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
Revised manuscript 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
Revised manuscript 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
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
RoadSurf 1.1: open-source road weather model library
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
A general comprehensive evaluation method for cross-scale precipitation forecasts
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands
Balloon drift estimation and improved position estimates for radiosondes
Emission ensemble approach to improve the development of multi-scale emission inventories
What is the relative impact of nudging and online coupling on meteorological variables, pollutant concentrations and aerosol optical properties?
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations
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
TAMS: A Tracking, Classifying, and Variable-Assigning Algorithm for Mesoscale Convective Systems in Simulated and Satellite-Derived Datasets
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
Short summary
Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary
Short summary
Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
Short summary
Short summary
RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
Short summary
Short summary
The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
Short summary
Short summary
We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
Short summary
Short summary
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
Short summary
Short summary
By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
Short summary
Short summary
We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
Short summary
Short summary
This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
Short summary
Short summary
Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
Short summary
Short summary
The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
Short summary
Short summary
The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
Short summary
Short summary
There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
Short summary
Short summary
This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
Short summary
Short summary
This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
Short summary
Short summary
We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
Short summary
Short summary
This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
Short summary
Short summary
Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
Short summary
Short summary
In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
Short summary
Short summary
We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
Short summary
Short summary
For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
Short summary
Short summary
Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
Short summary
Short summary
This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
Short summary
Short summary
This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
Short summary
Short summary
An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
Short summary
Short summary
This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
Short summary
Short summary
Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Short summary
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary
Short summary
This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
Short summary
Short summary
Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
Short summary
Short summary
Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
Short summary
Short summary
Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Short summary
Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Short summary
An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
Short summary
Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Short summary
In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary
Short summary
A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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 reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
Short summary
Short summary
In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. 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.
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.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
EGUsphere, https://doi.org/10.22541/essoar.169903618.82717612/v2, https://doi.org/10.22541/essoar.169903618.82717612/v2, 2024
Short summary
Short summary
Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate of the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
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.
Kelly M. Núñez Ocasio and Zachary L. Moon
EGUsphere, https://doi.org/10.5194/egusphere-2024-259, https://doi.org/10.5194/egusphere-2024-259, 2024
Short summary
Short summary
TAMS is an open-source mesoscale convective system tracking and classifying Python-based package that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
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.
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...