Articles | Volume 15, issue 14
https://doi.org/10.5194/gmd-15-5807-2022
© Author(s) 2022. 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-15-5807-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A description of the first open-source community release of MISTRA-v9.0: a 0D/1D atmospheric boundary layer chemistry model
Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences, University of East Anglia, NR4 7TJ, Norwich, UK
now at: EDYTEM, Université Savoie Mont-Blanc, CNRS, 73000 Chambéry, France
Jan Kaiser
Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences, University of East Anglia, NR4 7TJ, Norwich, UK
Max Thomas
Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences, University of East Anglia, NR4 7TJ, Norwich, UK
now at: the Department of Physics, University of Otago, P.O. Box 56, Dunedin 9054, New Zealand
Andreas Bott
Institute of Geosciences, University of Bonn, Bonn, Germany
Roland von Glasow
Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences, University of East Anglia, NR4 7TJ, Norwich, UK
deceased, 6 September 2015
Related authors
Matan Ben-Asher, Antoine Chabas, Jean-Yves Josnin, Josué Bock, Emmanuel Malet, Amaël Poulain, Yves Perrette, and Florence Magnin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2450, https://doi.org/10.5194/egusphere-2025-2450, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
We studied how water moves through fractured rock walls in a high mountain area in the Alps. Using sensors and tracers over two years, in a high-altitude site, we tracked where the water came from and when it flowed. Most of it came from melting snow, but some came from rain and older ice. The results show that heat and water flow can speed up the melting of frozen ground, which may affect mountain stability. This helps us understand how climate change influences these fragile environments.
Feras Abdulsamad, Josué Bock, Florence Magnin, Emmanuel Malet, André Revil, Matan Ben-Asher, Jessy Richard, Pierre-Allain Duvillard, Marios Karaoulis, Thomas Condom, Ludovic Ravanel, and Philip Deline
EGUsphere, https://doi.org/10.5194/egusphere-2025-637, https://doi.org/10.5194/egusphere-2025-637, 2025
Short summary
Short summary
Permafrost dynamics at Aiguille du Midi in the French Alps was investigated using Automated Electrical Resistivity Tomography (A-ERT) during four years. A-ERT reveals seasonal and multi-year permafrost changes. Temperatures estimated using resistivity measurements provide a good agreement with measured temperature in borehole in frozen zone. Variations in active layer thickness across different faces were observed, along with a slight decrease in permafrost resistivity suggesting warming.
Matan Ben-Asher, Florence Magnin, Sebastian Westermann, Josué Bock, Emmanuel Malet, Johan Berthet, Ludovic Ravanel, and Philip Deline
Earth Surf. Dynam., 11, 899–915, https://doi.org/10.5194/esurf-11-899-2023, https://doi.org/10.5194/esurf-11-899-2023, 2023
Short summary
Short summary
Quantitative knowledge of water availability on high mountain rock slopes is very limited. We use a numerical model and field measurements to estimate the water balance at a steep rock wall site. We show that snowmelt is the main source of water at elevations >3600 m and that snowpack hydrology and sublimation are key factors. The new information presented here can be used to improve the understanding of thermal, hydrogeological, and mechanical processes on steep mountain rock slopes.
Josué Bock, Martine Michou, Pierre Nabat, Manabu Abe, Jane P. Mulcahy, Dirk J. L. Olivié, Jörg Schwinger, Parvadha Suntharalingam, Jerry Tjiputra, Marco van Hulten, Michio Watanabe, Andrew Yool, and Roland Séférian
Biogeosciences, 18, 3823–3860, https://doi.org/10.5194/bg-18-3823-2021, https://doi.org/10.5194/bg-18-3823-2021, 2021
Short summary
Short summary
In this study we analyse surface ocean dimethylsulfide (DMS) concentration and flux to the atmosphere from four CMIP6 Earth system models over the historical and ssp585 simulations.
Our analysis of contemporary (1980–2009) climatologies shows that models better reproduce observations in mid to high latitudes. The models disagree on the sign of the trend of the global DMS flux from 1980 onwards. The models agree on a positive trend of DMS over polar latitudes following sea-ice retreat dynamics.
Matan Ben-Asher, Antoine Chabas, Jean-Yves Josnin, Josué Bock, Emmanuel Malet, Amaël Poulain, Yves Perrette, and Florence Magnin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2450, https://doi.org/10.5194/egusphere-2025-2450, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
We studied how water moves through fractured rock walls in a high mountain area in the Alps. Using sensors and tracers over two years, in a high-altitude site, we tracked where the water came from and when it flowed. Most of it came from melting snow, but some came from rain and older ice. The results show that heat and water flow can speed up the melting of frozen ground, which may affect mountain stability. This helps us understand how climate change influences these fragile environments.
Feras Abdulsamad, Josué Bock, Florence Magnin, Emmanuel Malet, André Revil, Matan Ben-Asher, Jessy Richard, Pierre-Allain Duvillard, Marios Karaoulis, Thomas Condom, Ludovic Ravanel, and Philip Deline
EGUsphere, https://doi.org/10.5194/egusphere-2025-637, https://doi.org/10.5194/egusphere-2025-637, 2025
Short summary
Short summary
Permafrost dynamics at Aiguille du Midi in the French Alps was investigated using Automated Electrical Resistivity Tomography (A-ERT) during four years. A-ERT reveals seasonal and multi-year permafrost changes. Temperatures estimated using resistivity measurements provide a good agreement with measured temperature in borehole in frozen zone. Variations in active layer thickness across different faces were observed, along with a slight decrease in permafrost resistivity suggesting warming.
Charlotte A. J. Williams, Tom Hull, Jan Kaiser, Claire Mahaffey, Naomi Greenwood, Matthew Toberman, and Matthew R. Palmer
Biogeosciences, 21, 1961–1971, https://doi.org/10.5194/bg-21-1961-2024, https://doi.org/10.5194/bg-21-1961-2024, 2024
Short summary
Short summary
Oxygen (O2) is a key indicator of ocean health. The risk of O2 loss in the productive coastal/continental slope regions is increasing. Autonomous underwater vehicles equipped with O2 optodes provide lots of data but have problems resolving strong vertical O2 changes. Here we show how to overcome this and calculate how much O2 is supplied to the low-O2 bottom waters via mixing. Bursts in mixing supply nearly all of the O2 to bottom waters in autumn, stopping them reaching ecologically low levels.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
Short summary
Short summary
Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Matan Ben-Asher, Florence Magnin, Sebastian Westermann, Josué Bock, Emmanuel Malet, Johan Berthet, Ludovic Ravanel, and Philip Deline
Earth Surf. Dynam., 11, 899–915, https://doi.org/10.5194/esurf-11-899-2023, https://doi.org/10.5194/esurf-11-899-2023, 2023
Short summary
Short summary
Quantitative knowledge of water availability on high mountain rock slopes is very limited. We use a numerical model and field measurements to estimate the water balance at a steep rock wall site. We show that snowmelt is the main source of water at elevations >3600 m and that snowpack hydrology and sublimation are key factors. The new information presented here can be used to improve the understanding of thermal, hydrogeological, and mechanical processes on steep mountain rock slopes.
Max Thomas, Briana Cate, Jack Garnett, Inga J. Smith, Martin Vancoppenolle, and Crispin Halsall
The Cryosphere, 17, 3193–3201, https://doi.org/10.5194/tc-17-3193-2023, https://doi.org/10.5194/tc-17-3193-2023, 2023
Short summary
Short summary
A recent study showed that pollutants can be enriched in growing sea ice beyond what we would expect from a perfectly dissolved chemical. We hypothesise that this effect is caused by the specific properties of the pollutants working in combination with fluid moving through the sea ice. To test our hypothesis, we replicate this behaviour in a sea-ice model and show that this type of modelling can be applied to predicting the transport of chemicals with complex behaviour in sea ice.
Amelia M. H. Bond, Markus M. Frey, Jan Kaiser, Jörg Kleffmann, Anna E. Jones, and Freya A. Squires
Atmos. Chem. Phys., 23, 5533–5550, https://doi.org/10.5194/acp-23-5533-2023, https://doi.org/10.5194/acp-23-5533-2023, 2023
Short summary
Short summary
Atmospheric nitrous acid (HONO) amount fractions measured at Halley Research Station, Antarctica, were found to be low. Vertical fluxes of HONO from the snow were also measured and agree with the estimated HONO production rate from photolysis of snow nitrate. In a simple box model of HONO sources and sinks, there was good agreement between the measured flux and amount fraction. HONO was found to be an important OH radical source at Halley.
Benjamin R. Loveday, Timothy Smyth, Anıl Akpinar, Tom Hull, Mark E. Inall, Jan Kaiser, Bastien Y. Queste, Matt Tobermann, Charlotte A. J. Williams, and Matthew R. Palmer
Earth Syst. Sci. Data, 14, 3997–4016, https://doi.org/10.5194/essd-14-3997-2022, https://doi.org/10.5194/essd-14-3997-2022, 2022
Short summary
Short summary
Using a new approach to combine autonomous underwater glider data and satellite Earth observations, we have generated a 19-month time series of North Sea net primary productivity – the rate at which phytoplankton absorbs carbon dioxide minus that lost through respiration. This time series, which spans 13 gliders, allows for new investigations into small-scale, high-frequency variability in the biogeochemical processes that underpin the carbon cycle and coastal marine ecosystems in shelf seas.
Michael P. Hemming, Jan Kaiser, Jacqueline Boutin, Liliane Merlivat, Karen J. Heywood, Dorothee C. E. Bakker, Gareth A. Lee, Marcos Cobas García, David Antoine, and Kiminori Shitashima
Ocean Sci., 18, 1245–1262, https://doi.org/10.5194/os-18-1245-2022, https://doi.org/10.5194/os-18-1245-2022, 2022
Short summary
Short summary
An underwater glider mission was carried out in spring 2016 near a mooring in the northwestern Mediterranean Sea. The glider deployment served as a test of a prototype ion-sensitive field-effect transistor pH sensor. Mean net community production rates were estimated from glider and buoy measurements of dissolved oxygen and inorganic carbon concentrations before and during the spring bloom. Incorporating advection is important for accurate mass budgets. Unexpected metabolic quotients were found.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
Short summary
Short summary
Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Tom Hull, Naomi Greenwood, Antony Birchill, Alexander Beaton, Matthew Palmer, and Jan Kaiser
Biogeosciences, 18, 6167–6180, https://doi.org/10.5194/bg-18-6167-2021, https://doi.org/10.5194/bg-18-6167-2021, 2021
Short summary
Short summary
The shallow shelf seas play a large role in the global cycling of CO2 and also support large fisheries. We use an autonomous underwater vehicle in the central North Sea to measure the rates of change in oxygen and nutrients.
Using these data we determine the amount of carbon dioxide taken out of the atmosphere by the sea and measure how productive the region is.
These observations will be useful for improving our predictive models and help us predict and adapt to a changing ocean.
Josué Bock, Martine Michou, Pierre Nabat, Manabu Abe, Jane P. Mulcahy, Dirk J. L. Olivié, Jörg Schwinger, Parvadha Suntharalingam, Jerry Tjiputra, Marco van Hulten, Michio Watanabe, Andrew Yool, and Roland Séférian
Biogeosciences, 18, 3823–3860, https://doi.org/10.5194/bg-18-3823-2021, https://doi.org/10.5194/bg-18-3823-2021, 2021
Short summary
Short summary
In this study we analyse surface ocean dimethylsulfide (DMS) concentration and flux to the atmosphere from four CMIP6 Earth system models over the historical and ssp585 simulations.
Our analysis of contemporary (1980–2009) climatologies shows that models better reproduce observations in mid to high latitudes. The models disagree on the sign of the trend of the global DMS flux from 1980 onwards. The models agree on a positive trend of DMS over polar latitudes following sea-ice retreat dynamics.
Max Thomas, Johannes C. Laube, Jan Kaiser, Samuel Allin, Patricia Martinerie, Robert Mulvaney, Anna Ridley, Thomas Röckmann, William T. Sturges, and Emmanuel Witrant
Atmos. Chem. Phys., 21, 6857–6873, https://doi.org/10.5194/acp-21-6857-2021, https://doi.org/10.5194/acp-21-6857-2021, 2021
Short summary
Short summary
CFC gases are destroying the Earth's life-protecting ozone layer. We improve understanding of CFC destruction by measuring the isotopic fingerprint of the carbon in the three most abundant CFCs. These are the first such measurements in the main region where CFCs are destroyed – the stratosphere. We reconstruct the atmospheric isotope histories of these CFCs back to the 1950s by measuring air extracted from deep snow and using a model. The model and the measurements are generally consistent.
Luca Possenti, Ingunn Skjelvan, Dariia Atamanchuk, Anders Tengberg, Matthew P. Humphreys, Socratis Loucaides, Liam Fernand, and Jan Kaiser
Ocean Sci., 17, 593–614, https://doi.org/10.5194/os-17-593-2021, https://doi.org/10.5194/os-17-593-2021, 2021
Short summary
Short summary
A Seaglider was deployed for 8 months in the Norwegian Sea mounting an oxygen and, for the first time, a CO2 optode and a chlorophyll fluorescence sensor. The oxygen and CO2 data were used to assess the spatial and temporal variability and calculate the net community production, N(O2) and N(CT). The dataset was used to calculate net community production from inventory changes, air–sea flux, diapycnal mixing and entrainment.
Max Thomas, James France, Odile Crabeck, Benjamin Hall, Verena Hof, Dirk Notz, Tokoloho Rampai, Leif Riemenschneider, Oliver John Tooth, Mathilde Tranter, and Jan Kaiser
Atmos. Meas. Tech., 14, 1833–1849, https://doi.org/10.5194/amt-14-1833-2021, https://doi.org/10.5194/amt-14-1833-2021, 2021
Short summary
Short summary
We describe the Roland von Glasow Air-Sea-Ice Chamber, a laboratory facility for studying ocean–sea-ice–atmosphere interactions. We characterise the technical capabilities of our facility to help future users plan and perform experiments. We also characterise the sea ice grown in the facility, showing that the extinction of photosynthetically active radiation, the bulk salinity, and the growth rate of our artificial sea ice are within the range of natural values.
Cited articles
Aiuppa, A., Franco, A., von Glasow, R., Allen, A. G., D'Alessandro, W., Mather, T. A., Pyle, D. M., and Valenza, M.: The tropospheric processing of acidic gases and hydrogen sulphide in volcanic gas plumes as inferred from field and model investigations, Atmos. Chem. Phys., 7, 1441–1450, https://doi.org/10.5194/acp-7-1441-2007, 2007. a
Andreae, M. O. and Crutzen, P. J.: Atmospheric aerosols: biogeochemical sources
and role in atmospheric chemistry, Science, 276, 1052–1058,
https://doi.org/10.1126/science.276.5315.1052, 1997. a
Audiffren, N., Renard, M., Buisson, E., and Chaumerliac, N.: Deviations from
the Henry's law equilibrium during cloud events: a numerical approach of
the mass transfer between phases and its specific numerical effects,
Atmos. Res., 49, 139–161, https://doi.org/10.1016/S0169-8095(98)00072-6,
1998. a
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson‐Parris,
D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A., Dufresne, J.,
Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J. M.,
Lohmann, U., Malavelle, F., Mauritsen, T., McCoy, D. T., Myhre, G.,
Mülmenstädt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y.,
Schulz, M., Schwartz, S. E., Sourdeval, O., Storelvmo, T., Toll, V., Winker,
D., and Stevens, B.: Bounding global aerosol radiative forcing of climate
change, Rev. Geophys., 58, e2019RG000660, https://doi.org/10.1029/2019RG000660, 2020. a
Bender, F. A.: Aerosol forcing: still uncertain, still relevant, AGU Advances,
1, e2019AV000128, https://doi.org/10.1029/2019AV000128, 2020. a
Bobrowski, N., von Glasow, R., Aiuppa, A., Inguaggiato, S., Louban, I.,
Ibrahim, O. W., and Platt, U.: Reactive halogen chemistry in volcanic plumes,
J. Geophys. Res., 112, D06311, https://doi.org/10.1029/2006JD007206, 2007. a
Bobrowski, N., von Glasow, R., Giuffrida, G. B., Tedesco, D., Aiuppa, A.,
Yalire, M., Arellano, S., Johansson, M., and Galle, B.: Gas emission strength
and evolution of the molar ratio of in the plume of
Nyiragongo in comparison to Etna: Br-emission & evolution from
Nyiragongo, J. Geophys. Res.-Atmos., 120, 277–291,
https://doi.org/10.1002/2013JD021069, 2015. a
Bock, J., Kaiser, J., Thomas, M., Bott, A., and von Glasgow, R.: MISTRA v9.0 (9.0), Zenodo [code], https://doi.org/10.5281/zenodo.6838912, 2022. a
Bott, A.: A numerical model of the cloud-topped planetary boundary-layer:
chemistry in marine stratus and the effects on aerosol particles, Atmos.
Environ., 33, 1921–1936, https://doi.org/10.1016/S1352-2310(98)00151-4,
1999a. a
Bott, A.: A numerical model of the cloud-topped planetary boundary-layer: cloud
processing of aerosol particles in marine stratus, Environ. Modell.
Softw., 14, 635–643, https://doi.org/10.1016/S1364-8152(99)00005-5,
1999b. a, b
Bott, A.: A flux method for the numerical solution of the stochastic collection
equation: extension to two-dimensional particle distributions, J.
Atmos. Sci., 57, 284–294,
https://doi.org/10.1175/1520-0469(2000)057<0284:AFMFTN>2.0.CO;2, 2000. a, b, c
Bott, A.: A new method for the solution of the stochastic collection equation
in cloud models with spectral aerosol and cloud drop microphysics,
Atmos. Res., 59-60, 361–372, https://doi.org/10.1016/S0169-8095(01)00125-9,
2001. a
Bott, A.: Comparison of a spectral microphysics and a two-moment cloud scheme:
numerical simulations of the cloud-topped marine boundary layer,
Bound.-Lay. Meteorol., 175, 153–178, https://doi.org/10.1007/s10546-020-00501-4,
2020. a, b, c, d
Bott, A. and Carmichael, G. R.: Multiphase chemistry in a microphysical
radiation fog model – a numerical study, Atmos. Environ. A-Gen., 27, 503–522, https://doi.org/10.1016/0960-1686(93)90208-G, 1993. a, b
Bott, A., Sievers, U., and Zdunkowski, W.: A radiation fog model with a
detailed treatment of the interaction between radiative transfer and fog
microphysics, J. Atmos. Sci., 47, 2153–2166,
https://doi.org/10.1175/1520-0469(1990)047<2153:ARFMWA>2.0.CO;2, 1990. a
Bott, A., Trautmann, T., and Zdunkowski, W.: A numerical model of the
cloud-topped planetary boundary-layer: radiation, turbulence and spectral
microphysics in marine stratus, Q. J. Roy. Meteor.
Soc., 122, 635–667, https://doi.org/10.1002/qj.49712253105, 1996. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster,
P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh,
S., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and Aerosols, in:
Climate Change 2013: The Physical Science Basis. Contribution of
Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Stocker, T.,
Qin, D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J., Nauels, A.,
Xia, Y., Bex, V., and Midgley, P., Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA, pp. 571–658,
https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter07_FINAL-1.pdf (last access: 31 May 2021),
2014. a
Burkholder, J. B., Curtius, J., Ravishankara, A. R., and Lovejoy, E. R.: Laboratory studies of the homogeneous nucleation of iodine oxides, Atmos. Chem. Phys., 4, 19–34, https://doi.org/10.5194/acp-4-19-2004, 2004. a
Buxmann, J., Bleicher, S., Platt, U., von Glasow, R., Sommariva, R., Held, A.,
Zetzsch, C., and Ofner, J.: Consumption of reactive halogen species from
sea-salt aerosol by secondary organic aerosol: slowing down the bromine
explosion, Environ. Chem., 12, 476–488, https://doi.org/10.1071/EN14226,
2015. a, b, c, d, e
Carslaw, K. S., Boucher, O., Spracklen, D. V., Mann, G. W., Rae, J. G. L., Woodward, S., and Kulmala, M.: A review of natural aerosol interactions and feedbacks within the Earth system, Atmos. Chem. Phys., 10, 1701–1737, https://doi.org/10.5194/acp-10-1701-2010, 2010. a
Chameides, W. L.: The photochemistry of a remote marine stratiform cloud,
J. Geophys. Res.-Atmos., 89, 4739–4755,
https://doi.org/10.1029/JD089iD03p04739, 1984. a
Chameides, W. L. and Stelson, A. W.: Aqueous-phase chemical processes in
deliquescent sea-salt aerosols: A mechanism that couples the atmospheric
cycles of S and sea salt, J. Geophys. Res.-Atmos., 97,
20565–20580, https://doi.org/10.1029/92JD01923, 1992. a
Chaumerliac, N., Leriche, M., and Audiffren, N.: Modeling of scavenging
processes in clouds: some remaining questions about the partitioning of gases
among gas and liquid phases, Atmos. Res., 53, 29–43,
https://doi.org/10.1016/S0169-8095(99)00041-1, 2000. a
Damian, V., Sandu, A., Damian, M., Potra, F., and Carmichael, G. R.: The
kinetic preprocessor KPP-a software environment for solving chemical
kinetics, Comput. Chem. Eng., 26, 1567–1579,
https://doi.org/10.1016/S0098-1354(02)00128-X, 2002. a
Davies, R.: Response of cloud supersaturation to radiative forcing, J.
Atmos. Sci., 42, 2820–2825,
https://doi.org/10.1175/1520-0469(1985)042<2820:ROCSTR>2.0.CO;2, 1985. a
Driedonks, A. G. M. and Duynkerke, P. G.: Current problems in the
stratocumulus-topped atmospheric boundary layer, Bound.-Lay. Meteorol.,
46, 275–303, https://doi.org/10.1007/BF00120843, 1989. a
Duynkerke, P. G.: Dynamics of cloudy boundary layers, in: Clear and cloudy
boundary layers: proceedings of the colloquium “Clear and cloudy boundary
layers”, Amsterdam, 26–29 August 1997, edited by: Holtslag, A. A. M. and
Duynkerke, P. G., Koninklijke Nederlandse Akademie van Wetenschappen,
Verhandelingen, Afd. Natuurkunde. Eerste reeks, pp. 151–167, Royal
Netherlands Academy of Arts and Science, Amsterdam, ISBN 978-90-6984-235-6, 1998. a
Ervens, B.: Modeling the processing of aerosol and trace gases in clouds and
fogs, Chem. Rev., 115, 4157–4198, https://doi.org/10.1021/cr5005887, 2015. a
Finlayson-Pitts, B. J.: Reactions at surfaces in the atmosphere: integration of
experiments and theory as necessary (but not necessarily sufficient) for
predicting the physical chemistry of aerosols, Phys. Chem. Chem.
Phys., 11, 7760–7779, https://doi.org/10.1039/b906540g, 2009. a
George, C., Ammann, M., D’Anna, B., Donaldson, D. J., and Nizkorodov, S. A.:
Heterogeneous photochemistry in the atmosphere, Chem. Rev., 115,
4218–4258, https://doi.org/10.1021/cr500648z, 2015. a
Gombosi, T. I.: Gaskinetic theory, Cambridge atmospheric and space science
series, Cambridge University Press, Cambridge, England, New York, https://doi.org/10.1017/CBO9780511524943, ISBN 9780521439664, 1994. a
Jones, C. E., Hornsby, K. E., Sommariva, R., Dunk, R. M., von Glasow, R.,
McFiggans, G., and Carpenter, L. J.: Quantifying the contribution of marine
organic gases to atmospheric iodine, Geophys. Res. Lett., 37,
L18804, https://doi.org/10.1029/2010GL043990, 2010. a
Kanakidou, M., Myriokefalitakis, S., and Tsigaridis, K.: Aerosols in
atmospheric chemistry and biogeochemical cycles of nutrients, Environ.
Res. Lett., 13, 063004, https://doi.org/10.1088/1748-9326/aabcdb, 2018. a
Kerminen, V.-M. and Kulmala, M.: Analytical formulae connecting the “real”
and the “apparent” nucleation rate and the nuclei number concentration
for atmospheric nucleation events, J. Aerosol Sci., 33, 609–622,
https://doi.org/10.1016/S0021-8502(01)00194-X, 2002. a
Kerminen, V.-M., Anttila, T., Lehtinen, K., and Kulmala, M.: Parameterization
for atmospheric new-particle formation: application to a system involving
sulfuric acid and condensable water-soluble organic vapors, Aerosol Sci.
Tech., 38, 1001–1008, https://doi.org/10.1080/027868290519085, 2004. a
Landgraf, J. and Crutzen, P. J.: An efficient method for online calculations of
photolysis and heating rates, J. Atmos. Sci., 55,
863–878, https://doi.org/10.1175/1520-0469(1998)055<0863:AEMFOC>2.0.CO;2, 1998. a, b
Lawler, M. J., Finley, B. D., Keene, W. C., Pszenny, A. A. P., Read, K. A., von
Glasow, R., and Saltzman, E. S.: Pollution‐enhanced reactive chlorine
chemistry in the eastern tropical Atlantic boundary layer, Geophys.
Res. Lett., 36, L08810, https://doi.org/10.1029/2008GL036666, 2009. a
Lee, C.-T. and Hsu, W.-C.: The measurement of liquid water mass associated with
collected hygroscopic particles, J. Aerosol Sci., 31, 189–197,
https://doi.org/10.1016/S0021-8502(99)00048-8, 2000. a
Liang, J. and Jacobson, M. Z.: A study of sulfur dioxide oxidation pathways
over a range of liquid water contents, pH values, and temperatures, J. Geophys. Res.-Atmos., 104, 13749–13769,
https://doi.org/10.1029/1999JD900097, 1999. a
Luo, B., Carslaw, K. S., Peter, T., and Clegg, S. L.: Vapour pressures of
H2SO4/HNO3/HCl/HBr/H2O solutions to low
stratospheric temperatures, Geophys. Res. Lett., 22, 247–250,
https://doi.org/10.1029/94GL02988, 1995. a
Lurmann, F. W., Lloyd, A. C., and Atkinson, R.: A chemical mechanism for use in
long-range transport/acid deposition computer modeling, J.
Geophys. Res., 91, 10905, https://doi.org/10.1029/JD091iD10p10905, 1986. a
Mellor, G. L. and Yamada, T.: Development of a turbulence closure model for
geophysical fluid problems, Rev. Geophys., 20, 851–875,
https://doi.org/10.1029/RG020i004p00851, 1982. a, b
Metcalf, M., Reid, J. K., and Cohen, M.: Fortran 95/2003 explained, Numerical
mathematics and scientific computation, Oxford University Press, Oxford, New
York, ISBN 978-01985269, 2004. a
Molina, C., Toro A., R., Manzano, C., Canepari, S., Massimi, L., and
Leiva-Guzmán, M.: Airborne aerosols and human health: leapfrogging from mass
concentration to oxidative potential, Atmosphere, 11, 917,
https://doi.org/10.3390/atmos11090917, 2020. a
Monahan, E. C., Spiel, D. E., and Davidson, K. L.: A model of marine aerosol
generation via whitecaps and wave disruption, in: Oceanic Whitecaps, edited
by: Monahan, E. C. and Niocaill, G. M., vol. 2, pp. 167–174, Springer
Netherlands, Dordrecht, https://doi.org/10.1007/978-94-009-4668-2_16, 1986. a, b
Napari, I., Noppel, M., Vehkamäki, H., and Kulmala, M.: Parametrization of
ternary nucleation rates for H2SO4-NH3-H2O vapors,
J. Geophys. Res.-Atmos., 107, AAC 6–1–AAC 6–6,
https://doi.org/10.1029/2002JD002132, 2002. a
NCAR: The NCAR Command Language (Version 6.6.2) [Software],
https://doi.org/10.5065/D6WD3XH5, 2019. a
Pechtl, S. and von Glasow, R.: Reactive chlorine in the marine boundary layer
in the outflow of polluted continental air: a model study, Geophys.
Res. Lett., 34, L11813, https://doi.org/10.1029/2007GL029761, 2007. a
Pechtl, S., Lovejoy, E. R., Burkholder, J. B., and von Glasow, R.: Modeling the possible role of iodine oxides in atmospheric new particle formation, Atmos. Chem. Phys., 6, 505–523, https://doi.org/10.5194/acp-6-505-2006, 2006. a, b, c, d
Pechtl, S., Schmitz, G., and von Glasow, R.: Modelling iodide – iodate speciation in atmospheric aerosol: Contributions of inorganic and organic iodine chemistry, Atmos. Chem. Phys., 7, 1381–1393, https://doi.org/10.5194/acp-7-1381-2007, 2007. a, b
Piot, M. and von Glasow, R.: The potential importance of frost flowers, recycling on snow, and open leads for ozone depletion events, Atmos. Chem. Phys., 8, 2437–2467, https://doi.org/10.5194/acp-8-2437-2008, 2008. a
Piot, M. and von Glasow, R.: Modelling the multiphase near-surface chemistry
related to ozone depletions in polar spring, J. Atmos.
Chem., 64, 77–105, https://doi.org/10.1007/s10874-010-9170-1, 2009. a
Pitzer, K. S.: Ion interaction approach: theory and data correlation, in:
Activity coefficients in electrolyte solutions, edited by: Pitzer, K. S.,
CRC Press, Boca Raton, 75–153, https://doi.org/10.1201/9781351069472-3, 1991. a
Pöschl, U.: Atmospheric aerosols: composition, transformation, climate and
health effects, Angewandte Chemie International Edition, 44, 7520–7540,
https://doi.org/10.1002/anie.200501122, 2005. a
Ruggaber, A., Dlugi, R., Bott, A., Forkel, R., Herrmann, H., and Jacobi, H.-W.:
Modelling of radiation quantities and photolysis frequencies in the aqueous
phase in the troposphere, Atmos. Environ., 31, 3137–3150,
https://doi.org/10.1016/S1352-2310(97)00058-7, 1997. a
Sander, R.: Modeling atmospheric chemistry: interactions between gas-phase
species and liquid cloud/aerosol particles, Surv. Geophys., 20, 1–31,
https://doi.org/10.1023/A:1006501706704, 1999. a
Sander, R. and Crutzen, P. J.: Model study indicating halogen activation and
ozone destruction in polluted air masses transported to the sea, J.
Geophys. Res.-Atmos., 101, 9121–9138, https://doi.org/10.1029/95JD03793,
1996. a
Sandu, A. and Sander, R.: Technical note: Simulating chemical systems in Fortran90 and Matlab with the Kinetic PreProcessor KPP-2.1, Atmos. Chem. Phys., 6, 187–195, https://doi.org/10.5194/acp-6-187-2006, 2006. a
Schwartz, S. E.: Mass-transport considerations pertinent to aqueous phase
reactions of gases in liquid-water clouds, in: Chemistry of Multiphase
Atmospheric Systems, edited by: Jaeschke, W., Springer
Berlin Heidelberg, Berlin, Heidelberg, pp. 415–471, https://doi.org/10.1007/978-3-642-70627-1_16,
1986. a
Shaw, M. A. and Rood, M. J.: Measurement of the crystallization humidities of
ambient aerosol particles, Atmos. Environ. A-Gen.,
24, 1837–1841, https://doi.org/10.1016/0960-1686(90)90516-P, 1990. a
Simpson, W. R., Brown, S. S., Saiz-Lopez, A., Thornton, J. A., and von Glasow,
R.: Tropospheric halogen chemistry: sources, cycling, and impacts, Chem.
Rev., 115, 4035–4062, https://doi.org/10.1021/cr5006638, 2015. a
Smith, M. H., Park, P. M., and Consterdine, I. E.: Marine aerosol
concentrations and estimated fluxes over the sea, Q. J.
Roy. Meteor. Soc., 119, 809–824, https://doi.org/10.1002/qj.49711951211,
1993.
a, b
Smoydzin, L. and von Glasow, R.: Do organic surface films on sea salt aerosols influence atmospheric chemistry? – a model study, Atmos. Chem. Phys., 7, 5555–5567, https://doi.org/10.5194/acp-7-5555-2007, 2007. a
Smoydzin, L. and von Glasow, R.: Modelling chemistry over the Dead Sea: bromine and ozone chemistry, Atmos. Chem. Phys., 9, 5057–5072, https://doi.org/10.5194/acp-9-5057-2009, 2009. a
Sommariva, R. and von Glasow, R.: Multiphase halogen chemistry in the tropical
Atlantic Ocean, Environ. Sci. Technol., 46,
10429–10437, https://doi.org/10.1021/es300209f, 2012. a, b, c
Tang, I. N.: Thermodynamic and optical properties of mixed-salt aerosols of
atmospheric importance, J. Geophys. Res.-Atmos., 102,
1883–1893, https://doi.org/10.1029/96JD03085, 1997. a, b
Thomas, J. L., Stutz, J., Lefer, B., Huey, L. G., Toyota, K., Dibb, J. E., and von Glasow, R.: Modeling chemistry in and above snow at Summit, Greenland – Part 1: Model description and results, Atmos. Chem. Phys., 11, 4899–4914, https://doi.org/10.5194/acp-11-4899-2011, 2011. a
Thomas, J. L., Dibb, J. E., Huey, L. G., Liao, J., Tanner, D., Lefer, B., von Glasow, R., and Stutz, J.: Modeling chemistry in and above snow at Summit, Greenland – Part 2: Impact of snowpack chemistry on the oxidation capacity of the boundary layer, Atmos. Chem. Phys., 12, 6537–6554, https://doi.org/10.5194/acp-12-6537-2012, 2012. a
von Glasow, R.: Modeling the gas and aqueous phase chemistry of the marine
boundary layer, PhD thesis, Universität Mainz, Germany, https://doi.org/10.25358/openscience-1082,
2000. a, b
von Glasow, R. and Bott, A.: Interaction of radiation fog with tall vegetation,
Atmos. Environ., 33, 1333–1346, https://doi.org/10.1016/S1352-2310(98)00372-0,
1999. a
von Glasow, R. and Crutzen, P. J.: Model study of multiphase DMS oxidation with a focus on halogens, Atmos. Chem. Phys., 4, 589–608, https://doi.org/10.5194/acp-4-589-2004, 2004. a, b
von Glasow, R., Sander, R., Bott, A., and Crutzen, P. J.: Modeling halogen
chemistry in the marine boundary layer 1. Cloud-free MBL, J.
Geophys. Res., 107, 4341, https://doi.org/10.1029/2001JD000942, 2002a. a
von Glasow, R., Sander, R., Bott, A., and Crutzen, P. J.: Modeling halogen
chemistry in the marine boundary layer 2. Interactions with sulfur and the
cloud-covered MBL, J. Geophys. Res., 107, 4323,
https://doi.org/10.1029/2001JD000943, 2002b. a
Wesely, M.: Parameterization of surface resistances to gaseous dry deposition
in regional-scale numerical models, Atmos. Environ., 23,
1293–1304, https://doi.org/10.1016/0004-6981(89)90153-4, 1989. a
Woodcock, A. H., Kientzler, C. F., Arons, A. B., and Blanchard, D. C.: Giant
condensation nuclei from bursting bubbles, Nature, 172, 1144–1145,
https://doi.org/10.1038/1721144a0, 1953. a
Zhang, S., Wu, J., Fan, W., Yang, Q., and Zhao, D.: Review of aerosol optical
depth retrieval using visibility data, Earth-Sci. Rev., 200, 102986,
https://doi.org/10.1016/j.earscirev.2019.102986, 2020. a
Short summary
MISTRA-v9.0 is an atmospheric boundary layer chemistry model. The model includes a detailed particle description with regards to the microphysics, gas–particle interactions, and liquid phase chemistry within particles. Version 9.0 is the first release of MISTRA as an open-source community model. This paper presents a thorough description of the model characteristics and components. We show some examples of simulations reproducing previous studies with MISTRA with good consistency.
MISTRA-v9.0 is an atmospheric boundary layer chemistry model. The model includes a detailed...