-31-2007, 2007.
Barlage, M., Chen, F., Tewari, M., Ikeda, K., Gochis, D., Dudhia, J., Rasmussen, R., Livneh, B., Ek, M., and Mitchell, K.: Noah land surface model modifications to improve snowpack prediction in the Colorado Rocky Mountains, J. Geophys. Res., 115, D22101, https://doi.org/10.1029/2009JD013470, 2010.
Bonan, G. B.: A land surface model (LSM ver. 1.0) for ecological, hydrological, and atmospheric studies: Technical description and user's guide, NCAR Tech. Note 4171STR, 150 pp., available at: http://opensky.ucar.edu/islandora/object/technotes:185 (last access: 25 May 2016), 1996.
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In this study, the latest version of MEGAN is coupled within CLM4 in WRF-Chem. In this implementation, MEGAN shares a consistent vegetation map with CLM4. This improved modeling framework is used to investigate the impact of two land surface schemes on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models.
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