Articles | Volume 8, issue 3
https://doi.org/10.5194/gmd-8-549-2015
https://doi.org/10.5194/gmd-8-549-2015
Development and technical paper
 | 
12 Mar 2015
Development and technical paper |  | 12 Mar 2015

Characterising Brazilian biomass burning emissions using WRF-Chem with MOSAIC sectional aerosol

S. Archer-Nicholls, D. Lowe, E. Darbyshire, W. T. Morgan, M. M. Bela, G. Pereira, J. Trembath, J. W. Kaiser, K. M. Longo, S. R. Freitas, H. Coe, and G. McFiggans

Related authors

Development, intercomparison, and evaluation of an improved mechanism for the oxidation of dimethyl sulfide in the UKCA model
Ben A. Cala, Scott Archer-Nicholls, James Weber, N. Luke Abraham, Paul T. Griffiths, Lorrie Jacob, Y. Matthew Shin, Laura E. Revell, Matthew Woodhouse, and Alexander T. Archibald
Atmos. Chem. Phys., 23, 14735–14760, https://doi.org/10.5194/acp-23-14735-2023,https://doi.org/10.5194/acp-23-14735-2023, 2023
Short summary
Large simulated future changes in the nitrate radical under the CMIP6 SSP scenarios: implications for oxidation chemistry
Scott Archer-Nicholls, Rachel Allen, Nathan L. Abraham, Paul T. Griffiths, and Alex T. Archibald
Atmos. Chem. Phys., 23, 5801–5813, https://doi.org/10.5194/acp-23-5801-2023,https://doi.org/10.5194/acp-23-5801-2023, 2023
Short summary
Simulating organic aerosol in Delhi with WRF-Chem using the volatility-basis-set approach: exploring model uncertainty with a Gaussian process emulator
Ernesto Reyes-Villegas, Douglas Lowe, Jill S. Johnson, Kenneth S. Carslaw, Eoghan Darbyshire, Michael Flynn, James D. Allan, Hugh Coe, Ying Chen, Oliver Wild, Scott Archer-Nicholls, Alex Archibald, Siddhartha Singh, Manish Shrivastava, Rahul A. Zaveri, Vikas Singh, Gufran Beig, Ranjeet Sokhi, and Gordon McFiggans
Atmos. Chem. Phys., 23, 5763–5782, https://doi.org/10.5194/acp-23-5763-2023,https://doi.org/10.5194/acp-23-5763-2023, 2023
Short summary
Sources of surface O3 in the UK: tagging O3 within WRF-Chem
Johana Romero-Alvarez, Aurelia Lupaşcu, Douglas Lowe, Alba Badia, Scott Archer-Nicholls, Steve Dorling, Claire E. Reeves, and Tim Butler
Atmos. Chem. Phys., 22, 13797–13815, https://doi.org/10.5194/acp-22-13797-2022,https://doi.org/10.5194/acp-22-13797-2022, 2022
Short summary
Improvements to the representation of BVOC chemistry–climate interactions in UKCA (v11.5) with the CRI-Strat 2 mechanism: incorporation and evaluation
James Weber, Scott Archer-Nicholls, Nathan Luke Abraham, Youngsub M. Shin, Thomas J. Bannan, Carl J. Percival, Asan Bacak, Paulo Artaxo, Michael Jenkin, M. Anwar H. Khan, Dudley E. Shallcross, Rebecca H. Schwantes, Jonathan Williams, and Alex T. Archibald
Geosci. Model Dev., 14, 5239–5268, https://doi.org/10.5194/gmd-14-5239-2021,https://doi.org/10.5194/gmd-14-5239-2021, 2021
Short summary

Related subject area

Atmospheric sciences
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025,https://doi.org/10.5194/gmd-18-2983-2025, 2025
Short summary
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025,https://doi.org/10.5194/gmd-18-2861-2025, 2025
Short summary
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025,https://doi.org/10.5194/gmd-18-2747-2025, 2025
Short summary
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025,https://doi.org/10.5194/gmd-18-2701-2025, 2025
Short summary
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025,https://doi.org/10.5194/gmd-18-2679-2025, 2025
Short summary

Cited articles

Abdul-razzak, H. and Ghan, S. J.: A parameterization of aerosol activation 3. Sectional representation, J. Geophys. Res., 107, 4026, https://doi.org/10.1029/2001JD000483, 2002.
Ackermann, I. J., Hass, H., Memmesheimer, M., Ebel, A., Binkowski, F. S., and Shankar, U.: Modal aerosol dynamics model for Europe: development and first applications, Atmos. Environ., 32, 2981–2999, 1998.
Ackerman, T. P. and Toon, O. B.: Absorption of visible radiation in atmosphere containing mixtures of absorbing and nonabsorbing particles, Appl. Optics, 21, 758, https://doi.org/10.1364/AO.21.000758, 1982.
Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D., and Wennberg, P. O.: Emission factors for open and domestic biomass burning for use in atmospheric models, Atmos. Chem. Phys., 11, 4039–4072, https://doi.org/10.5194/acp-11-4039-2011, 2011.
Andela, N., Kaiser, J. W., Heil, A., van Leeuwen, T. T., Wooster, M. J., van der Werf, G. R., Remy, S., and Schultz, M. G.: Assessment of the Global Fire Assimilation System (GFASv1), Tech. Memo. 702, European Centre for Medium-range Weather Forecasts (ECMWF), Reading, UK, 2013.
Short summary
The regional WRF-Chem model was used to study aerosol particles from biomass burning in South America. The modelled estimates of fire plume injection heights were found to be too high, with serious implications for modelled aerosol vertical distribution, transport and impacts on local climate. A modified emission scenario was developed which improved the predicted injection height. Model results were compared and evaluated against in situ measurements from the 2012 SAMBBA flight campaign.
Share