Articles | Volume 12, issue 7
https://doi.org/10.5194/gmd-12-3283-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-3283-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The FireWork v2.0 air quality forecast system with biomass burning emissions from the Canadian Forest Fire Emissions Prediction System v2.03
Air Quality Research Division, Environment and Climate Change
Canada, Ontario, Canada
Kerry Anderson
Canadian Forest Service, Natural Resources Canada, Alberta, Canada
retired
Radenko Pavlovic
Air Quality Modelling Applications Section, Environment and Climate
Change Canada, Quebec, Canada
Michael D. Moran
Air Quality Research Division, Environment and Climate Change
Canada, Ontario, Canada
Peter Englefield
Canadian Forest Service, Natural Resources Canada, Alberta, Canada
Dan K. Thompson
Canadian Forest Service, Natural Resources Canada, Alberta, Canada
Rodrigo Munoz-Alpizar
Air Quality Modelling Applications Section, Environment and Climate
Change Canada, Quebec, Canada
Hugo Landry
Air Quality Modelling Applications Section, Environment and Climate
Change Canada, Quebec, Canada
Related authors
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul Makar, and Dan Thompson
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-31, https://doi.org/10.5194/gmd-2024-31, 2024
Preprint under review for GMD
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Debora Griffin, Jack Chen, Kerry Anderson, Paul Makar, Chris A. McLinden, Enrico Dammers, and Andre Fogal
EGUsphere, https://doi.org/10.5194/egusphere-2023-649, https://doi.org/10.5194/egusphere-2023-649, 2023
Short summary
Short summary
Satellite-derived CO emissions provide new insights into the understanding of global CO emission rates from wildfires. We use TROPOMI satellite data to create a global inventory database of wildfire CO emissions. These satellite-derived wildfire emissions are used for the evaluation and improvement of existing fire emission inventories, and to examine how the wildfire CO emissions changed over the past two decades.
Katherine L. Hayden, Shao-Meng Li, John Liggio, Michael J. Wheeler, Jeremy J. B. Wentzell, Amy Leithead, Peter Brickell, Richard L. Mittermeier, Zachary Oldham, Cristian M. Mihele, Ralf M. Staebler, Samar G. Moussa, Andrea Darlington, Mengistu Wolde, Daniel Thompson, Jack Chen, Debora Griffin, Ellen Eckert, Jenna C. Ditto, Megan He, and Drew R. Gentner
Atmos. Chem. Phys., 22, 12493–12523, https://doi.org/10.5194/acp-22-12493-2022, https://doi.org/10.5194/acp-22-12493-2022, 2022
Short summary
Short summary
In this study, airborne measurements provided the most detailed characterization, to date, of boreal forest wildfire emissions. Measurements showed a large diversity of air pollutants expanding the volatility range typically reported. A large portion of organic species was unidentified, likely comprised of complex organic compounds. Aircraft-derived emissions improve wildfire chemical speciation and can support reliable model predictions of pollution from boreal forest wildfires.
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
Geosci. Model Dev., 15, 219–249, https://doi.org/10.5194/gmd-15-219-2022, https://doi.org/10.5194/gmd-15-219-2022, 2022
Short summary
Short summary
A new lookup table for aerosol optical properties based on a Mie scattering code was calculated and adopted within an improved version of the photolysis module in the GEM-MACH in-line chemical transport model. The modified version of the photolysis module makes use of online interactive aerosol feedback and applies core-shell parameterizations to the black carbon absorption efficiency based on Bond et al. (2006) to the size bins with black carbon mass fraction of less than 40 %.
Debora Griffin, Chris A. McLinden, Enrico Dammers, Cristen Adams, Chelsea E. Stockwell, Carsten Warneke, Ilann Bourgeois, Jeff Peischl, Thomas B. Ryerson, Kyle J. Zarzana, Jake P. Rowe, Rainer Volkamer, Christoph Knote, Natalie Kille, Theodore K. Koenig, Christopher F. Lee, Drew Rollins, Pamela S. Rickly, Jack Chen, Lukas Fehr, Adam Bourassa, Doug Degenstein, Katherine Hayden, Cristian Mihele, Sumi N. Wren, John Liggio, Ayodeji Akingunola, and Paul Makar
Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, https://doi.org/10.5194/amt-14-7929-2021, 2021
Short summary
Short summary
Satellite-derived NOx emissions from biomass burning are estimated with TROPOMI observations. Two common emission estimation methods are applied, and sensitivity tests with model output were performed to determine the accuracy of these methods. The effect of smoke aerosols on TROPOMI NO2 columns is estimated and compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
Short summary
Short summary
Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Paul A. Makar, Ayodeji Akingunola, Jack Chen, Balbir Pabla, Wanmin Gong, Craig Stroud, Christopher Sioris, Kerry Anderson, Philip Cheung, Junhua Zhang, and Jason Milbrandt
Atmos. Chem. Phys., 21, 10557–10587, https://doi.org/10.5194/acp-21-10557-2021, https://doi.org/10.5194/acp-21-10557-2021, 2021
Short summary
Short summary
We have examined the effects of airborne particles on absorption and scattering of incoming sunlight by the particles themselves via cloud formation. We used an advanced, combined high-resolution weather forecast and chemical transport computer model, for western North America, and simulations with and without the connections between particles and weather enabled. Feedbacks improved weather and air pollution forecasts and changed cloud behaviour and forest-fire pollutant amount and height.
Debora Griffin, Christopher Sioris, Jack Chen, Nolan Dickson, Andrew Kovachik, Martin de Graaf, Swadhin Nanda, Pepijn Veefkind, Enrico Dammers, Chris A. McLinden, Paul Makar, and Ayodeji Akingunola
Atmos. Meas. Tech., 13, 1427–1445, https://doi.org/10.5194/amt-13-1427-2020, https://doi.org/10.5194/amt-13-1427-2020, 2020
Short summary
Short summary
This study looks into validating the aerosol layer height product from the recently launched TROPOspheric Monitoring Instrument (TROPOMI) for forest fire plume through comparisons with two other satellite products, and interpreting differences due to the individual measurement techniques. These satellite observations are compared to predicted plume heights from Environment and Climate Change's air quality forecast model.
Cristen Adams, Chris A. McLinden, Mark W. Shephard, Nolan Dickson, Enrico Dammers, Jack Chen, Paul Makar, Karen E. Cady-Pereira, Naomi Tam, Shailesh K. Kharol, Lok N. Lamsal, and Nickolay A. Krotkov
Atmos. Chem. Phys., 19, 2577–2599, https://doi.org/10.5194/acp-19-2577-2019, https://doi.org/10.5194/acp-19-2577-2019, 2019
Short summary
Short summary
We estimated how much carbon monoxide, ammonia, and nitrogen oxides were emitted in the smoke from the Fort McMurray Horse River wildfire using satellite data and air quality models. The fire emitted amounts of carbon monoxide that were similar to anthropogenic (human-caused) emissions for all of Alberta over a full year. We also estimated large amounts of ammonia and nitrogen oxides emitted from the fire. These results can be used to evaluate the performance of air quality forecasting models.
Wanmin Gong, Stephen R. Beagley, Sophie Cousineau, Mourad Sassi, Rodrigo Munoz-Alpizar, Sylvain Ménard, Jacinthe Racine, Junhua Zhang, Jack Chen, Heather Morrison, Sangeeta Sharma, Lin Huang, Pascal Bellavance, Jim Ly, Paul Izdebski, Lynn Lyons, and Richard Holt
Atmos. Chem. Phys., 18, 16653–16687, https://doi.org/10.5194/acp-18-16653-2018, https://doi.org/10.5194/acp-18-16653-2018, 2018
Short summary
Short summary
The navigability of the Arctic Ocean is increasing with the warming in recent years. Using model simulations at a much finer resolution than previous pan-Arctic studies, the impact of marine shipping emissions on air pollution in the Canadian Arctic is assessed for present (2010) and projected levels in 2030. The study found that shipping emissions have a local-to-regional impact in the Arctic at the current level; the impact will increase significantly in a projected business-as-usual scenario.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul Makar, and Dan Thompson
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-31, https://doi.org/10.5194/gmd-2024-31, 2024
Preprint under review for GMD
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
Short summary
Short summary
This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Debora Griffin, Jack Chen, Kerry Anderson, Paul Makar, Chris A. McLinden, Enrico Dammers, and Andre Fogal
EGUsphere, https://doi.org/10.5194/egusphere-2023-649, https://doi.org/10.5194/egusphere-2023-649, 2023
Short summary
Short summary
Satellite-derived CO emissions provide new insights into the understanding of global CO emission rates from wildfires. We use TROPOMI satellite data to create a global inventory database of wildfire CO emissions. These satellite-derived wildfire emissions are used for the evaluation and improvement of existing fire emission inventories, and to examine how the wildfire CO emissions changed over the past two decades.
Katherine L. Hayden, Shao-Meng Li, John Liggio, Michael J. Wheeler, Jeremy J. B. Wentzell, Amy Leithead, Peter Brickell, Richard L. Mittermeier, Zachary Oldham, Cristian M. Mihele, Ralf M. Staebler, Samar G. Moussa, Andrea Darlington, Mengistu Wolde, Daniel Thompson, Jack Chen, Debora Griffin, Ellen Eckert, Jenna C. Ditto, Megan He, and Drew R. Gentner
Atmos. Chem. Phys., 22, 12493–12523, https://doi.org/10.5194/acp-22-12493-2022, https://doi.org/10.5194/acp-22-12493-2022, 2022
Short summary
Short summary
In this study, airborne measurements provided the most detailed characterization, to date, of boreal forest wildfire emissions. Measurements showed a large diversity of air pollutants expanding the volatility range typically reported. A large portion of organic species was unidentified, likely comprised of complex organic compounds. Aircraft-derived emissions improve wildfire chemical speciation and can support reliable model predictions of pollution from boreal forest wildfires.
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
Geosci. Model Dev., 15, 219–249, https://doi.org/10.5194/gmd-15-219-2022, https://doi.org/10.5194/gmd-15-219-2022, 2022
Short summary
Short summary
A new lookup table for aerosol optical properties based on a Mie scattering code was calculated and adopted within an improved version of the photolysis module in the GEM-MACH in-line chemical transport model. The modified version of the photolysis module makes use of online interactive aerosol feedback and applies core-shell parameterizations to the black carbon absorption efficiency based on Bond et al. (2006) to the size bins with black carbon mass fraction of less than 40 %.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
Short summary
Short summary
We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Debora Griffin, Chris A. McLinden, Enrico Dammers, Cristen Adams, Chelsea E. Stockwell, Carsten Warneke, Ilann Bourgeois, Jeff Peischl, Thomas B. Ryerson, Kyle J. Zarzana, Jake P. Rowe, Rainer Volkamer, Christoph Knote, Natalie Kille, Theodore K. Koenig, Christopher F. Lee, Drew Rollins, Pamela S. Rickly, Jack Chen, Lukas Fehr, Adam Bourassa, Doug Degenstein, Katherine Hayden, Cristian Mihele, Sumi N. Wren, John Liggio, Ayodeji Akingunola, and Paul Makar
Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, https://doi.org/10.5194/amt-14-7929-2021, 2021
Short summary
Short summary
Satellite-derived NOx emissions from biomass burning are estimated with TROPOMI observations. Two common emission estimation methods are applied, and sensitivity tests with model output were performed to determine the accuracy of these methods. The effect of smoke aerosols on TROPOMI NO2 columns is estimated and compared to aircraft observations from four different aircraft campaigns measuring biomass burning plumes in 2018 and 2019 in North America.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
Short summary
Short summary
Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Nicolas Gasset, Vincent Fortin, Milena Dimitrijevic, Marco Carrera, Bernard Bilodeau, Ryan Muncaster, Étienne Gaborit, Guy Roy, Nedka Pentcheva, Maxim Bulat, Xihong Wang, Radenko Pavlovic, Franck Lespinas, Dikra Khedhaouiria, and Juliane Mai
Hydrol. Earth Syst. Sci., 25, 4917–4945, https://doi.org/10.5194/hess-25-4917-2021, https://doi.org/10.5194/hess-25-4917-2021, 2021
Short summary
Short summary
In this paper, we highlight the importance of including land-data assimilation as well as offline precipitation analysis components in a regional reanalysis system. We also document the performance of the first multidecadal 10 km reanalysis performed with the GEM atmospheric model that can be used for seamless land-surface and hydrological modelling in North America. It is of particular interest for transboundary basins, as existing datasets often show discontinuities at the border.
Paul A. Makar, Ayodeji Akingunola, Jack Chen, Balbir Pabla, Wanmin Gong, Craig Stroud, Christopher Sioris, Kerry Anderson, Philip Cheung, Junhua Zhang, and Jason Milbrandt
Atmos. Chem. Phys., 21, 10557–10587, https://doi.org/10.5194/acp-21-10557-2021, https://doi.org/10.5194/acp-21-10557-2021, 2021
Short summary
Short summary
We have examined the effects of airborne particles on absorption and scattering of incoming sunlight by the particles themselves via cloud formation. We used an advanced, combined high-resolution weather forecast and chemical transport computer model, for western North America, and simulations with and without the connections between particles and weather enabled. Feedbacks improved weather and air pollution forecasts and changed cloud behaviour and forest-fire pollutant amount and height.
Dan K. Thompson and Kimberly Morrison
Nat. Hazards Earth Syst. Sci., 20, 3439–3454, https://doi.org/10.5194/nhess-20-3439-2020, https://doi.org/10.5194/nhess-20-3439-2020, 2020
Short summary
Short summary
We describe critically low relative humidity and high wind speeds above which only documented wildfires were seen to occur and where no agricultural fires were documented in southern Canada. We then applied these thresholds to the much larger satellite record from 2002–2018 to quantify regional differences in both the rate of observed burning and the number of days with critical weather conditions to sustain a wildfire in this grassland and agricultural region.
Debora Griffin, Christopher Sioris, Jack Chen, Nolan Dickson, Andrew Kovachik, Martin de Graaf, Swadhin Nanda, Pepijn Veefkind, Enrico Dammers, Chris A. McLinden, Paul Makar, and Ayodeji Akingunola
Atmos. Meas. Tech., 13, 1427–1445, https://doi.org/10.5194/amt-13-1427-2020, https://doi.org/10.5194/amt-13-1427-2020, 2020
Short summary
Short summary
This study looks into validating the aerosol layer height product from the recently launched TROPOspheric Monitoring Instrument (TROPOMI) for forest fire plume through comparisons with two other satellite products, and interpreting differences due to the individual measurement techniques. These satellite observations are compared to predicted plume heights from Environment and Climate Change's air quality forecast model.
Cynthia H. Whaley, Elisabeth Galarneau, Paul A. Makar, Michael D. Moran, and Junhua Zhang
Atmos. Chem. Phys., 20, 2911–2925, https://doi.org/10.5194/acp-20-2911-2020, https://doi.org/10.5194/acp-20-2911-2020, 2020
Short summary
Short summary
Benzene and polycyclic aromatic compounds are toxic air pollutants and ubiquitous in the environment. Using a chemical transport model, we have determined the net impact of vehicle emissions on ambient concentrations of these species. Traffic emissions were found to be a significant fraction of ambient pollution in the densely populated modelled region of North America. Our simulations demonstrate the air quality benefits that would result from transitioning to a zero-emission vehicle fleet.
Mark W. Shephard, Enrico Dammers, Karen E. Cady-Pereira, Shailesh K. Kharol, Jesse Thompson, Yonatan Gainariu-Matz, Junhua Zhang, Chris A. McLinden, Andrew Kovachik, Michael Moran, Shabtai Bittman, Christopher E. Sioris, Debora Griffin, Matthew J. Alvarado, Chantelle Lonsdale, Verica Savic-Jovcic, and Qiong Zheng
Atmos. Chem. Phys., 20, 2277–2302, https://doi.org/10.5194/acp-20-2277-2020, https://doi.org/10.5194/acp-20-2277-2020, 2020
Short summary
Short summary
Presented is a description and survey demonstrating the capabilities of the CrIS ammonia product for monitoring, air quality forecast model evaluation, dry deposition estimates, and emission estimates of an agricultural hotspot.
Paul A. Moore, Maxwell C. Lukenbach, Dan K. Thompson, Nick Kettridge, Gustaf Granath, and James M. Waddington
Biogeosciences, 16, 3491–3506, https://doi.org/10.5194/bg-16-3491-2019, https://doi.org/10.5194/bg-16-3491-2019, 2019
Short summary
Short summary
Using very-high-resolution digital elevation models (DEMs), we assessed the basic structure and microtopographic variability of hummock–hollow plots at boreal and hemi-boreal sites primarily in North America. Using a simple model of peatland biogeochemical function, our results suggest that both surface heating and moss productivity may not be adequately resolved in models which only consider idealized hummock–hollow units.
Xiaoyi Zhao, Debora Griffin, Vitali Fioletov, Chris McLinden, Jonathan Davies, Akira Ogyu, Sum Chi Lee, Alexandru Lupu, Michael D. Moran, Alexander Cede, Martin Tiefengraber, and Moritz Müller
Atmos. Chem. Phys., 19, 10619–10642, https://doi.org/10.5194/acp-19-10619-2019, https://doi.org/10.5194/acp-19-10619-2019, 2019
Short summary
Short summary
New nitrogen dioxide (NO2) retrieval algorithms are developed for Pandora zenith-sky measurements. A column-to-surface conversion look-up table was produced for the Pandora instruments; therefore, quick and practical Pandora-based surface NO2 concentration data can be obtained for air quality monitoring purposes. It is demonstrated that the surface NO2 concentration is controlled not only by the planetary boundary layer height but also by both boundary layer dynamics and photochemistry.
Matthew Russell, Amir Hakami, Paul A. Makar, Ayodeji Akingunola, Junhua Zhang, Michael D. Moran, and Qiong Zheng
Atmos. Chem. Phys., 19, 4393–4417, https://doi.org/10.5194/acp-19-4393-2019, https://doi.org/10.5194/acp-19-4393-2019, 2019
Short summary
Short summary
High-resolution air-quality forecast modeling results are compared for two different grid spacings for the Environment and Climate Change Canada GEM-MACH model. While the higher-resolution simulations have worse formal error scores, we show that the higher-resolution model nevertheless has the ability to better resolve plume maxima and has better performance when the evaluation occurs using new scoring metrics which operate on an equal-representative-area basis.
Cristen Adams, Chris A. McLinden, Mark W. Shephard, Nolan Dickson, Enrico Dammers, Jack Chen, Paul Makar, Karen E. Cady-Pereira, Naomi Tam, Shailesh K. Kharol, Lok N. Lamsal, and Nickolay A. Krotkov
Atmos. Chem. Phys., 19, 2577–2599, https://doi.org/10.5194/acp-19-2577-2019, https://doi.org/10.5194/acp-19-2577-2019, 2019
Short summary
Short summary
We estimated how much carbon monoxide, ammonia, and nitrogen oxides were emitted in the smoke from the Fort McMurray Horse River wildfire using satellite data and air quality models. The fire emitted amounts of carbon monoxide that were similar to anthropogenic (human-caused) emissions for all of Alberta over a full year. We also estimated large amounts of ammonia and nitrogen oxides emitted from the fire. These results can be used to evaluate the performance of air quality forecasting models.
Wanmin Gong, Stephen R. Beagley, Sophie Cousineau, Mourad Sassi, Rodrigo Munoz-Alpizar, Sylvain Ménard, Jacinthe Racine, Junhua Zhang, Jack Chen, Heather Morrison, Sangeeta Sharma, Lin Huang, Pascal Bellavance, Jim Ly, Paul Izdebski, Lynn Lyons, and Richard Holt
Atmos. Chem. Phys., 18, 16653–16687, https://doi.org/10.5194/acp-18-16653-2018, https://doi.org/10.5194/acp-18-16653-2018, 2018
Short summary
Short summary
The navigability of the Arctic Ocean is increasing with the warming in recent years. Using model simulations at a much finer resolution than previous pan-Arctic studies, the impact of marine shipping emissions on air pollution in the Canadian Arctic is assessed for present (2010) and projected levels in 2030. The study found that shipping emissions have a local-to-regional impact in the Arctic at the current level; the impact will increase significantly in a projected business-as-usual scenario.
Junhua Zhang, Michael D. Moran, Qiong Zheng, Paul A. Makar, Pegah Baratzadeh, George Marson, Peter Liu, and Shao-Meng Li
Atmos. Chem. Phys., 18, 10459–10481, https://doi.org/10.5194/acp-18-10459-2018, https://doi.org/10.5194/acp-18-10459-2018, 2018
Short summary
Short summary
This paper discusses the development of new synthesized emissions inventories and the generation of air quality model-ready emissions files for the Athabasca Oil Sands Region of Alberta, Canada, using multiple emissions inventories, continuous emissions monitoring data, and inferred emission rates based on aircraft measurements. Novel facility-specific gridded spatial surrogate fields were generated to allocate emissions spatially within each huge mining facility.
Paul A. Makar, Ayodeji Akingunola, Julian Aherne, Amanda S. Cole, Yayne-abeba Aklilu, Junhua Zhang, Isaac Wong, Katherine Hayden, Shao-Meng Li, Jane Kirk, Ken Scott, Michael D. Moran, Alain Robichaud, Hazel Cathcart, Pegah Baratzedah, Balbir Pabla, Philip Cheung, Qiong Zheng, and Dean S. Jeffries
Atmos. Chem. Phys., 18, 9897–9927, https://doi.org/10.5194/acp-18-9897-2018, https://doi.org/10.5194/acp-18-9897-2018, 2018
Short summary
Short summary
Complex computer model output was compared to and fused with observation data, to estimate potential damage due to acidifying precipitation for ecosystems in the Canadian provinces of Alberta and Saskatchewan. Estimated deposition was compared to the maximum no-damage ecosystem capacity for sulfur and/or nitrogen uptake; these critical loads were exceeded, for areas between 10 000 and 330 000 square kilometres, depending on ecosystem type: ecosystem damage will occur at 2013 emission levels.
Ayodeji Akingunola, Paul A. Makar, Junhua Zhang, Andrea Darlington, Shao-Meng Li, Mark Gordon, Michael D. Moran, and Qiong Zheng
Atmos. Chem. Phys., 18, 8667–8688, https://doi.org/10.5194/acp-18-8667-2018, https://doi.org/10.5194/acp-18-8667-2018, 2018
Short summary
Short summary
We examine the manner in which air-quality models simulate lofting of buoyant plumes of emissions from stacks (plume rise) and the impact of the level of detail in algorithms simulating particles' variation in size (particle size distribution). The most commonly used plume rise algorithm underestimates the height of plumes compared to observations, while a revised algorithm has much better performance. A 12-bin size distribution reduced the forecast 2-bin size distribution bias error by 32 %.
Stephanie C. Pugliese, Jennifer G. Murphy, Felix R. Vogel, Michael D. Moran, Junhua Zhang, Qiong Zheng, Craig A. Stroud, Shuzhan Ren, Douglas Worthy, and Gregoire Broquet
Atmos. Chem. Phys., 18, 3387–3401, https://doi.org/10.5194/acp-18-3387-2018, https://doi.org/10.5194/acp-18-3387-2018, 2018
Short summary
Short summary
We developed the Southern Ontario CO2 Emissions (SOCE) inventory, which identifies the spatial and temporal distribution (2.5 km and hourly, respectively) of CO2 emissions from seven source sectors. When the SOCE inventory was used with a chemistry transport model, we found strong agreement between modelled and measured mixing ratios. We were able to quantify that natural gas combustion contributes > 80 % of CO2 emissions at nighttime while on-road emissions contribute > 70 % during the day.
Kerry Anderson, Al Pankratz, Curtis Mooney, and Kelly Fleetham
Earth Syst. Sci. Data, 10, 325–337, https://doi.org/10.5194/essd-10-325-2018, https://doi.org/10.5194/essd-10-325-2018, 2018
Short summary
Short summary
A field project was conducted to measure smoke plumes from wildland fires in Alberta. This study used handheld inclinometers and photos taken at fire lookout towers. Observations of 222 plumes were collected from 2010 to 2015.
Unanticipated issues were uncovered including instrument limitations, environmental conditions, and subjectivity of observations. Despite these problems, the data set showed responses to fire behaviour conditions consistent with processes leading to plume rise.
Unanticipated issues were uncovered including instrument limitations, environmental conditions, and subjectivity of observations. Despite these problems, the data set showed responses to fire behaviour conditions consistent with processes leading to plume rise.
Matthew C. Elmes, Dan K. Thompson, James H. Sherwood, and Jonathan S. Price
Nat. Hazards Earth Syst. Sci., 18, 157–170, https://doi.org/10.5194/nhess-18-157-2018, https://doi.org/10.5194/nhess-18-157-2018, 2018
Short summary
Short summary
The infrequent coinciding of several hydrometeorological conditions common to the Western Boreal Plain, including low autumn soil moisture, modest snowpack, lack of spring precipitation, and high spring air temperatures and winds, ultimately led to the widespread Horse river fire in May of 2016. Monitoring antecedent soil moisture would aid management strategies in producing of more accurate overwintered Drought Code calculations, providing early warning signals ahead of spring wildfire seasons.
Yuan You, Ralf M. Staebler, Samar G. Moussa, Yushan Su, Tony Munoz, Craig Stroud, Junhua Zhang, and Michael D. Moran
Atmos. Chem. Phys., 17, 14119–14143, https://doi.org/10.5194/acp-17-14119-2017, https://doi.org/10.5194/acp-17-14119-2017, 2017
Short summary
Short summary
A novel approach for traffic emission measurements is shown to have the capacity to provide high-time-resolution accurate concentrations of key air pollutants. A top-down method for quantifying real-world emission rates produced vehicular emission factor estimates for carbon monoxide that agreed well with bottom-up values. Significant ammonia and hydrogen cyanide emissions were observed. The main factors modulating the concentrations were turbulent mixing and traffic density.
Vitali Fioletov, Chris A. McLinden, Shailesh K. Kharol, Nickolay A. Krotkov, Can Li, Joanna Joiner, Michael D. Moran, Robert Vet, Antoon J. H. Visschedijk, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys., 17, 12597–12616, https://doi.org/10.5194/acp-17-12597-2017, https://doi.org/10.5194/acp-17-12597-2017, 2017
Vitali E. Fioletov, Chris A. McLinden, Nickolay Krotkov, Can Li, Joanna Joiner, Nicolas Theys, Simon Carn, and Mike D. Moran
Atmos. Chem. Phys., 16, 11497–11519, https://doi.org/10.5194/acp-16-11497-2016, https://doi.org/10.5194/acp-16-11497-2016, 2016
Short summary
Short summary
We introduce the first space-based catalogue of SO2 emission sources seen by OMI. The inventory contains about 500 sources. They account for about a half of all SO2 emissions; the remaining half is likely related to sources emitting less than 30 kt yr−1 and not detected by OMI. The sources are grouped by type (volcanoes, power plants, oil- and gas-related sources, and smelters) and country. The catalogue presented herein can be used for verification of available SO2 emission inventories.
D. Wen, L. Zhang, J. C. Lin, R. Vet, and M. D. Moran
Geosci. Model Dev., 7, 1037–1050, https://doi.org/10.5194/gmd-7-1037-2014, https://doi.org/10.5194/gmd-7-1037-2014, 2014
P. A. Makar, R. Nissen, A. Teakles, J. Zhang, Q. Zheng, M. D. Moran, H. Yau, and C. diCenzo
Geosci. Model Dev., 7, 1001–1024, https://doi.org/10.5194/gmd-7-1001-2014, https://doi.org/10.5194/gmd-7-1001-2014, 2014
X. Wang, L. Zhang, and M. D. Moran
Geosci. Model Dev., 7, 799–819, https://doi.org/10.5194/gmd-7-799-2014, https://doi.org/10.5194/gmd-7-799-2014, 2014
E. Galarneau, P. A. Makar, Q. Zheng, J. Narayan, J. Zhang, M. D. Moran, M. A. Bari, S. Pathela, A. Chen, and R. Chlumsky
Atmos. Chem. Phys., 14, 4065–4077, https://doi.org/10.5194/acp-14-4065-2014, https://doi.org/10.5194/acp-14-4065-2014, 2014
L. Zhang, X. Wang, M. D. Moran, and J. Feng
Atmos. Chem. Phys., 13, 10005–10025, https://doi.org/10.5194/acp-13-10005-2013, https://doi.org/10.5194/acp-13-10005-2013, 2013
E. Solazzo, R. Bianconi, G. Pirovano, M. D. Moran, R. Vautard, C. Hogrefe, K. W. Appel, V. Matthias, P. Grossi, B. Bessagnet, J. Brandt, C. Chemel, J. H. Christensen, R. Forkel, X. V. Francis, A. B. Hansen, S. McKeen, U. Nopmongcol, M. Prank, K. N. Sartelet, A. Segers, J. D. Silver, G. Yarwood, J. Werhahn, J. Zhang, S. T. Rao, and S. Galmarini
Geosci. Model Dev., 6, 791–818, https://doi.org/10.5194/gmd-6-791-2013, https://doi.org/10.5194/gmd-6-791-2013, 2013
D. Wen, J. C. Lin, L. Zhang, R. Vet, and M. D. Moran
Geosci. Model Dev., 6, 327–344, https://doi.org/10.5194/gmd-6-327-2013, https://doi.org/10.5194/gmd-6-327-2013, 2013
Related subject area
Atmospheric sciences
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
Spherical air mass factors in one and two dimensions with SASKTRAN 1.6.0
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
Implementation and evaluation of updated photolysis rates in the EMEP MSC-W chemistry-transport model using Cloud-J v7.3e
Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2
Assimilation of GNSS Tropospheric Gradients into the Weather Research and Forecasting Model Version 4.4.1
A global grid model for the estimation of zenith tropospheric delay considering the variations at different altitudes
Data assimilation for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta): ensemble of 3D ensemble-variational (En-3DEnVar) assimilations
A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest
Simulations of 7Be and 10Be with the GEOS-Chem global model v14.0.2 using state-of-the-art production rates
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors
A mountain-induced moist baroclinic wave test case for the dynamical cores of atmospheric general circulation models
The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2
Challenges of constructing and selecting the "perfect" initial and boundary conditions for the LES model PALM
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 1: Understanding expressiveness of schemes for different regions from the mechanism perspective
Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model
Efficient and Stable Coupling of the SuperdropNet Deep Learning-based Cloud Microphysics (v0.1.0) to the ICON Climate and Weather Model (v2.6.5)
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
Short summary
Short summary
The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
Short summary
Short summary
In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
Short summary
Short summary
Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
Short summary
Short summary
This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
Short summary
Short summary
PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
Short summary
Short summary
Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
Short summary
Short summary
Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
Short summary
Short summary
We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
Short summary
Short summary
The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
Short summary
Short summary
We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
Short summary
Short summary
A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
Short summary
Short summary
The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
Short summary
Short summary
Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
Short summary
Short summary
Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
Short summary
Short summary
Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
Short summary
Short summary
This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
Short summary
Short summary
With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
Short summary
Short summary
GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
Short summary
Short summary
In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
Short summary
Short summary
The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
Short summary
Short summary
Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
Short summary
Short summary
In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
Short summary
Short summary
We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
Short summary
Short summary
The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
Short summary
Short summary
Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
Short summary
Short summary
Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
Short summary
Short summary
A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
Short summary
Short summary
Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
Short summary
Short summary
Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
Short summary
Short summary
In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
Short summary
Short summary
This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
Short summary
Short summary
We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
Short summary
Short summary
Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
Short summary
Short summary
Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
Short summary
Short summary
Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-202, https://doi.org/10.5194/gmd-2023-202, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Global Navigation Satellite Systems provide moisture observations through its densely distributed ground station network. In this research, we assimilated a new type of observation called tropospheric gradient observations, which was never incorporated into a weather model. Here, we have developed a forward operator for gradient observations and performed impact studies. Promising improvements were observed in the humidity fields of the model in the assimilation study.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
Short summary
Short summary
The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
Short summary
Short summary
We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Hang, and Feijuan Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-201, https://doi.org/10.5194/gmd-2023-201, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
In this study, we have developed a model (RF-PWV) to characterize PWV variation with altitude in the study area. The RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
Short summary
Short summary
The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
Short summary
Short summary
In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
Short summary
Short summary
Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
Short summary
Short summary
This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Jelena Radovic, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-197, https://doi.org/10.5194/gmd-2023-197, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
The initial and boundary conditions are of crucial importance for numerical model (e.g., PALM model) validation studies and have a large influence on the model results especially in the case of studying the atmosphere of a real, complex, and densely built urban environments. Our experiments with different driving conditions for the LES model PALM show its strong dependency on them which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, https://doi.org/10.5194/gmd-16-6635-2023, 2023
Short summary
Short summary
Most current studies on planetary boundary layer (PBL) parameterization schemes are relatively fragmented and lack systematic in-depth analysis and discussion. In this study, we comprehensively evaluate the performance capability of the PBL scheme in five typical regions of China in different seasons from the mechanism of the scheme and the effects of PBL schemes on the near-surface meteorological parameters, vertical structures of the PBL, PBL height, and turbulent diffusion.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev., 16, 6531–6552, https://doi.org/10.5194/gmd-16-6531-2023, https://doi.org/10.5194/gmd-16-6531-2023, 2023
Short summary
Short summary
It is important to know how well atmospheric models do in mountains, but there are not very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado River basin against the available data. The model works rather well, but there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we could not do before.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David Greenberg
EGUsphere, https://doi.org/10.5194/egusphere-2023-2047, https://doi.org/10.5194/egusphere-2023-2047, 2023
Short summary
Short summary
In weather and climate models, rain formation is simplified by parameterizations to be computationally efficient. We trained a machine learning algorithm, SuperdropNet, to emulate rain formation in warm clouds based on physically more accurate super-droplet simulations. Here, we validate SuperdropNet coupled to ICON in a warm bubble experiment. We find the coupled simulation runs stable and produces reasonable results, and present a computational benchmark for the coupling software.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
EGUsphere, https://doi.org/10.5194/egusphere-2023-2587, https://doi.org/10.5194/egusphere-2023-2587, 2023
Short summary
Short summary
The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation we find that MESSy’s bias in modelling routinely observed inorganic aerosol mass concentrations is reduced. Furthermore, the representation of fine aerosol pH is particularly improved in the marine boundary layer.
Angel Liduvino Vara-Vela, Christoffer Karoff, Noelia Rojas Benavente, and Janaina P. Nascimento
Geosci. Model Dev., 16, 6413–6431, https://doi.org/10.5194/gmd-16-6413-2023, https://doi.org/10.5194/gmd-16-6413-2023, 2023
Short summary
Short summary
A 1-year simulation of atmospheric CH4 over Europe is performed and evaluated against observations based on the TROPOspheric Monitoring Instrument (TROPOMI). A good general model–observation agreement is found, with discrepancies reaching their minimum and maximum values during the summer peak season and winter months, respectively. A huge and under-explored potential for CH4 inverse modeling using improved TROPOMI XCH4 data sets in large-scale applications is identified.
Cited articles
Abbott, G. and Chapman, M.: Addressing the New Normal: 21st Century Disaster
Management in British Columbia, available at:
https://www2.gov.bc.ca/assets/gov/public-safety-and-emergency-services/emergency-preparedness-response-recovery/embc/bc-flood-and-wildfire-review-addressing
-the-new-normal-21st-century-disaster-management-in-bc-web.pdf (last access: 1 August 2018),
2018.
Achtemeier, G. L., Goodrick, S. A., Liu, Y., Garcia-Menendez, F., Hu, Y., and
Odman, M. T.: Modeling Smoke Plume-Rise and Dispersion from Southern United
States Prescribed Burns with Daysmoke, Atmosphere-Basel, 2, 358–388,
https://doi.org/10.3390/atmos2030358, 2011.
Adams, C., McLinden, C. A., Shephard, M. W., Dickson, N., Dammers, E., Chen, J., Makar, P., Cady-Pereira, K. E., Tam, N., Kharol, S. K., Lamsal, L. N., and Krotkov, N. A.: Satellite-derived emissions of carbon monoxide, ammonia, and nitrogen dioxide from the 2016 Horse River wildfire in the Fort McMurray area, Atmos. Chem. Phys., 19, 2577–2599, https://doi.org/10.5194/acp-19-2577-2019, 2019.
Ahmadov, R., Grell, G., James, E., Freitas, S., Pereira, G., Csiszar, I.,
Tsidulko, M., Pierce, B., McKeen, S., Peckham, S., Alexander, C., Saide, P.
and Benjamin, S.: A high-resolution coupled meteorology-smoke modeling
system HRRR-Smoke to simulate air quality over the CONUS domain in real
time, in: 19th EGU General Assembly, EGU2017, proceedings from the conference
held 23–28 April 2017 in Vienna, Austria, 19, p.10841,
2017.
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.
Akingunola, A., Makar, P. A., Zhang, J., Darlington, A., Li, S.-M., Gordon, M., Moran, M. D., and Zheng, Q.: A chemical transport model study of plume-rise and particle size distribution for the Athabasca oil sands, Atmos. Chem. Phys., 18, 8667–8688, https://doi.org/10.5194/acp-18-8667-2018, 2018.
Anderson, G. K., Sandberg, D. V., and Norheim, R. A.: Fire Emission
Production Simulator (FEPS) User's Guide, available at:
http://www.fs.fed.us/pnw/fera/feps/FEPS_users_guide.pdf (last access: 1 August 2018), 2004.
Anderson, H. E.: Aids to determining fuel models for estimating fire
behavior, available at:
http://www.fs.fed.us/rm/pubs_int/int_gtr122.html (last access: 1 August 2018), 1982.
Anderson, K. and cast of thousands: CFFEPS v2.03, Canadian Forest Service, Natural Resources Canada, Zenodo, https://doi.org/10.5281/zenodo.2579383, 2019.
Anderson, K., Simpson, B., Hall, R. J., Englefield, P., Gartrell, M., and
Metsaranta, J. M.: Integrating forest fuels and land cover data for improved
estimation of fuel consumption and carbon emissions from boreal fires, Int.
J. Wildland Fire, 24, 665, https://doi.org/10.1071/WF14142, 2015.
Anderson, K. R.: Incorporating smoldering into fire growth modelling, in
Third Symposium on Fire and Forest Meteorology, American Meteorological
Society, American Meteorological Society, Boston, MA, USA, available at:
https://cfs.nrcan.gc.ca/publications?id=19950 (last access: 1 August 2018), 2000.
Anderson, K. R., Pankratz, A., and Mooney, C.: A thermodynamic approach to
estimating smoke plume heights, in Ninth Symposium on Fire and Forest
Meteorology, American Meteorological Society, Palm Springs, CA, USA,
available at: https://cfs.nrcan.gc.ca/publications?id=33463 (last access: 1 August 2018),
2011.
Baker, K. R., Woody, M. C., Tonnesen, G. S., Hutzell, W., Pye, H. O. T.,
Beaver, M. R., Pouliot, G., and Pierce, T.: Contribution of regional-scale
fire events to ozone and PM2.5 air quality estimated by photochemical
modeling approaches, Atmos. Environ., 140, 539–554,
https://doi.org/10.1016/J.ATMOSENV.2016.06.032, 2016.
Baker, K. R., Woody, M. C., Valin, L., Szykman, J., Yates, E. L., Iraci, L.
T., Choi, H. D., Soja, A. J., Koplitz, S. N., Zhou, L., Campuzano-Jost, P.,
Jimenez, J. L., and Hair, J. W.: Photochemical model evaluation of 2013
California wild fire air quality impacts using surface, aircraft, and
satellite data, Sci. Total Environ., 637–638, 1137–1149, https://doi.org/10.1016/j.scitotenv.2018.05.048,
2018.
BC Ministry of Environment: BC Health Wildfire Smoke Response Coordination
Guideline, available at:
http://www.bccdc.ca/resource-gallery/Documents/BC Health Wildfire Smoke Response Coordination Guideline 2017.pdf (last access: 1 August 2018), 2017.
Beaudoin, A., Bernier, P. Y., Villemaire, P., Guindon, L., and Guo, X. J.:
Tracking forest attributes across Canada between 2001 and 2011 using a k
nearest neighbors mapping approach applied to MODIS imagery, Can. J. Forest
Res., 48, 85–93, https://doi.org/10.1139/cjfr-2017-0184, 2018.
Block, W. M., Conner, L. M., Brewer, P. A., Ford, P., Haufler, J., Litt, A.,
Masters, R. E., Mitchell, L. R., and Park, J.: Effects of prescribed fire on
wildlife and wildlife habitat in selected ecosystems of North America,
Bethesda, Maryland, USA, available at:
https://www.fs.usda.gov/treesearch/pubs/all/53210 (last access: 1 August 2018), 2016.
Briggs, G. A.: A Plume Rise Model Compared with Observations, J. Air Pollut.
Control Assoc., 15, 433–438, https://doi.org/10.1080/00022470.1965.10468404, 1965.
Byram, G. M.: Combustion of forest fuels, in: Forest fire: control and use,
edited by: Davis, K. P., McGraw-Hill, New York, NY, USA, 61–89,
available at: https://www.frames.gov/catalog/9652 (last access: 1 August 2018), 1959.
Calgary Airsheds Council: Simplified Wildfire Smoke Guide, available at: http://craz.ca/simplified-wildfire-smoke-guide (last access: 1 August 2018), 2017.
Cascio, W. E.: Wildland fire smoke and human health, Sci. Total Environ.,
624, 586–595, https://doi.org/10.1016/J.SCITOTENV.2017.12.086, 2018.
Charron, M., Polavarapu, S., Buehner, M., Vaillancourt, P. A., Charette, C.,
Roch, M., Morneau, J., Garand, L., Aparicio, J. M., MacPherson, S.,
Pellerin, S., St-James, J., Heilliette, S., Charron, M., Polavarapu, S.,
Buehner, M., Vaillancourt, P. A., Charette, C., Roch, M., Morneau, J.,
Garand, L., Aparicio, J. M., MacPherson, S., Pellerin, S., St-James, J., and
Heilliette, S.: The Stratospheric Extension of the Canadian Global
Deterministic Medium-Range Weather Forecasting System and Its Impact on
Tropospheric Forecasts, Mon. Weather Rev., 140, 1924–1944,
https://doi.org/10.1175/MWR-D-11-00097.1, 2012.
Chen, J. and GEM-MACH development team: GEM-MACH atmospheric chemistry module for the GEM numerical weather prediction model, Environment and Climate Change Canada, Zenodo, https://doi.org/10.5281/zenodo.2579386, 2019.
Commission for Environmental Cooperation: 2010 Land Cover of North America
at 30 meters, North Am. Environ. Atlas, available at:
http://www.cec.org/tools-and-resources/north-american-environmental-atlas (last access: 1 August 2018),
2017.
Côté, J., Gravel, S., Méthot, A., Patoine, A., Roch, M.,
Staniforth, A., Côté, J., Gravel, S., Méthot, A., Patoine, A.,
Roch, M., and Staniforth, A.: The Operational CMC–MRB Global Environmental
Multiscale (GEM) Model. Part I: Design Considerations and Formulation, Mon.
Weather Rev., 126, 1373–1395, https://doi.org/10.1175/1520-0493(1998)126<1373:TOCMGE>2.0.CO;2, 1998.
de Groot, W. J., Landry, R., Kurz, W. A., Anderson, K. R., Englefield, P.,
Fraser, R. H., Hall, R. J., Banfield, E., Raymond, D. A., Decker, V.,
Lynham, T. J., and Pritchard, J. M.: Estimating direct carbon emissions from
Canadian wildland fires, Int. J. Wildland Fire, 16, 593,
https://doi.org/10.1071/WF06150, 2007.
de Groot, W. J., Pritchard, J. M., and Lynham, T. J.: Forest floor fuel
consumption and carbon emissions in Canadian boreal forest fires, Can. J.
Forest Res., 39, 367–382, https://doi.org/10.1139/X08-192, 2009.
Englefield, P., Lee, B. S., Fraser, R. H., Landry, R., Hall, R. J., Lynham,
T. J., Cihlar, J., Li, Z., Jin, J.-Z., and Ahern, F. J.: Applying geographic
information systems and remote sensing to forest fire monitoring, mapping
and modelling in Canada, in: 22nd Tall Timbers Fire Ecology Conference: Fire
in Temperate, Boreal, and Montane Ecosystems Ecology Conference: Fire in
Temperate, Boreal, and Montane Ecosystems, edited by: Engstrom, R. T.,
Galley, K. E. M., and de Groot, W. J., Tall Timbers Research Station,
Tallahassee, FL, USA, 240–245, available at:
https://cfs.nrcan.gc.ca/publications?id=25111&lang=en_CA (last access: 1 August 2018), 2004.
Finlay, S. E., Moffat, A., Gazzard, R., Baker, D., and Murray, V.: Health
Impacts of Wildfires, PLoS Curr., https://doi.org/10.1371/4f959951cce2c, 2012.
Fish, J. A., Peters, M. D. J., Ramsey, I., Sharplin, G., Corsini, N., and
Eckert, M.: Effectiveness of public health messaging and communication
channels during smoke events: A rapid systematic review, J. Environ.
Manage., 193, 247–256, https://doi.org/10.1016/J.JENVMAN.2017.02.012, 2017.
Forestry Canada Fire Danger Group: Development and structure of the Canadian
Forest Fire Behavior Prediction System, available at:
https://cfs.nrcan.gc.ca/publications?id=10068 (last access: 1 August 2018), 1992.
Fraser, A., Dastoor, A., and Ryjkov, A.: How important is biomass burning in Canada to mercury contamination?, Atmos. Chem. Phys., 18, 7263–7286, https://doi.org/10.5194/acp-18-7263-2018, 2018.
Freitas, S. R., Longo, K. M., Chatfield, R., Latham, D., Silva Dias, M. A. F., Andreae, M. O., Prins, E., Santos, J. C., Gielow, R., and Carvalho Jr., J. A.: Including the sub-grid scale plume rise of vegetation fires in low resolution atmospheric transport models, Atmos. Chem. Phys., 7, 3385–3398, https://doi.org/10.5194/acp-7-3385-2007, 2007.
Fung, C. S., Misra, P. K., Bloxam, R., and Wong, S.: A numerical experiment
on the relative importance of H2O2 O3 in aqueous conversion of SO2 to ,
Atmos. Environ., 25, 411–423,
https://doi.org/10.1016/0960-1686(91)90312-U, 1991.
Garcia-Menendez, F., Hu, Y., and Odman, M. T.: Simulating smoke transport
from wildland fires with a regional-scale air quality model: sensitivity to
spatiotemporal allocation of fire emissions, Sci. Total Environ., 493,
544–553, https://doi.org/10.1016/j.scitotenv.2014.05.108, 2014.
Gong, S. L., Barrie, L. A., Blanchet, J. -P., Salzen, K. von, Lohmann, U.,
Lesins, G., Spacek, L., Zhang, L. M., Girard, E., Lin, H., Leaitch, R.,
Leighton, H., Chylek, P., and Huang, P.: Canadian Aerosol Module: A
size-segregated simulation of atmospheric aerosol processes for climate and
air quality models 1. Module development, J. Geophys. Res., 108, 4007,
https://doi.org/10.1029/2001JD002002, 2003.
Gong, W., Makar, P. A., Zhang, J., Milbrandt, J., Gravel, S., Hayden, K. L.,
Macdonald, A. M., and Leaitch, W. R.: Modelling aerosol–cloud–meteorology
interaction: A case study with a fully coupled air quality model (GEM-MACH),
Atmos. Environ., 115, 695–715, https://doi.org/10.1016/j.atmosenv.2015.05.062, 2015.
Hatch, L. E., Yokelson, R. J., Stockwell, C. E., Veres, P. R., Simpson, I. J., Blake, D. R., Orlando, J. J., and Barsanti, K. C.: Multi-instrument comparison and compilation of non-methane organic gas emissions from biomass burning and implications for smoke-derived secondary organic aerosol precursors, Atmos. Chem. Phys., 17, 1471–1489, https://doi.org/10.5194/acp-17-1471-2017, 2017.
Herron-Thorpe, F. L., Mount, G. H., Emmons, L. K., Lamb, B. K., Jaffe, D. A., Wigder, N. L., Chung, S. H., Zhang, R., Woelfle, M. D., and Vaughan, J. K.: Air quality simulations of wildfires in the Pacific Northwest evaluated with surface and satellite observations during the summers of 2007 and 2008, Atmos. Chem. Phys., 14, 12533–12551, https://doi.org/10.5194/acp-14-12533-2014, 2014.
Huang, R., Zhang, X., Chan, D., Kondragunta, S., Russell, A. G., and Odman,
M. T.: Burned Area Comparisons Between Prescribed Burning Permits in
Southeastern United States and Two Satellite-Derived Products, J. Geophys.
Res.-Atmos., 123, 4746–4757, https://doi.org/10.1029/2017JD028217, 2018.
Huang, X. and Rein, G.: Upward-and-downward spread of smoldering peat fire,
P. Combust. Inst., 37, 4025–4033, https://doi.org/10.1016/J.PROCI.2018.05.125,
2019.
Jaffe, D.: Long-range transport of Siberian biomass burning emissions and
impact on surface ozone in western North America, Geophys. Res. Lett.,
31, L16106, https://doi.org/10.1029/2004GL020093, 2004.
Jaffe, D. A. and Wigder, N. L.: Ozone production from wildfires: A critical
review, Atmos. Environ., 51, 1–10, https://doi.org/10.1016/j.atmosenv.2011.11.063,
2012.
Johnston, F. H., Henderson, S. B., Chen, Y., Randerson, J. T., Marlier, M.,
DeFries, R. S., Kinney, P., Bowman, D. M. J. S., and Brauer, M.: Estimated
Global Mortality Attributable to Smoke from Landscape Fires, Environ. Health
Persp., 120, 695–701, https://doi.org/10.1289/ehp.1104422, 2012.
Jolliffe, I. T. and Stephenson, D. B.: Forecast verification?: a
practitioner's guide in atmospheric science, John Wiley & Sons, available at:
https://www.wiley.com/en-ca/Forecast+Verification
%3A
+A+Practitioner's+Guide+in+Atmospheric+Science
%2C
+2nd+Edition-p-9780470660713 (last access: 1 August 2018),
2012.
Knorr, W., Dentener, F., Lamarque, J.-F., Jiang, L., and Arneth, A.: Wildfire air pollution hazard during the 21st century, Atmos. Chem. Phys., 17, 9223–9236, https://doi.org/10.5194/acp-17-9223-2017, 2017.
Kochanski, A. K., Jenkins, M. A., Yedinak, K., Mandel, J., Beezley, J. D.,
and Lamb, B.: Toward an integrated system for fire, smoke, and air quality
simulations, Int. J. Wildl. Fire, 25, 534, https://doi.org/10.1071/WF14074, 2014.
Landis, M. S., Edgerton, E. S., White, E. M., Wentworth, G. R., Sullivan, A.
P., and Dillner, A. M.: The impact of the 2016 Fort McMurray Horse River
Wildfire on ambient air pollution levels in the Athabasca Oil Sands Region,
Alberta, Canada, Sci. Total Environ., 618, 1665–1676,
https://doi.org/10.1016/J.SCITOTENV.2017.10.008, 2018.
Larkin, N. K., O'Neill, S. M., Solomon, R., Raffuse, S., Strand, T.,
Sullivan, D. C., Krull, C., Rorig, M., Peterson, J. L., and Ferguson, S. A.:
The BlueSky smoke modeling framework, Int. J. Wildland Fire, 18, 906–920,
https://doi.org/10.1071/WF07086, 2009.
Larkin, N. K., Raffuse, S. M., and Strand, T. M.: Wildland fire emissions,
carbon, and climate: U.S. emissions inventories, Forest Ecol. Manag., 317,
61–69, https://doi.org/10.1016/J.FORECO.2013.09.012, 2014.
Larsen, A. E., Reich, B. J., Ruminski, M., and Rappold, A. G.: Impacts of
fire smoke plumes on regional air quality, 2006–2013, J. Expo. Sci.
Env. Epid., 28, 319–327, https://doi.org/10.1038/s41370-017-0013-x, 2018.
Lawson, B. D. and Armitage, O. B.: Weather Guide for the Canadian Forest
Fire Danger Rating System, available at:
http://cfs.nrcan.gc.ca/publications?id=29152 (last access: 1 August 2018), 2008.
Lawson, B. D., Armitage, O. B., and Hoskins, W. D.: Diurnal variation in the
fine fuel moisture code: tables and computer source code, Victoria, BC,
available at: https://cfs.nrcan.gc.ca/publications?id=4244 (last access: 1 August 2018),
1996.
Lee, B., Alexander, M., Hawkes, B., Lynham, T., Stocks, B., and
Englefield, P.: Information systems in support of wildland fire management
decision making in Canada, Comput. Electron. Agr., 37, 185–198,
https://doi.org/10.1016/S0168-1699(02)00120-5, 2002.
Lee, P., McQueen, J., Stajner, I., Huang, J., Pan, L., Tong, D., Kim, H.,
Tang, Y., Kondragunta, S., Ruminski, M., Lu, S., Rogers, E., Saylor, R.,
Shafran, P., Huang, H.-C., Gorline, J., Upadhayay, S., Artz, R., Lee, P.,
McQueen, J., Stajner, I., Huang, J., Pan, L., Tong, D., Kim, H., Tang, Y.,
Kondragunta, S., Ruminski, M., Lu, S., Rogers, E., Saylor, R., Shafran, P.,
Huang, H.-C., Gorline, J., Upadhayay, S., and Artz, R.: NAQFC Developmental
Forecast Guidance for Fine Particulate Matter (PM2.5), Weather Forecast.,
32, 343–360, https://doi.org/10.1175/WAF-D-15-0163.1, 2017.
Liu, J. C., Pereira, G., Uhl, S. A., Bravo, M. A., and Bell, M. L.: A
systematic review of the physical health impacts from non-occupational
exposure to wildfire smoke, Environ. Res., 136, 120–132,
https://doi.org/10.1016/j.envres.2014.10.015, 2014.
Liu, X., Huey, L. G., Yokelson, R. J., Selimovic, V., Simpson, I. J.,
Müller, M., Jimenez, J. L., Campuzano-Jost, P., Beyersdorf, A. J.,
Blake, D. R., Butterfield, Z., Choi, Y., Crounse, J. D., Day, D. A., Diskin,
G. S., Dubey, M. K., Fortner, E., Hanisco, T. F., Hu, W., King, L. E.,
Kleinman, L., Meinardi, S., Mikoviny, T., Onasch, T. B., Palm, B. B.,
Peischl, J., Pollack, I. B., Ryerson, T. B., Sachse, G. W., Sedlacek, A. J.,
Shilling, J. E., Springston, S., St. Clair, J. M., Tanner, D. J., Teng, A.
P., Wennberg, P. O., Wisthaler, A., and Wolfe, G. M.: Airborne measurements
of western U.S. wildfire emissions: Comparison with prescribed burning and
air quality implications, J. Geophys. Res.-Atmos., 122, 6108–6129,
https://doi.org/10.1002/2016JD026315, 2017.
Liu, Y., Goodrick, S. L., and Stanturf, J. A.: Future U.S. wildfire potential
trends projected using a dynamically downscaled climate change scenario,
Forest Ecol. Manag., 294, 120–135, https://doi.org/10.1016/j.foreco.2012.06.049, 2013.
Lurmann, F. W. and Stockwell, W. R.: Intercomparison of the ADOM and RADM
gas-phase chemical mechanisms, Electrical Power Research Institute Topical
Report, 1989.
Makar, P., Bouchet, V., and Nenes, A.: Inorganic chemistry calculations
using HETV – a vectorized solver for the – – system based on
the ISORROPIA algorithms, Atmos. Environ., 37, 2279–2294,
https://doi.org/10.1016/S1352-2310(03)00074-8, 2003.
Mallia, D., Kochanski, A., Urbanski, S., and Lin, J.: Optimizing Smoke and
Plume Rise Modeling Approaches at Local Scales, Atmosphere-Basel, 9,
166, https://doi.org/10.3390/atmos9050166, 2018.
Mandel, J., Amram, S., Beezley, J. D., Kelman, G., Kochanski, A. K., Kondratenko, V. Y., Lynn, B. H., Regev, B., and Vejmelka, M.: Recent advances and applications of WRF–SFIRE, Nat. Hazards Earth Syst. Sci., 14, 2829–2845, https://doi.org/10.5194/nhess-14-2829-2014, 2014.
Matthias, V., Arndt, J. A., Aulinger, A., Bieser, J., Denier van der Gon,
H., Kranenburg, R., Kuenen, J., Neumann, D., Pouliot, G., and Quante, M.:
Modeling emissions for three-dimensional atmospheric chemistry transport
models, J. Air Waste Manage., 68, 763–800,
https://doi.org/10.1080/10962247.2018.1424057, 2018.
Mebust, A. K., Russell, A. R., Hudman, R. C., Valin, L. C., and Cohen, R. C.: Characterization of wildfire NOx emissions using MODIS fire radiative power and OMI tropospheric NO2 columns, Atmos. Chem. Phys., 11, 5839–5851, https://doi.org/10.5194/acp-11-5839-2011, 2011.
MNP LLP: A Review of the 2016 Horse River Wildfire, available at:
https://www.alberta.ca/assets/documents/Wildfire-MNP-Report.pdf (last access: 1 August 2018), 2017.
Moran, M. D., Pavlovic, R., and Anselmo, D.: Regional Air Quality
Deterministic Prediction System (RAQDPS): Update from version 019 to version
020, Montreal, available at:
http://collaboration.cmc.ec.gc.ca/cmc/CMOI/product_guide/docs/tech_notes/technote_raqdps-v20_20180918_e.pdf, last access: 1 December 2018.
Munoz-Alpizar, R., Pavlovic, R., Moran, M., Chen, J., Gravel, S., Henderson,
S., Ménard, S., Racine, J., Duhamel, A., Gilbert, S., Beaulieu, P.-A.,
Landry, H., Davignon, D., Cousineau, S., and Bouchet, V.: Multi-Year
(2013–2016) PM2.5 Wildfire Pollution Exposure over North America as
Determined from Operational Air Quality Forecasts, Atmosphere-Basel,
8, 179, https://doi.org/10.3390/atmos8090179, 2017.
National Interagency Fire Center: National Interagency Fire Center,
available at: https://www.nifc.gov/fireInfo/fireInfo_statistics.html, last access: 12 July 2018.
Natural Resources Canada: The State of Canada's Forests, Ottawa, ON,
available at: http://cfs.nrcan.gc.ca/publications?id=39336 (last access: 1 February 2019),
2018.
Ottmar, R. D.: Wildland fire emissions, carbon, and climate: Modeling fuel
consumption, Forest Ecol. Manag., 317, 41–50,
https://doi.org/10.1016/j.foreco.2013.06.010, 2013.
Paugam, R., Wooster, M., Freitas, S., and Val Martin, M.: A review of approaches to estimate wildfire plume injection height within large-scale atmospheric chemical transport models, Atmos. Chem. Phys., 16, 907–925, https://doi.org/10.5194/acp-16-907-2016, 2016.
Pavlovic, R., Chen, J., Davignon, D., Moran, M., Beaulieu, P.-A., Landry,
H., Sassi, M., Gilbert, S., Munoz-Alpizar, R., Anderson, K., Englefield, P.,
M. O'Neill, S., K. Larkin, N., Racine, J., Cousineau, S., Ménard, S.,
Malo, A., Gauthier, J.-P., Ek, N., and Bouchet, V.: FireWork – A Canadian
Operational Air Quality Forecast Model With Near-Real-Time Biomass Burning
Emissions, Can. Wildl. Fire Smoke Smoke Newsl., Fall, 18–29, 2016a.
Pavlovic, R., Chen, J., Anderson, K., Moran, M. D., Beaulieu, P.-A.,
Davignon, D., and Cousineau, S.: The FireWork Air Quality Forecast System
with Near-Real-Time Biomass Burning Emissions: Recent Developments and
Evaluation of Performance for the 2015 North American Wildfire Season, J.
Air Waste Manage., 66, 819–841,
https://doi.org/10.1080/10962247.2016.1158214, 2016b.
Pouliot, G., Rao, V., McCarty, J. L., and Soja, A.: Development of the crop
residue and rangeland burning in the 2014 National Emissions Inventory using
information from multiple sources, J. Air Waste Manage., 67,
613–622, https://doi.org/10.1080/10962247.2016.1268982, 2017.
Prichard, S. J., Ottmar, R. D., and Anderson, G. K.: Consume 3.0 User's
Guide, Seattle, WA, available at:
https://www.frames.gov/catalog/1260 (last access: 1 August 2018), 2006.
Quayle, B., Lannom, K., Finco, M., Norton, J., and Warnick, R.: Monitoring
wildland fire activity on a national-scale with MODIS imagery, in: 2nd
International Wildland Fire Ecology and Fire Management Congress and 5th
Symposium on Fire and Forest Meteorology, American Meteorological Society,
Boston, MA, USA, 2003.
Rappold, A. G., Reyes, J., Pouliot, G., Cascio, W. E., and Diaz-Sanchez, D.:
Community Vulnerability to Health Impacts of Wildland Fire Smoke Exposure,
Environ. Sci. Technol., 51, 6674–6682, https://doi.org/10.1021/acs.est.6b06200,
2017.
Reid, C. E., Brauer, M., Johnston, F. H., Jerrett, M., Balmes, J. R., and
Elliott, C. T.: Critical Review of Health Impacts of Wildfire Smoke
Exposure, Environ. Health Persp., 124, 1334–1343, https://doi.org/10.1289/ehp.1409277, 2016.
Rio, C., Hourdin, F., and Chédin, A.: Numerical simulation of tropospheric injection of biomass burning products by pyro-thermal plumes, Atmos. Chem. Phys., 10, 3463–3478, https://doi.org/10.5194/acp-10-3463-2010, 2010.
Schigas, R. and Stull, R.: BlueSky Canada Part 3 – BlueSky Canada Wildfire
Smoke: Status at UBC, Can. Smoke Newsl., 29–32, available at:
https://www.canadawildfire.org/older-issues (last access: 1 September 2018), 2013.
Simon, H., Beck, L., Bhave, P. V., Divita, F., Hsu, Y., Luecken, D., Mobley,
J. D., Pouliot, G. A., Reff, A., Sarwar, G., and Strum, M.: The development
and uses of EPA's SPECIATE database, Atmos. Pollut. Res., 1, 196–206,
https://doi.org/10.5094/APR.2010.026, 2010.
Sofiev, M., Ermakova, T., and Vankevich, R.: Evaluation of the smoke-injection height from wild-land fires using remote-sensing data, Atmos. Chem. Phys., 12, 1995–2006, https://doi.org/10.5194/acp-12-1995-2012, 2012.
Stajner, I., Davidson, P., Byun, D., McQueen, J., Draxler, R., Dickerson, P.,
and Meagher, J.: US National Air Quality Forecast Capability: Expanding
Coverage to Include Particulate Matter, in: Air Pollution Modeling and its
Application XXI. NATO Science for Peace and Security Series C: Environmental
Security, Springer, Dordrecht, 379–384, 2011.
Stieb, D. M., Burnett, R. T., Smith-Doiron, M., Brion, O., Shin, H. H., and
Economou, V.: A New Multipollutant, No-Threshold Air Quality Health Index
Based on Short-Term Associations Observed in Daily Time-Series Analyses, J.
Air Waste Manage., 58, 435–450, https://doi.org/10.3155/1047-3289.58.3.435,
2008.
Stroud, C. A., Makar, P. A., Moran, M. D., Gong, W., Gong, S., Zhang, J., Hayden, K., Mihele, C., Brook, J. R., Abbatt, J. P. D., and Slowik, J. G.: Impact of model grid spacing on regional- and urban- scale air quality predictions of organic aerosol, Atmos. Chem. Phys., 11, 3107–3118, https://doi.org/10.5194/acp-11-3107-2011, 2011.
Struzik, E.: Firestorm?: how wildfire will shape our future, Edward
Struzik, Island Press, Washington, DC, 2017.
Teakles, A. D., So, R., Ainslie, B., Nissen, R., Schiller, C., Vingarzan, R., McKendry, I., Macdonald, A. M., Jaffe, D. A., Bertram, A. K., Strawbridge, K. B., Leaitch, W. R., Hanna, S., Toom, D., Baik, J., and Huang, L.: Impacts of the July 2012 Siberian fire plume on air quality in the Pacific Northwest, Atmos. Chem. Phys., 17, 2593–2611, https://doi.org/10.5194/acp-17-2593-2017, 2017.
Urbanski, S.: Wildland fire emissions, carbon, and climate: Emission
factors, Forest Ecol. Manag., 317, 51–60, https://doi.org/10.1016/J.FORECO.2013.05.045,
2014.
U.S. Geological Survey: Earth Resources Observation and Science Center: 13
Anderson Fire Behavior Fuel Models (FBFM13), Wildl. Fire Sci., available at: https://www.landfire.gov/fbfm13.php (last access: 1 December 2018), 2016.
Valerino, M. J., Johnson, J. J., Izumi, J., Orozco, D., Hoff, R. M.,
Delgado, R., and Hennigan, C. J.: Sources and composition of PM2.5 in
the Colorado Front Range during the DISCOVER-AQ study, J. Geophys. Res.-Atmos., 122, 566–582, https://doi.org/10.1002/2016JD025830, 2017.
Val Martin, M., Kahn, R., and Tosca, M.: A Global Analysis of Wildfire Smoke
Injection Heights Derived from Space-Based Multi-Angle Imaging, Remote
Sens., 10, 1609, https://doi.org/10.3390/rs10101609, 2018.
Van Wagner, C. E.: The Development and Structure of the Canadian Forest Fire
Weather Index System, Ottawa, ON, available at:
https://cfs.nrcan.gc.ca/publications?id=19927 (last access: 1 August 2018), 1987.
Wentworth, G. R., Aklilu, Y., Landis, M. S., and Hsu, Y.-M.: Impacts of a
large boreal wildfire on ground level atmospheric concentrations of PAHs,
VOCs and ozone, Atmos. Environ., 178, 19–30,
https://doi.org/10.1016/J.ATMOSENV.2018.01.013, 2018.
Western Regional Air Partnership: 2002 Fire Emission Inventory for the WRAP
Region- Phase II, available at:
https://www.wrapair.org//forums/fejf/tasks/FEJFtask7PhaseII.html (last access: 1 August 2018), 2005.
Wotton, B. M., Flannigan, M. D., and Marshall, G. A.: Potential climate
change impacts on fire intensity and key wildfire suppression thresholds in
Canada, Environ. Res. Lett., 12, 095003, https://doi.org/10.1088/1748-9326/aa7e6e,
2017.
Yao, J., Raffuse, S. M., Brauer, M., Williamson, G. J., Bowman, D. M. J. S.,
Johnston, F. H., and Henderson, S. B.: Predicting the minimum height of
forest fire smoke within the atmosphere using machine learning and data from
the CALIPSO satellite, Remote Sens. Environ., 206, 98–106,
https://doi.org/10.1016/J.RSE.2017.12.027, 2018.
Yuchi, W., Yao, J., McLean, K. E., Stull, R., Pavlovic, R., Davignon, D.,
Moran, M. D., and Henderson, S. B.: Blending forest fire smoke forecasts with
observed data can improve their utility for public health applications,
Atmos. Environ., 145, 308–317, https://doi.org/10.1016/J.ATMOSENV.2016.09.049, 2016.
Yukon Health and Social Services: Yukon wildfire smoke response guidelines
for protecting public health, available at:
http://www.hss.gov.yk.ca/pdf/wildfiresmokeresponseguidelines.pdf (last access: 1 August 2018), 2017.
Zhang, J., Moran, M. D., Zheng, Q., Makar, P. A., Baratzadeh, P., Marson, G., Liu, P., and Li, S.-M.: Emissions preparation and analysis for multiscale air quality modeling over the Athabasca Oil Sands Region of Alberta, Canada, Atmos. Chem. Phys., 18, 10459–10481, https://doi.org/10.5194/acp-18-10459-2018, 2018.
Zhang, X., Kondragunta, S., and Roy, D. P.: Interannual variation in biomass
burning and fire seasonality derived from geostationary satellite data
across the contiguous United States from 1995 to 2011, J. Geophys. Res.-Biogeo., 119, 1147–1162, https://doi.org/10.1002/2013JG002518, 2014.
Zhou, L., Baker, K. R., Napelenok, S. L., Pouliot, G., Elleman, R., O'Neill,
S. M., Urbanski, S. P., and Wong, D. C.: Modeling crop residue burning
experiments to evaluate smoke emissions and plume transport, Sci. Total
Environ., 627, 523–533, https://doi.org/10.1016/j.scitotenv.2018.01.237, 2018.
Short summary
Emissions from wildland fires can cause significant impacts on regional air quality. We introduce the Canadian Forest Fire Emissions Prediction System and demonstrate its integration with Canada's FireWork operational air quality forecast system with biomass burning emissions. The coupled system shows improved skill in providing short-term, 48 h forecasts of surface air pollutant concentrations (PM2.5, O3, and NO2) from the impacts of regional wildland fires across the North American domain.
Emissions from wildland fires can cause significant impacts on regional air quality. We...