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

Related authors

Toward a learnable Artificial Intelligence Model for Aerosol Chemistry and Interactions (AIMACI) based on the Multi-Head Self-Attention algorithm
Zihan Xia, Chun Zhao, Zining Yang, Qiuyan Du, Jiawang Feng, Chen Jin, Jun Shi, and Hong An
Atmos. Chem. Phys., 25, 6197–6218, https://doi.org/10.5194/acp-25-6197-2025,https://doi.org/10.5194/acp-25-6197-2025, 2025
Short summary
WRF-Chem simulations of snow nitrate and other physicochemical properties in northern China
Xia Wang, Tao Che, Xueyin Ruan, Shanna Yue, Jing Wang, Chun Zhao, and Lei Geng
Geosci. Model Dev., 18, 651–670, https://doi.org/10.5194/gmd-18-651-2025,https://doi.org/10.5194/gmd-18-651-2025, 2025
Short summary
Amending the algorithm of aerosol–radiation interactions in WRF-Chem (v4.4)
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025,https://doi.org/10.5194/gmd-18-585-2025, 2025
Short summary
Aerosol impacts on regional climate: chaotic or physical effect?
Jiawang Feng, Chun Zhao, Jun Gu, Gudongze Li, Mingyue Xu, Shengfu Lin, and Jie Feng
EGUsphere, https://doi.org/10.5194/egusphere-2024-4037,https://doi.org/10.5194/egusphere-2024-4037, 2025
Short summary
Comprehensive evaluation of iAMAS (v1.0) in simulating Antarctic meteorological fields with observations and reanalysis
Qike Yang, Chun Zhao, Jiawang Feng, Gudongze Li, Jun Gu, Zihan Xia, Mingyue Xu, and Zining Yang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-229,https://doi.org/10.5194/gmd-2024-229, 2025
Revised manuscript accepted for GMD
Short summary

Related subject area

Atmospheric sciences
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025,https://doi.org/10.5194/gmd-18-3985-2025, 2025
Short summary
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025,https://doi.org/10.5194/gmd-18-3921-2025, 2025
Short summary
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025,https://doi.org/10.5194/gmd-18-3965-2025, 2025
Short summary
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025,https://doi.org/10.5194/gmd-18-3819-2025, 2025
Short summary
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025,https://doi.org/10.5194/gmd-18-3781-2025, 2025
Short summary

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.
Download
Short summary
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.
Share