Articles | Volume 22, issue 24
https://doi.org/10.5194/acp-22-15887-2022
© 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/acp-22-15887-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A global climatology of ice-nucleating particles under cirrus conditions derived from model simulations with MADE3 in EMAC
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Johannes Hendricks
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Mattia Righi
Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
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Ice nucleating particles strongly influence cirrus cloud properties but remain difficult to measure at cirrus temperatures. By combining EMAC model simulations with in situ observations from the CIRRUS-HL campaign, we investigate aerosol-cirrus interactions across latitudes. While the model generally agrees with observations, it overestimates ice crystal number concentrations detrained from convection, which we correct applying a new radius-temperature parametrization from the observations.
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Katja Weigel, Lisa Bock, Bettina K. Gier, Axel Lauer, Mattia Righi, Manuel Schlund, Kemisola Adeniyi, Bouwe Andela, Enrico Arnone, Peter Berg, Louis-Philippe Caron, Irene Cionni, Susanna Corti, Niels Drost, Alasdair Hunter, Llorenç Lledó, Christian Wilhelm Mohr, Aytaç Paçal, Núria Pérez-Zanón, Valeriu Predoi, Marit Sandstad, Jana Sillmann, Andreas Sterl, Javier Vegas-Regidor, Jost von Hardenberg, and Veronika Eyring
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This work presents new diagnostics for the Earth System Model Evaluation Tool (ESMValTool) v2.0 on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The ESMValTool v2.0 diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) with a focus on the ESMs participating in the Coupled Model Intercomparison Project (CMIP).
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Axel Lauer, Veronika Eyring, Omar Bellprat, Lisa Bock, Bettina K. Gier, Alasdair Hunter, Ruth Lorenz, Núria Pérez-Zanón, Mattia Righi, Manuel Schlund, Daniel Senftleben, Katja Weigel, and Sabrina Zechlau
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The Earth System Model Evaluation Tool is a community software tool designed for evaluation and analysis of climate models. New features of version 2.0 include analysis scripts for important large-scale features in climate models, diagnostics for extreme events, regional model and impact evaluation. In this paper, newly implemented climate metrics, emergent constraints for climate-relevant feedbacks and diagnostics for future model projections are described and illustrated with examples.
Cited articles
Abbatt, J. P. D., Benz, S., Cziczo, D. J., Kanji, Z., Lohmann, U., and
Möhler, O.: Solid Ammonium Sulfate Aerosols as Ice Nuclei: A Pathway for
Cirrus Cloud Formation, Science, 313, 1770–1773,
https://doi.org/10.1126/science.1129726, 2006. a, b
Barahona, D., Rodriguez, J., and Nenes, A.: Sensitivity of the global
distribution of cirrus ice crystal concentration to heterogeneous freezing,
J. Geophys. Res.-Atmos., 115, D23213, https://doi.org/10.1029/2010JD014273, 2010. a, b, c
Bateman, A. P., Gong, Z., Liu, P., Sato, B., Cirino, G., Zhang, Y., Artaxo, P., Bertram, A. K., Manzi, A. O., Rizzo, L. V., Souza, R. A. F., Zaveri, R. A., and Martin, S. T.: Sub-micrometre particulate matter is primarily in liquid form over Amazon rainforest, Nat. Geosci., 9, 34–37,
https://doi.org/10.1038/ngeo2599, 2015. a
Baustian, K., Wise, M., Jensen, E., Schill, G., Freedman, M., and Tolbert, M.: State transformations and ice nucleation in amorphous (semi-) solid organic aerosol, Atmos. Chem. Phys., 13, 5615–5628, https://doi.org/10.5194/acp-13-5615-2013, 2013. a, b
Baustian, K. J., Wise, M. E., and Tolbert, M. A.: Depositional ice nucleation
on solid ammonium sulfate and glutaric acid particles, Atmos. Chem. Phys.,
10, 2307–2317, https://doi.org/10.5194/acp-10-2307-2010, 2010. a
Beer, C. G.: Global modelling of ice nucleating particles and their effects on cirrus clouds, PhD thesis, Ludwig-Maximilians-Universität München,
https://doi.org/10.5282/edoc.28470, 2021. a
Beer, C. G.: Model simulation data used in “A global climatology of ice nucleating-particles under cirrus conditions derived from model simulations with MADE3 in EMAC” (Beer et al., Atmos. Chem. Phys., 2022), Zenodo [data set], https://doi.org/10.5281/zenodo.6834299, 2022. a
Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris,
D., Boucher, O., Carslaw, K. S., Christensen, M., Daniau, A.-L., Dufresne,
J.-L., 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, b
Bertozzi, B., Wagner, R., Song, J., Höhler, K., Pfeifer, J., Saathoff, H., Leisner, T., and Möhler, O.: Ice nucleation ability of ammonium sulfate aerosol particles internally mixed with secondary organics, Atmos. Chem. Phys., 21, 10779–10798, https://doi.org/10.5194/acp-21-10779-2021, 2021. a
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, Cambridge University Press, 571–657,
https://doi.org/10.1017/CBO9781107415324.016, 2013. a, b
Chou, C., Kanji, Z. A., Stetzer, O., Tritscher, T., Chirico, R., Heringa, M. F., Weingartner, E., Prévôt, A. S. H., Baltensperger, U., and Lohmann, U.: Effect of photochemical ageing on the ice nucleation properties of diesel and wood burning particles, Atmos. Chem. Phys., 13, 761–772,
https://doi.org/10.5194/acp-13-761-2013, 2013. a
Colberg, C. A., Luo, B. P., Wernli, H., Koop, T., and Peter, T.: A novel model to predict the physical state of atmospheric
aerosol particles, Atmos. Chem. Phys., 3, 909–924, https://doi.org/10.5194/acp-3-909-2003, 2003. a
Cziczo, D. J., Froyd, K. D., Hoose, C., Jensen, E. J., Diao, M., Zondlo, M. A., Smith, J. B., Twohy, C. H., and Murphy, D. M.: Clarifying the dominant
sources and mechanisms of cirrus cloud formation, Science, 340, 1320–1324,
https://doi.org/10.1126/science.1234145, 2013. a
David, R. O., Marcolli, C., Fahrni, J., Qiu, Y., Perez Sirkin, Y. A., Molinero, V., Mahrt, F., Brühwiler, D., Lohmann, U., and Kanji, Z. A.: Pore condensation and freezing is responsible for ice formation below water
saturation for porous particles, P. Natl. Acad. Sci. USA, 116, 8184–8189,
https://doi.org/10.1073/pnas.1813647116, 2019. a, b
DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D.,
Twohy, C. H., Richardson, M., Eidhammer, T., and Rogers, D.: Predicting
global atmospheric ice nuclei distributions and their impacts on climate, P. Natl. Acad. Sci. USA, 107, 11217–11222, https://doi.org/10.1073/pnas.0910818107, 2010. a, b, c, d
Dentener, F., Kinne, S., Bond, T., Boucher, O., Cofala, J., Generoso, S., Ginoux, P., Gong, S., Hoelzemann, J. J., Ito, A., Marelli, L., Penner, J. E., Putaud, J.-P., Textor, C., Schulz, M., van der Werf, G. R., and Wilson, J.: Emissions of primary aerosol and precursor gases in the years 2000 and 1750 prescribed data-sets for AeroCom, Atmos. Chem. Phys., 6, 4321–4344, https://doi.org/10.5194/acp-6-4321-2006, 2006. a
Feng, L., Smith, S. J., Braun, C., Crippa, M., Gidden, M. J., Hoesly, R.,
Klimont, Z., van Marle, M., van den Berg, M., and van der Werf, G. R.: The
generation of gridded emissions data for CMIP6, Geosci. Model Dev., 13,
461–482, https://doi.org/10.5194/gmd-13-461-2020, 2020. a
Froyd, K. D., Yu, P., Schill, G. P., Brock, C. A., Kupc, A., Williamson, C. J., Jensen, E. J., Ray, E., Rosenlof, K. H., Bian, H., Darmenov, A. S., Colarco, P. R., Diskin, G. S., Bui, T., and Murphy, D. M.: Dominant role of mineral dust in cirrus cloud formation revealed by global-scale measurements, Nat. Geosci., 15, 177–183, https://doi.org/10.1038/s41561-022-00901-w, 2022. a
Gasparini, B. and Lohmann, U.: Why cirrus cloud seeding cannot substantially
cool the planet, J. Geophys. Res.-Atmos., 121, 4877–4893,
https://doi.org/10.1002/2015JD024666, 2016. a
Guenther, A., Hewitt, C. N., Erickson, D., Fall, R., Geron, C., Graedel, T.,
Harley, P., Klinger, L., Lerdau, M., Mckay, W. A., Pierce, T., Scholes, B.,
Steinbrecher, R., Tallamraju, R., Taylor, J., and Zimmerman, P.: A global
model of natural volatile organic compound emissions, J. Geophys. Res., 100,
8873–8892, https://doi.org/10.1029/94JD02950, 1995. a, b
Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron,
C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181–3210, https://doi.org/10.5194/acp-6-3181-2006, 2006. a
Hartigan, J. A. and Wong, M. A.: Algorithm AS 136: A K-Means Clustering
Algorithm, Appl. Stat., 28, 100–108, 1979. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteorol. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020. a
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G.,
Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018. a
Hoose, C. and Möhler, O.: Heterogeneous ice nucleation on atmospheric
aerosols: a review of results from laboratory experiments, Atmos. Chem.
Phys., 12, 9817–9854, https://doi.org/10.5194/acp-12-9817-2012, 2012. a
Ignatius, K., Kristensen, T. B., Järvinen, E., Nichman, L., Fuchs, C.,
Gordon, H., Herenz, P., Hoyle, C. R., Duplissy, J., Garimella, S., Dias, A.,
Frege, C., Höppel, N., Tröstl, J., Wagner, R., Yan, C., Amorim, A.,
Baltensperger, U., Curtius, J., Donahue, N. M., Gallagher, M. W., Kirkby, J.,
Kulmala, M., Möhler, O., Saathoff, H., Schnaiter, M., Tomé, A., Virtanen, A., Worsnop, D., and Stratmann, F.: Heterogeneous ice nucleation of viscous secondary organic aerosol produced from ozonolysis of α-pinene, Atmos. Chem. Phys., 16, 6495–6509, https://doi.org/10.5194/acp-16-6495-2016, 2016. a, b, c, d, e
Järvinen, E., Ignatius, K., Nichman, L., Kristensen, T. B., Fuchs, C., Hoyle, C. R., Höppel, N., Corbin, J. C., Craven, J., Duplissy, J., Ehrhart, S., Haddad, I. E., Frege, C., Gordon, H., Jokinen, T., Kallinger, P., Kirkby, J., Kiselev, A., Naumann, K.-H., Petäjä, T., Pinterich, T., Prevot, A. S. H., Saathoff, H., Schiebel, T., Sengupta, K., Simon, M., Slowik, J. G., Tröstl, J., Virtanen, A., Vochezer, P., Vogt, S., Wagner, A. C., Wagner, R., Williamson, C., Winkler, P. M., Yan, C., Baltensperger, U., Donahue, N. M., Flagan, R. C., Gallagher, M., Hansel, A., Kulmala, M., Stratmann, F., Worsnop, D. R., Möhler, O., Leisner, T., and Schnaiter, M.: Observation of viscosity transition in alpha-pinene secondary organic aerosol, Atmos. Chem. Phys., 16, 4423–4438, https://doi.org/10.5194/acp-16-4423-2016, 2016. a
Jensen, E. J., Pfister, L., Bui, T.-P., Lawson, P., and Baumgardner, D.: Ice
nucleation and cloud microphysical properties in tropical tropopause layer
cirrus, Atmos. Chem. Phys., 10, 1369–1384, https://doi.org/10.5194/acp-10-1369-2010,
2010. a
Jensen, E. J., Diskin, G., Lawson, R. P., Lance, S., Bui, T. P., Hlavka, D.,
McGill, M., Pfister, L., Toon, O. B., and Gao, R.: Ice nucleation and
dehydration in the Tropical Tropopause Layer, P. Natl. Acad. Sci. USA, 110,
2041–2046, https://doi.org/10.1073/pnas.1217104110, 2013. a
Jöckel, P., Kerkweg, A., Buchholz-Dietsch, J., Tost, H., Sander, R., and
Pozzer, A.: Technical Note: Coupling of chemical processes with the Modular
Earth Submodel System (MESSy) submodel TRACER, Atmos. Chem. Phys., 8, 1677–1687, https://doi.org/10.5194/acp-8-1677-2008, 2008. a
Jöckel, P., Kerkweg, A., Pozzer, A., Sander, R., Tost, H., Riede, H.,
Baumgaertner, A., Gromov, S., and Kern, B.: Development cycle 2 of the modular earth submodel system (MESSy2), Geosci. Model Dev., 3, 717–752,
https://doi.org/10.5194/gmd-3-717-2010, 2010. a
Kaiser, J. C., Hendricks, J., Righi, M., Riemer, N., Zaveri, R. A., Metzger,
S., and Aquila, V.: The MESSy aerosol submodel MADE3 (v2.0b): description and a box model test, Geosci. Model Dev., 7, 1137–1157,
https://doi.org/10.5194/gmd-7-1137-2014, 2014. a, b, c
Kaiser, J. C., Hendricks, J., Righi, M., Jöckel, P., Tost, H., Kandler, K., Weinzierl, B., Sauer, D., Heimerl, K., Schwarz, J. P., Perring, A. E., and Popp, T.: Global aerosol modeling with MADE3 (v3.0) in EMAC (based on v2.53): model description and evaluation, Geosci. Model Dev., 12, 541–579, https://doi.org/10.5194/gmd-12-541-2019, 2019. a, b, c
Kanji, Z. A., DeMott, P. J., Möhler, O., and Abbatt, J. P. D.: Results from the University of Toronto continuous flow diffusion chamber at ICIS 2007: instrument intercomparison and ice onsets for different aerosol types, Atmos. Chem. Phys., 11, 31–41, https://doi.org/10.5194/acp-11-31-2011, 2011. a
Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo,
D. J., and Krämer, M.: Overview of Ice Nucleating Particles, Meteorol.
Monogr., 58, 1.1–1.33, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0006.1, 2017. a, b, c
Kärcher, B.: Cirrus clouds and their response to anthropogenic activities, Curr. Clim. Change Rep., 3, 45–57, https://doi.org/10.1007/s40641-017-0060-3, 2017. a
Kärcher, B. and Lohmann, U.: A parameterization of cirrus cloud formation: Homogeneous freezing of supercooled aerosols, J. Geophys. Res.-Atmos., 107, 4010, https://doi.org/10.1029/2001JD000470, 2002. a
Kärcher, B., Hendricks, J., and Lohmann, U.: Physically based
parameterization of cirrus cloud formation for use in global atmospheric
models, J. Geophys. Res.-Atmos., 111, D01205, https://doi.org/10.1029/2005JD006219,
2006. a, b, c, d
Koehler, K. A., DeMott, P. J., Kreidenweis, S. M., Popovicheva, O. B., Petters, M. D., Carrico, C. M., Kireeva, E. D., Khokhlova, T. D., and Shonija, N. K.: Cloud condensation nuclei and ice nucleation activity of hydrophobic and hydrophilic soot particles, Phys. Chem. Chem. Phys., 11, 7906–7920, https://doi.org/10.1039/B905334B, 2009. a
Koop, T., Luo, B., Tsias, A., and Peter, T.: Water activity as the determinant for homogeneous ice nucleation in aqueous solutions, Nature, 406, 611–614, https://doi.org/10.1038/35020537, 2000. a
Koop, T., Bookhold, J., Shiraiwa, M., and Pöschl, U.: Glass transition and phase state of organic compounds: dependency on molecular properties and
implications for secondary organic aerosols in the atmosphere, Phys. Chem.
Chem. Phys., 13, 19238–19255, https://doi.org/10.1039/c1cp22617g, 2011. a, b
Kulkarni, G., Sanders, C., Zhang, K., Liu, X., and Zhao, C.: Ice nucleation of bare and sulfuric acid-coated mineral dust particles and implication for
cloud properties, J. Geophys. Res.-Atmos., 119, 9993–10011,
https://doi.org/10.1002/2014jd021567, 2014. a, b
Kulkarni, G., China, S., Liu, S., Nandasiri, M., Sharma, N., Wilson, J., Aiken, A. C., Chand, D., Laskin, A., Mazzoleni, C., Pekour, M., Shilling, J.,
Shutthanandan, V., Zelenyuk, A., and Zaveri, R. A.: Ice nucleation activity
of diesel soot particles at cirrus relevant temperature conditions: Effects
of hydration, secondary organics coating, soot morphology, and coagulation,
Geophys. Res. Lett., 43, 3580–3588, https://doi.org/10.1002/2016GL068707, 2016. a, b, c, d
Laaksonen, A., Kulmala, M., O'Dowd, C. D., Joutsensaari, J., Vaattovaara, P.,
Mikkonen, S., Lehtinen, K. E. J., Sogacheva, L., Maso, M. D., Aalto, P.,
Petäjä, T., Sogachev, A., Yoon, Y. J., Lihavainen, H., Nilsson, D.,
Facchini, M. C., Cavalli, F., Fuzzi, S., Hoffmann, T., Arnold, F., Hanke, M.,
Sellegri, K., Umann, B., Junkermann, W., Coe, H., Allan, J. D., Alfarra, M. R., Worsnop, D. R., Riekkola, M. L., Hyötyläinen, T., and Viisanen,
Y.: The role of VOC oxidation products in continental new particle formation, Atmos. Chem. Phys., 8, 2657–2665, https://doi.org/10.5194/acp-8-2657-2008, 2008. a
Li, J., Hendricks, J., Righi, M., and Beer, C. G.: An aerosol classification
scheme for global simulations using the K-means machine learning method,
Geosci. Model Dev., 15, 509–533, https://doi.org/10.5194/gmd-15-509-2022, 2022. a
Liu, X., Penner, J. E., Das, B., Bergmann, D., Rodriguez, J. M., Strahan, S.,
Wang, M., and Feng, Y.: Uncertainties in global aerosol simulations:
Assessment using three meteorological data sets, J. Geophys. Res.-Atmos.,
112, D11212, https://doi.org/10.1029/2006JD008216, 2007. a
Mahrt, F., Marcolli, C., David, R. O., Grönquist, P., Meier, E. J. B.,
Lohmann, U., and Kanji, Z. A.: Ice nucleation abilities of soot particles
determined with the Horizontal Ice Nucleation Chamber, Atmos. Chem. Phys.,
18, 13363–13392, https://doi.org/10.5194/acp-18-13363-2018, 2018. a, b, c
Mahrt, F., Kilchhofer, K., Marcolli, C., Grönquist, P., David, R. O.,
Rösch, M., Lohmann, U., and Kanji, Z. A.: The Impact of Cloud Processing on the Ice Nucleation Abilities of Soot Particles at Cirrus Temperatures, J.
Geophys. Res.-Atmos., 125, e2019JD030922, https://doi.org/10.1029/2019jd030922, 2020. a, b
Marcolli, C.: Pre-activation of aerosol particles by ice preserved in pores,
Atmos. Chem. Phys., 17, 1595–1622, https://doi.org/10.5194/acp-17-1595-2017, 2017. a
Martin, S. T.: Phase Transitions of Aqueous Atmospheric Particles, Chem. Rev., 100, 3403–3454, https://doi.org/10.1021/cr990034t, 2000. a, b
Martin, S. T., Schlenker, J. C., Malinowski, A., Hung, H.-M., and Rudich, Y.:
Crystallization of atmospheric sulfate-nitrate-ammonium particles, Geophys.
Res. Lett., 30, 1–6, https://doi.org/10.1029/2003GL017930, 2003. a
Martin, S. T., Hung, H.-M., Park, R. J., Jacob, D. J., Spurr, R. J. D., Chance, K. V., and Chin, M.: Effects of the physical state of tropospheric
ammonium-sulfate-nitrate particles on global aerosol direct radiative
forcing, Atmos. Chem. Phys., 4, 183–214, https://doi.org/10.5194/acp-4-183-2004, 2004. a
McGraw, Z., Storelvmo, T., Samset, B. H., and Stjern, C. W.: Global Radiative
Impacts of Black Carbon Acting as Ice Nucleating Particles, Geophys. Res.
Lett., 47, e2020GL089056, https://doi.org/10.1029/2020GL089056, 2020. a
Modular Earth Submodel System (MESSy): https://www.messy-interface.org/, last access: 6 December 2022. a
Möhler, O., Field, P. R., Connolly, P., Benz, S., Saathoff, H., Schnaiter, M., Wagner, R., Cotton, R., Krämer, M., Mangold, A., and Heymsfield, A. J.: Efficiency of the deposition mode ice nucleation on mineral dust particles, Atmos. Chem. Phys., 6, 3007–3021, https://doi.org/10.5194/acp-6-3007-2006, 2006. a, b
Möhler, O., Benz, S., Saathoff, H., Schnaiter, M., Wagner, R., Schneider, J., Walter, S., Ebert, V., and Wagner, S.: The effect of organic coating on the heterogeneous ice nucleation efficiency of mineral dust aerosols, Environ. Res. Lett., 3, 025007, https://doi.org/10.1088/1748-9326/3/2/025007, 2008. a, b, c
Mülmenstädt, J. and Feingold, G.: The Radiative Forcing of
Aerosol–Cloud Interactions in Liquid Clouds: Wrestling and Embracing
Uncertainty, Curr. Clim. Change Rep., 4, 23–40,
https://doi.org/10.1007/s40641-018-0089-y, 2018. a, b
Murphy, D. M. and Koop, T.: Review of the vapour pressures of ice and
supercooled water for atmospheric applications, Q. J. Roy. Meteorol. Soc., 131, 1539–1565, https://doi.org/10.1256/qj.04.94, 2005. a
Murray, B. J., Wilson, T. W., Dobbie, S., Cui, Z., Al-Jumur, S. M., Möhler, O., Schnaiter, M., Wagner, R., Benz, S., Niemand, M., Saathoff, H., Ebert, V., Wagner, S., and Kärcher, B.: Heterogeneous nucleation of ice particles on glassy aerosols under cirrus conditions, Nat. Geosci., 3, 233–237, https://doi.org/10.1038/NGEO817, 2010. a
Murray, B. J., Carslaw, K. S., and Field, P. R.: Opinion: Cloud-phase climate
feedback and the importance of ice-nucleating particles, Atmos. Chem. Phys.,
21, 665–679, https://doi.org/10.5194/acp-21-665-2021, 2021. a
Nichman, L., Wolf, M., Davidovits, P., Onasch, T. B., Zhang, Y., Worsnop,
D. R., Bhandari, J., Mazzoleni, C., and Cziczo, D. J.: Laboratory study of
the heterogeneous ice nucleation on black-carbon-containing aerosol, Atmos.
Chem. Phys., 19, 12175–12194, https://doi.org/10.5194/acp-19-12175-2019, 2019. a
Park, R. J., Jacob, D. J., Field, B. D., Yantosca, R. M., and Chin, M.: Natural and transboundary pollution influences on sulfate-nitrate-ammonium aerosols in the United States: Implications for policy, J. Geophys. Res., 109, D15204, https://doi.org/10.1029/2003jd004473, 2004. a
Penner, J. E., Zhou, C., Garnier, A., and Mitchell, D. L.: Anthropogenic
Aerosol Indirect Effects in Cirrus Clouds, J. Geophys. Res.-Atmos., 123,
11652–11677, https://doi.org/10.1029/2018JD029204, 2018. a, b, c
Reid, J. P., Bertram, A. K., Topping, D. O., Laskin, A., Martin, S. T.,
Petters, M. D., Pope, F. D., and Rovelli, G.: The viscosity of atmospherically relevant organic particles, Nat. Commun., 9, 956,
https://doi.org/10.1038/s41467-018-03027-z, 2018. a, b
Righi, M., Hendricks, J., Lohmann, U., Beer, C. G., Hahn, V., Heinold, B.,
Heller, R., Krämer, M., Ponater, M., Rolf, C., Tegen, I., and Voigt, C.:
Coupling aerosols to (cirrus) clouds in the global EMAC-MADE3
aerosol-climate model, Geosci. Model Dev., 13, 1635–1661,
https://doi.org/10.5194/gmd-13-1635-2020, 2020. a, b, c, d, e, f, g
Roeckner, E., Arpe, K., Bengtsson, L., Christoph, M., Claussen, M.,
Dümenil, L., Esch, M., Giorgetta, M. A., Schlese, U., and Schulzweida,
U.: The atmospheric general circulation model ECHAM-4: Model description
and simulation of present-day climate, MPI Report, https://hdl.handle.net/11858/00-001M-0000-0013-ADE3-C (last access: 6 December 2022), 1996. a
Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kornblueh,
L., Manzini, E., Schlese, U., and Schulzweida, U.: Sensitivity of Simulated
Climate to Horizontal and Vertical Resolution in the ECHAM5 Atmosphere
Model, J. Climate, 19, 3771–3791, https://doi.org/10.1175/JCLI3824.1, 2006. a
Rogers, D. C., DeMott, P. J., Kreidenweis, S. M., and Chen, Y.: Measurements of ice nucleating aerosols during SUCCESS, Geophys. Res. Lett., 25,
1383–1386, https://doi.org/10.1029/97gl03478, 1998. a, b, c, d
Rogers, D. C., DeMott, P. J., and Kreidenweis, S. M.: Airborne measurements of tropospheric ice-nucleating aerosol particles in the Arctic spring, J.
Geophys. Res.-Atmos., 106, 15053–15063, https://doi.org/10.1029/2000jd900790, 2001a. a, b, c, d
Rogers, D. C., DeMott, P. J., Kreidenweis, S. M., and Chen, Y.: A
Continuous-Flow Diffusion Chamber for Airborne Measurements of Ice Nuclei, J.
Atmos. Ocean. Tech., 18, 725–741, https://doi.org/10.1175/1520-0426(2001)018<0725:acfdcf>2.0.co;2, 2001b. a
Rotman, D. A., Tannahill, J. R., Kinnison, D. E., Connell, P. S., Bergmann, D., Proctor, D., Rodriguez, J. M., Lin, S. J., Rood, R. B., Prather, M. J.,
Rasch, P. J., Considine, D. B., Ramaroson, R., and Kawa, S. R.: Global
Modeling Initiative assessment model: Model description, integration, and
testing of the transport shell, J. Geophys. Res.-Atmos., 106, 1669–1691,
https://doi.org/10.1029/2000jd900463, 2001. a
Rumble, J. R.: CRC handbook of chemistry and physics, in: 98th Edn., CRC Press, ISBN 1498784542, 2004. a
Saukko, E., Zorn, S., Kuwata, M., Keskinen, J., and Virtanen, A.: Phase State
and Deliquescence Hysteresis of Ammonium-Sulfate-Seeded Secondary Organic
Aerosol, Aerosol Sci. Tech., 49, 531–537, https://doi.org/10.1080/02786826.2015.1050085, 2015. a
Schill, G. P., De Haan, D. O., and Tolbert, M. A.: Heterogeneous ice nucleation on simulated secondary organic aerosol, Environ. Sci. Technol., 48, 1675–1682, https://doi.org/10.1021/es4046428, 2014. a
Schrod, J., Weber, D., Drücke, J., Keleshis, C., Pikridas, M., Ebert, M.,
Cvetković, B., Nickovic, S., Marinou, E., Baars, H., Ansmann, A.,
Vrekoussis, M., Mihalopoulos, N., Sciare, J., Curtius, J., and Bingemer, H. G.: Ice nucleating particles over the Eastern Mediterranean measured by
unmanned aircraft systems, Atmos. Chem. Phys., 17, 4817–4835,
https://doi.org/10.5194/acp-17-4817-2017, 2017. a, b, c, d
Shiraiwa, M., Li, Y., Tsimpidi, A. P., Karydis, V. A., Berkemeier, T., Pandis, S. N., Lelieveld, J., Koop, T., and Pöschl, U.: Global distribution of particle phase state in atmospheric secondary organic aerosols, Nat. Commun., 8, 15002, https://doi.org/10.1038/ncomms15002, 2017. a, b, c
Smith, M. L., Bertram, A. K., and Martin, S. T.: Deliquescence, efflorescence, and phase miscibility of mixed particles of ammonium sulfate and isoprene-derived secondary organic material, Atmos. Chem. Phys., 12,
9613–9628, https://doi.org/10.5194/acp-12-9613-2012, 2012. a
Smith, M. L., You, Y., Kuwata, M., Bertram, A. K., and Martin, S. T.: Phase
Transitions and Phase Miscibility of Mixed Particles of Ammonium Sulfate,
Toluene-Derived Secondary Organic Material, and Water, J. Phys. Chem. A, 117,
8895–8906, https://doi.org/10.1021/jp405095e, 2013. a
Tegen, I., Harrison, S. P., Kohfeld, K., Prentice, I. C., Coe, M., and Heimann, M.: Impact of vegetation and preferential source areas on global dust aerosol: Results from a model study, J. Geophys. Res.-Atmos., 107,
14-1–14-27, https://doi.org/10.1029/2001JD000963, 2002. a, b
Tsimpidi, A. P., Karydis, V. A., Pozzer, A., Pandis, S. N., and Lelieveld, J.: ORACLE (v1.0): module to simulate the organic aerosol composition and
evolution in the atmosphere, Geosci. Model Dev., 7, 3153–3172,
https://doi.org/10.5194/gmd-7-3153-2014, 2014. a
van Marle, M. J. E., Kloster, S., Magi, B. I., Marlon, J. R., Daniau, A.-L.,
Field, R. D., Arneth, A., Forrest, M., Hantson, S., Kehrwald, N. M., Knorr,
W., Lasslop, G., Li, F., Mangeon, S., Yue, C., Kaiser, J. W., and van der
Werf, G. R.: Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750–2015), Geosci. Model Dev., 10, 3329–3357,
https://doi.org/10.5194/gmd-10-3329-2017, 2017. a
Wagner, R., Höhler, K., Huang, W., Kiselev, A., Möhler, O., Mohr, C.,
Pajunoja, A., Saathoff, H., Schiebel, T., Shen, X., and Virtanen, A.:
Heterogeneous ice nucleation of α-pinene SOA particles before and
after ice cloud processing, J. Geophys. Res.-Atmos., 122, 4924–4943,
https://doi.org/10.1002/2016JD026401, 2017. a
Wagner, R., Ickes, L., Bertram, A. K., Els, N., Gorokhova, E., Möhler, O., Murray, B. J., Umo, N. S., and Salter, M. E.: Heterogeneous ice nucleation ability of aerosol particles generated from Arctic sea surface microlayer and surface seawater samples at cirrus temperatures, Atmos. Chem. Phys., 21, 13903–13930, https://doi.org/10.5194/acp-21-13903-2021, 2021. a
Wang, J., Hoffmann, A. A., Park, R. J., Jacob, D. J., and Martin, S. T.: Global distribution of solid and aqueous sulfate aerosols: Effect of the hysteresis of particle phase transitions, J. Geophys. Res.-Atmos., 113, D11206, https://doi.org/10.1029/2007JD009367, 2008. a, b
Wilbourn, E. K., Thornton, D. C. O., Ott, C., Graff, J., Quinn, P. K., Bates,
T. S., Betha, R., Russell, L. M., Behrenfeld, M. J., and Brooks, S. D.: Ice
Nucleation by Marine Aerosols Over the North Atlantic Ocean in Late Spring, J. Geophys. Res.-Atmos., 125, e2019JD030913, https://doi.org/10.1029/2019jd030913, 2020. a, b
Wise, M. E., Baustian, K. J., and Tolbert, M. A.: Laboratory studies of ice
formation pathways from ammonium sulfate particles, Atmos. Chem. Phys., 9,
1639–1646, https://doi.org/10.5194/acp-9-1639-2009, 2009. a
Zhu, J. and Penner, J. E.: Radiative forcing of anthropogenic aerosols on
cirrus clouds using a hybrid ice nucleation scheme, Atmos. Chem. Phys., 20,
7801–7827, https://doi.org/10.5194/acp-20-7801-2020, 2020. a
Short summary
Ice-nucleating particles (INPs) have important influences on cirrus clouds and the climate system; however, their global atmospheric distribution in the cirrus regime is still very uncertain. We present a global climatology of INPs under cirrus conditions derived from model simulations, considering the mineral dust, soot, crystalline ammonium sulfate, and glassy organics INP types. The comparison of respective INP concentrations indicates the large importance of ammonium sulfate particles.
Ice-nucleating particles (INPs) have important influences on cirrus clouds and the climate...
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