CoChat
Sign Up
Cited by 26Atmospheric aerosols and cloudsClimate Change and GeoengineeringMeteorological Phenomena and Simulations

Cirrus cloud thinning using a more physically based ice microphysics scheme in the ECHAM-HAM general circulation model

Open access
Tully, Colin, Neubauer, David, Omanovic, Nadja, Lohmann, Ulrike·2022·Atmospheric Chemistry and Physics
DOI 10.5194/acp-22-11455-2022

Published version of a preprint

Open this paper in CoChat — free account

Abstract

Abstract. Cirrus cloud thinning (CCT) is a relatively new radiation management proposal to counteract anthropogenic climate warming by targeting Earth’s terrestrial radiation balance. The efficacy of this method was presented in several general circulation model (GCM) studies that showed widely varied radiative responses, originating in part from the differences in the representation of cirrus ice microphysics between the different GCMs. The recent implementation of a new, more physically based ice microphysics scheme (Predicted Particle Properties, P3) that abandons ice hydrometeor size class separation into the ECHAM-HAM GCM, coupled to a new approach for calculating cloud fractions that increases the relative humidity (RH) thresholds for cirrus cloud formation, motivated a reassessment of CCT efficacy. In this study, we first compared CCT sensitivity between the new cloud fraction approach and the original ECHAM-HAM cloud fraction approach. With the P3 scheme and the higher RH thresholds for cirrus cloud formation, we find a significant cooling response of −0.36 Wm−2 only for our simulation with a seeding particle concentration of 1 L−1, due mostly to rapid cloud adjustments. The most notable response is the reduction of the maximum global-mean net top-of-atmosphere (TOA) radiative anomalies from overseeding by more than 50 %, from 9.0 Wm−2 with the original cloud fraction approach, down to 4.3 Wm−2 using the new cloud fraction RH thresholds by avoiding artificial ice-cloud expansion upon ice nucleation. We attribute the large positive TOA anomalies to seeding particles overtaking both homogeneous nucleation and heterogeneous nucleation on mineral dust particles within cirrus clouds to produce more numerous and smaller ice crystals. This effect is amplified by longer ice residence times in clouds due to the more realistic, slower removal of ice via sedimentation in the P3 scheme. In an effort to avoid this overtaking effect of seeding particles, we increased the default critical ice saturation ratio (Si,seed) for ice nucleation on seeding particles from the default value of 1.05 to 1.35 in a second sensitivity test. With the higher Si,seed we eliminate overseeding and are able to produce cooling responses over a broader range of seeding particle concentrations, with the largest cooling of −0.32 Wm−2 for a seeding particle concentration of 10 L−1, which suggests that Si,seed is a key factor to consider for future CCT studies. However, the global-mean TOA anomalies contain high uncertainty. In response, we examined the TOA responses regionally and found that specific regions only show a small potential for targeted CCT, which is partially enhanced by using the larger Si,seed. Finally, in a seasonal analysis of TOA responses to CCT, we find that our results do not support the previous finding that high-latitude wintertime seeding is a feasible strategy to enhance CCT efficacy, as seeding in our model enhances the already positive cirrus longwave cloud radiative effect. Instead, our results show that summertime cooling occurs due to adjustments of lower-lying mixed-phase and liquid clouds. Therefore, we conclude that CCT is unlikely to act as a feasible climate intervention strategy on a global scale, and should be investigated further with higher-resolution studies in potential target regions and with studies dedicated to assessing potentially realistic seeding particle materials.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.5194/acp-22-11455-2022

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Modeling indicates that excessive INP can lead to cirrus overseeding, producing numerous small ice crystals that slow fall speeds, prolong cirrus lifetime, increasing optical thickness, and ultimately reduce outgoing longwave radiation, diminishing cooling.

    “Modeling indicates that excessive INP can lead to cirrus overseeding, producing numerous small ice crystals that slow fall speeds, prolong cirrus lifetime, increasing optical thickness, and ultimately reduce outgoing longwave radiation, diminishing cooling (Gasparini & Lohmann, 2016; Tully et al., 2022)”

    From Past Field Experiments of Solar Radiation Modification: A Review of the Scientific and Technical Aspects for Governance (2026) · cites this paper as Tully et al., 2022

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 97 · Cited by 26

Research works printed but not linked: 92

  1. Barahona, D. and Nenes, A.: Parameterization of cirrus cloud formation in large-scale models: Homogeneous nucleation, J. Geophys. Res.-Atmos., 113, D11211, https://doi.org/10.1029/2007JD009355, 2008. a · DOI
  2. Barahona, D. and Nenes, A.: Parameterizing the competition between homogeneous and heterogeneous freezing in cirrus cloud formation – monodisperse ice nuclei, Atmos. Chem. Phys., 9, 369–381, https://doi.org/10.5194/acp-9-369-2009, 2009. a, b · DOI
  3. Brinkop, S. and Roeckner, E.: Sensitivity of a general circulation model to parameterizations of cloud–turbulence interactions in the atmospheric boundary layer, Tellus A, 47, 197–220, https://doi.org/10.1034/j.1600-0870.1995.t01-1-00004.x, 1995. a, b · DOI
  4. Butchart, N.: The Brewer-Dobson circulation, Rev. Geophys., 52, 157–184, https://doi.org/10.1002/2013RG000448, 2014. a, b · DOI
  5. Butchart, N. and Scafie, A.: Removal of chlorofluorocarbons by increased mass exchange between the stratosphere and troposphere in a changing climate, Nature, 410, 799–802, https://doi.org/10.1038/35071047, 2001. a · DOI
  6. Butchart, N., Scafie, A., Bourqui, M., de Grandpré, J., Hare, S., Kettleborough, J., Langematz, U., Manzini, E., Sassi, F., Shibata, K., Shindell, D., and Sigmond, M.: Simulations of anthropogenic change in the strength of the Brewer–Dobson circulation, Clim. Dynam., 27, 727–741, https://doi.org/10.1007/s00382-006-0162-4, 2006. a · DOI
  7. Calvo, N., Garcia, R. R., Randel, W. J., and Marsh, D. R.: Dynamical Mechanism for the Increase in Tropical Upwelling in the Lowermost Tropical Stratosphere during Warm ENSO Events, J. Atmos. Sci., 67, 2331–2340, https://doi.org/10.1175/2010JAS3433.1, 2010. a, b, c · DOI
  8. Crutzen, P. J.: Albedo Enhancement by Stratospheric Sulfur Injections: A Contribution to Resolve a Policy Dilemma?, Climatic Change, 77, 2784–2786, https://doi.org/10.1007/s10584-006-9101-y, 2006. a, b · DOI · Paper page
  9. 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, b, c · DOI
  10. Cziczo, D. J., Wolf, M. J., Gasparini, B., Münch, S., and Lohmann, U.: Unanticipated Side Effects of Stratospheric Albedo Modification Proposals Due to Aerosol Composition and Phase, Sci. Rep., 9, 18825, https://doi.org/10.1038/s41598-019-53595-3, 2019. a · DOI · Paper page
  11. Delanoë, J., Protat, A., Testud, J., Bouniol, D., Heymsfield, A. J., Bansemer, A., Brown, P. R. A., and Forbes, R. M.: Statistical properties of the normalized ice particle size distribution, J. Geophys. Res.-Atmos., 110, D10201, https://doi.org/10.1029/2004JD005405, 2005. a · DOI
  12. DeMott, P. J., Cziczo, D. J., Prenni, A. J., Murphy, D. M., Kreidenweis, S. M., Thomson, D. S., Borys, R., and Rogers, D. C.: Measurements of the concentration and composition of nuclei for cirrus formation, P. Natl. Acad. Sci. USA, 100, 14655–14660, https://doi.org/10.1073/pnas.2532677100, 2003. a, b · DOI
  13. DeMott, P. J., Prenni, A. J., Liu, X., Kreidenweis, S. M., Petters, M. D., Twohy, C. H., Richardson, M. S., Eidhammer, T., and Rogers, D. C.: 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 · DOI
  14. Dietlicher, R., Neubauer, D., and Lohmann, U.: Prognostic parameterization of cloud ice with a single category in the aerosol-climate model ECHAM(v6.3.0)-HAM(v2.3), Geosci. Model Dev., 11, 1557–1576, https://doi.org/10.5194/gmd-11-1557-2018, 2018. a, b, c, d, e, f, g, h, i, j, k · DOI
  15. Dietlicher, R., Neubauer, D., and Lohmann, U.: Elucidating ice formation pathways in the aerosol–climate model ECHAM6-HAM2, Atmos. Chem. Phys., 19, 9061–9080, https://doi.org/10.5194/acp-19-9061-2019, 2019. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v · DOI
  16. Dykema, J. A., Keith, D. W., and Keutsch, F. N.: Improved aerosol radiative properties as a foundation for solar geoengineering risk assessment, Geophys. Res. Lett., 43, 7758–7766, https://doi.org/10.1002/2016GL069258, 2016. a · DOI · Paper page
  17. Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J.-L., Frame, D., Lunt, D., Mauritsen, T., Palmer, M., Watanabe, M., Wild, M., and Zhang, H.: The Earth’s Energy Budget, Climate Feedbacks, and Climate Sensitivity, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 923–1054, https://doi.org/10.1017/9781009157896.009​​​​​​​, 2021. a · DOI · Paper page
  18. 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, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v · DOI · Paper page
  19. Gasparini, B., Münch, S., Poncet, L., Feldmann, M., and Lohmann, U.: Is increasing ice crystal sedimentation velocity in geoengineering simulations a good proxy for cirrus cloud seeding?, Atmos. Chem. Phys., 17, 4871–4885, https://doi.org/10.5194/acp-17-4871-2017, 2017. a, b, c, d, e, f, g, h · DOI
  20. Gasparini, B., Meyer, A., Neubauer, D., Münch, S., and Lohmann, U.: Cirrus Cloud Properties as Seen by the CALIPSO Satellite and ECHAM-HAM Global Climate Model, J. Climate, 31, 1983–2003, https://doi.org/10.1175/JCLI-D-16-0608.1, 2018. a, b, c · DOI
  21. Gasparini, B., McGraw, Z., Storelvmo, T., and Lohmann, U.: To what extent can cirrus cloud seeding counteract global warming?, Environ. Res. Lett., 15, 054002, https://doi.org/10.1088/1748-9326/ab71a3, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n · DOI
  22. Gettelman, A., Liu, X., Ghan, S. J., Morrison, H., Park, S., Conley, A. J., Klein, S. A., Boyle, J., Mitchell, D. L., and Li, J.-L. F.: Global simulations of ice nucleation and ice supersaturation with an improved cloud scheme in the Community Atmosphere Model, J. Geophys. Res.-Atmos., 115, D18216, https://doi.org/10.1029/2009JD013797, 2010. a · DOI
  23. Gruber, S., Blahak, U., Haenel, F., Kottmeier, C., Leisner, T., Muskatel, H., Storelvmo, T., and Vogel, B.: A Process Study on Thinning of Arctic Winter Cirrus Clouds With High-Resolution ICON-ART Simulations, J. Geophys. Res.-Atmos., 124, 5860–5888, https://doi.org/10.1029/2018JD029815, 2019. a, b, c, d, e, f · DOI
  24. Gryspeerdt, E., Sourdeval, O., Quaas, J., Delanoë, J., Krämer, M., and Kühne, P.: Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 2: Controls on the ice crystal number concentration, Atmos. Chem. Phys., 18, 14351–14370, https://doi.org/10.5194/acp-18-14351-2018, 2018. a, b · DOI
  25. Heymsfield, A. J., Krämer, M., Luebke, A., Brown, P., Cziczo, D. J., Franklin, C., Lawson, P., Lohmann, U., McFarquhar, G., Ulanowski, Z., and Van Tricht, K.: Cirrus Clouds, Meteor. Mon., 58, 2.1–2.26, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0010.1, 2017. a, b, c, d, e, f · DOI
  26. 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 · DOI · Paper page
  27. Hong, Y., Liu, G., and Li, J.-L. F.: Assessing the Radiative Effects of Global Ice Clouds Based on CloudSat and CALIPSO Measurements, J. Climate, 29, 7651–7674, https://doi.org/10.1175/JCLI-D-15-0799.1, 2016. a · DOI
  28. Ickes, L., Welti, A., Hoose, C., and Lohmann, U.: Classical nucleation theory of homogeneous freezing of water: thermodynamic and kinetic parameters, Phys. Chem. Chem. Phys., 17, 5514–5537, https://doi.org/10.1039/C4CP04184D, 2015. a · DOI
  29. Jensen, E. J., Ueyama, R., Pfister, L., Bui, T. V., Alexander, M. J., Podglajen, A., Hertzog, A., Woods, S., Lawson, R. P., Kim, J.-E., and Schoeberl, M. R.: High-frequency gravity waves and homogeneous ice nucleation in tropical tropopause layer cirrus, Geophys. Res. Lett., 43, 6629–6635, https://doi.org/10.1002/2016GL069426, 2016a. a, b, c · DOI
  30. Jensen, E. J., Ueyama, R., Pfister, L., Bui, T. V., Lawson, R. P., Woods, S., Thornberry, T., Rollins, A. W., Diskin, G. S., DiGangi, J. P., and Avery, M. A.: On the Susceptibility of Cold Tropical Cirrus to Ice Nuclei Abundance, J. Atmos. Sci., 73, 2445–2464, https://doi.org/10.1175/JAS-D-15-0274.1, 2016b. a, b, c, d, e · DOI
  31. Joos, H., Spichtinger, P., Lohmann, U., Gayet, J.-F., and Minikin, A.: Orographic cirrus in the global climate model ECHAM5, J. Geophys. Res.-Atmos., 113, D18205, https://doi.org/10.1029/2007JD009605, 2008. a, b, c, d, e, f · DOI
  32. Joos, H., Spichtinger, P., and Lohmann, U.: Influence of a future climate on the microphysical and optical properties of orographic cirrus clouds in ECHAM5, J. Geophys. Res.-Atmos., 115, D19129, https://doi.org/10.1029/2010JD013824, 2010. a, b, c, d, e, f · DOI
  33. Kanji, Z. A., Ladino, L. A., Wex, H., Boose, Y., Burkert-Kohn, M., Cziczo, D. J., and Krämer, M.: Overview of Ice Nucleating Particles, Meteor. Mon., 58, 1.1–1.33, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0006.1, 2017. a · DOI
  34. Kärcher, B. and Burkhardt, U.: A cirrus cloud scheme for general circulation models, Q. J. Roy. Meteor. Soc., 134, 1439–1461, https://doi.org/10.1002/qj.301, 2008. a · DOI
  35. Kärcher, B. and Lohmann, U.: A parameterization of cirrus cloud formation: Homogeneous freezing of supercooled aerosols, J. Geophys. Res.-Atmos., 107, AAC 4-1–AAC 4-10, https://doi.org/10.1029/2001JD000470, 2002. a, b, c · DOI
  36. Kärcher, B. and Lohmann, U.: A parameterization of cirrus cloud formation: Heterogeneous freezing, J. Geophys. Res.-Atmos., 108, 4402, https://doi.org/10.1029/2002JD003220, 2003. a, b · DOI
  37. 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, e, f, g, h, i, j · DOI
  38. Kärcher, B., DeMott, P. J., Jensen, E. J., and Harrington, J. Y.: Studies on the Competition Between Homogeneous and Heterogeneous Ice Nucleation in Cirrus Formation, J. Geophys. Res.-Atmos., 127, e2021JD035805, https://doi.org/10.1029/2021JD035805, 2022. a · DOI
  39. 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, b, c, d · DOI
  40. Krämer, M., Rolf, C., Luebke, A., Afchine, A., Spelten, N., Costa, A., Meyer, J., Zöger, M., Smith, J., Herman, R. L., Buchholz, B., Ebert, V., Baumgardner, D., Borrmann, S., Klingebiel, M., and Avallone, L.: A microphysics guide to cirrus clouds – Part 1: Cirrus types, Atmos. Chem. Phys., 16, 3463–3483, https://doi.org/10.5194/acp-16-3463-2016, 2016. a, b, c, d, e, f, g, h · DOI
  41. Krämer, M., Rolf, C., Spelten, N., Afchine, A., Fahey, D., Jensen, E., Khaykin, S., Kuhn, T., Lawson, P., Lykov, A., Pan, L. L., Riese, M., Rollins, A., Stroh, F., Thornberry, T., Wolf, V., Woods, S., Spichtinger, P., Quaas, J., and Sourdeval, O.: A microphysics guide to cirrus – Part 2: Climatologies of clouds and humidity from observations, Atmos. Chem. Phys., 20, 12569–12608, https://doi.org/10.5194/acp-20-12569-2020, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w · DOI
  42. Kuebbeler, M., Lohmann, U., and Feichter, J.: Effects of stratospheric sulfate aerosol geo-engineering on cirrus clouds, Geophys. Res. Lett., 39, L23803, https://doi.org/10.1029/2012GL053797, 2012. a, b · DOI · Paper page
  43. Kuebbeler, M., Lohmann, U., Hendricks, J., and Kärcher, B.: Dust ice nuclei effects on cirrus clouds, Atmos. Chem. Phys., 14, 3027–3046, https://doi.org/10.5194/acp-14-3027-2014, 2014. a, b, c, d, e, f, g, h, i, j, k · DOI
  44. Liu, X. and Penner, J. E.: Ice nucleation parameterization for global models, Meteorol. Z., 14, 499–514, https://doi.org/10.1127/0941-2948/2005/0059, 2005. a · DOI
  45. Liu, X., Penner, J. E., Ghan, S. J., and Wang, M.: Inclusion of Ice Microphysics in the NCAR Community Atmospheric Model Version 3 (CAM3), J. Climate, 20, 4526–4547, https://doi.org/10.1175/JCLI4264.1, 2007. a · DOI
  46. Liu, X., Shi, X., Zhang, K., Jensen, E. J., Gettelman, A., Barahona, D., Nenes, A., and Lawson, P.: Sensitivity studies of dust ice nuclei effect on cirrus clouds with the Community Atmosphere Model CAM5, Atmos. Chem. Phys., 12, 12061–12079, https://doi.org/10.5194/acp-12-12061-2012, 2012. a · DOI
  47. Lohmann, U. and Diehl, K.: Sensitivity Studies of the Importance of Dust Ice Nuclei for the Indirect Aerosol Effect on Stratiform Mixed-Phase Clouds, J. Atmos. Sci., 63, 968–982, https://doi.org/10.1175/JAS3662.1, 2006. a · DOI
  48. Lohmann, U. and Ferrachat, S.: Impact of parametric uncertainties on the present-day climate and on the anthropogenic aerosol effect, Atmos. Chem. Phys., 10, 11373–11383, https://doi.org/10.5194/acp-10-11373-2010, 2010. a · DOI
  49. Lohmann, U. and Gasparini, B.: A cirrus cloud climate dial?, Science, 357, 248–249, https://doi.org/10.1126/science.aan3325, 2017. a · DOI
  50. Lohmann, U. and Kärcher, B.: First interactive simulations of cirrus clouds formed by homogeneous freezing in the ECHAM general circulation model, J. Geophys. Res.-Atmos., 107, AAC 8-1–AAC 8-13, https://doi.org/10.1029/2001JD000767, 2002. a · DOI
  51. Lohmann, U., Stier, P., Hoose, C., Ferrachat, S., Kloster, S., Roeckner, E., and Zhang, J.: Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM, Atmos. Chem. Phys., 7, 3425–3446, https://doi.org/10.5194/acp-7-3425-2007, 2007. a, b, c, d · DOI
  52. Lohmann, U., Spichtinger, P., Jess, S., Peter, T., and Smit, H.: Cirrus cloud formation and ice supersaturated regions in a global climate model, Environ. Res. Lett., 3, 045022, https://doi.org/10.1088/1748-9326/3/4/045022, 2008. a, b, c · DOI
  53. Lohmann, U., Lüönd, F., and Mahrt, F.: An Introduction to Clouds: From the Microscale to Climate, Cambridge University Press, https://doi.org/10.1017/CBO9781139087513, 2016. a · DOI
  54. Lohmann, U., Friebel, F., Kanji, Z., Mahrt, F., Mensah, A., and Neubauer, D.: Future warming exacerbated by aged-soot effect on cloud formation, Nat. Geosci., 13, 674–680, https://doi.org/10.1038/s41561-020-0631-0, 2020. a, b · DOI
  55. Mahrt, F., Marcolli, C., David, R. O., Grönquist, P., Barthazy Meier, E. J., 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 · DOI
  56. 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 · DOI · Paper page
  57. Mauritsen, T., Stevens, B., Roeckner, E., Crueger, T., Esch, M., Giorgetta, M., Haak, H., Jungclaus, J., Klocke, D., Matei, D., Mikolajewicz, U., Notz, D., Pincus, R., Schmidt, H., and Tomassini, L.: Tuning the climate of a global model, J. Adv. Model. Earth Syst., 4, M00A01, https://doi.org/10.1029/2012MS000154, 2012. a, b · DOI
  58. Mitchell, D. L., Rasch, P., Ivanova, D., McFarquhar, G., and Nousiainen, T.: Impact of small ice crystal assumptions on ice sedimentation rates in cirrus clouds and GCM simulations, Geophys. Res. Lett., 35, L09806, https://doi.org/10.1029/2008GL033552, 2008. a · DOI
  59. 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 · DOI
  60. 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 · DOI
  61. Morrison, H. and Milbrandt, J. A.: Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part I: Scheme Description and Idealized Tests, J. Atmos. Sci., 72, 287–311, https://doi.org/10.1175/JAS-D-14-0065.1, 2015. a, b, c · DOI
  62. Muench, S. and Lohmann, U.: Developing a Cloud Scheme With Prognostic Cloud Fraction and Two Moment Microphysics for ECHAM-HAM, J. Adv. Model. Earth Syst., 12, e2019MS001824, https://doi.org/10.1029/2019MS001824, 2020. a, b, c, d, e, f, g, h, i · DOI
  63. Muri, H., Kristjánsson, J. E., Storelvmo, T., and Pfeffer, M. A.: The climatic effects of modifying cirrus clouds in a climate engineering framework, J. Geophys. Res.-Atmos., 119, 4174–4191, https://doi.org/10.1002/2013JD021063, 2014. a · DOI · Paper page
  64. Murphy, D. M.: Effect of Stratospheric Aerosols on Direct Sunlight and Implications for Concentrating Solar Power, Environ. Sci. Technol., 43, 2784–2786, https://doi.org/10.1021/es802206b, 2009. a · DOI
  65. Murray, B. J., O'Sullivan, D., Atkinson, J. D., and Webb, M. E.: Ice nucleation by particles immersed in supercooled cloud droplets, Chem. Soc. Rev., 41, 6519–6554, https://doi.org/10.1039/C2CS35200A, 2012. a · DOI
  66. Neubauer, D., Lohmann, U., Hoose, C., and Frontoso, M. G.: Impact of the representation of marine stratocumulus clouds on the anthropogenic aerosol effect, Atmos. Chem. Phys., 14, 11997–12022, https://doi.org/10.5194/acp-14-11997-2014, 2014. a · DOI
  67. Neubauer, D., Ferrachat, S., Siegenthaler-Le Drian, C., Stier, P., Partridge, D. G., Tegen, I., Bey, I., Stanelle, T., Kokkola, H., and Lohmann, U.: The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 2: Cloud evaluation, aerosol radiative forcing, and climate sensitivity, Geosci. Model Dev., 12, 3609–3639, https://doi.org/10.5194/gmd-12-3609-2019, 2019. a, b, c, d, e, f · DOI
  68. Pelucchi, P., Neubauer, D., and Lohmann, U.: Vertical grid refinement for stratocumulus clouds in the radiation scheme of the global climate model ECHAM6.3-HAM2.3-P3, Geosci. Model Dev., 14, 5413–5434, https://doi.org/10.5194/gmd-14-5413-2021, 2021. a · DOI
  69. Penner, J. E., Zhou, C., and Liu, X.: Can cirrus cloud seeding be used for geoengineering?, Geophys. Res. Lett., 42, 8775–8782, https://doi.org/10.1002/2015GL065992, 2015. a, b, c, d, e, f, g, h, i · DOI
  70. Possner, A., Ekman, A. M. L., and Lohmann, U.: Cloud response and feedback processes in stratiform mixed-phase clouds perturbed by ship exhaust, Geophys. Res. Lett., 44, 1964–1972, https://doi.org/10.1002/2016GL071358, 2017. a · DOI
  71. Rind, D. and Lonergan, P.: Modeled impacts of stratospheric ozone and water vapor perturbations with implications for high-speed civil transport aircraft, J. Geophys. Res.-Atmos., 100, 7381–7396, https://doi.org/10.1029/95JD00196, 1995. a · DOI
  72. Rind, D., Lerner, J., and McLinden, C.: Changes of tracer distributions in the doubled CO2 climate, J. Geophys. Res.-Atmos., 106, 28061–28079, https://doi.org/10.1029/2001JD000439, 2001. a · DOI
  73. Robock, A.: Volcanic eruptions and climate, Rev. Geophys., 38, 191–219, https://doi.org/10.1029/1998RG000054, 2000. a · DOI · Paper page
  74. Robock, A., Jerch, K., and Bunzl, M.: 20 reasons why geoengineering may be a bad idea, B. Atom. Sci., 64, 14–59, https://doi.org/10.1080/00963402.2008.11461140, 2008. a · DOI
  75. Shi, X., Liu, X., and Zhang, K.: Effects of pre-existing ice crystals on cirrus clouds and comparison between different ice nucleation parameterizations with the Community Atmosphere Model (CAM5), Atmos. Chem. Phys., 15, 1503–1520, https://doi.org/10.5194/acp-15-1503-2015, 2015. a · DOI
  76. Slingo, J. M.: The Development and Verification of A Cloud Prediction Scheme For the Ecmwf Model, Q. J. Roy. Meteor. Soc., 113, 899–927, https://doi.org/10.1002/qj.49711347710, 1987. a · DOI
  77. Sourdeval, O., Gryspeerdt, E., Krämer, M., Goren, T., Delanoë, J., Afchine, A., Hemmer, F., and Quaas, J.: Ice crystal number concentration estimates from lidar–radar satellite remote sensing – Part 1: Method and evaluation, Atmos. Chem. Phys., 18, 14327–14350, https://doi.org/10.5194/acp-18-14327-2018, 2018. a, b, c, d, e, f · DOI
  78. Spichtinger, P. and Cziczo, D. J.: Impact of heterogeneous ice nuclei on homogeneous freezing events in cirrus clouds, J. Geophys. Res.-Atmos., 115, D14208, https://doi.org/10.1029/2009JD012168, 2010. a · DOI
  79. Stephens, G. L., Tsay, S.-C., Stackhouse, P. W., and Flatau, P. J.: The Relevance of the Microphysical and Radiative Properties of Cirrus Clouds to Climate and Climatic Feedback, J. Atmos. Sci., 47, 1742–1754, https://doi.org/10.1175/1520-0469(1990)047<1742:TROTMA>2.0.CO;2, 1990. a · DOI
  80. Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the MPI-M Earth System Model: ECHAM6, J. Adv. Model. Earth Syst., 5, 146–172, https://doi.org/10.1002/jame.20015, 2013. a, b, c · DOI
  81. Stier, P., Feichter, J., Kinne, S., Kloster, S., Vignati, E., Wilson, J., Ganzeveld, L., Tegen, I., Werner, M., Balkanski, Y., Schulz, M., Boucher, O., Minikin, A., and Petzold, A.: The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys., 5, 1125–1156, https://doi.org/10.5194/acp-5-1125-2005, 2005. a, b · DOI
  82. Storelvmo, T. and Herger, N.: Cirrus cloud susceptibility to the injection of ice nuclei in the upper troposphere, J. Geophys. Res.-Atmos., 119, 2375–2389, https://doi.org/10.1002/2013JD020816, 2014. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p · DOI · Paper page
  83. Storelvmo, T., Kristjansson, J. E., Muri, H., Pfeffer, M., Barahona, D., and Nenes, A.: Cirrus cloud seeding has potential to cool climate, Geophys. Res. Lett., 40, 178–182, https://doi.org/10.1029/2012GL054201, 2013. a, b, c, d, e, f, g, h, i, j, k · DOI
  84. Storelvmo, T., Boos, W. R., and Herger, N.: Cirrus cloud seeding: a climate engineering mechanism with reduced side effects?, Philos. T. Roy. Soc. A, 372, 20140116, https://doi.org/10.1098/rsta.2014.0116, 2014. a, b, c, d, e, f, g, h, i · DOI · Paper page
  85. Sundqvist, H., Berge, E., and Kristjánsson, J. E.: Condensation and Cloud Parameterization Studies with a Mesoscale Numerical Weather Prediction Model, Mon. Weather Rev., 117, 1641–1657, https://doi.org/10.1175/1520-0493(1989)117<1641:CACPSW>2.0.CO;2, 1989. a, b, c, d · DOI
  86. Tegen, I., Neubauer, D., Ferrachat, S., Siegenthaler-Le Drian, C., Bey, I., Schutgens, N., Stier, P., Watson-Parris, D., Stanelle, T., Schmidt, H., Rast, S., Kokkola, H., Schultz, M., Schroeder, S., Daskalakis, N., Barthel, S., Heinold, B., and Lohmann, U.: The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 1: Aerosol evaluation, Geosci. Model Dev., 12, 1643–1677, https://doi.org/10.5194/gmd-12-1643-2019, 2019. a, b · DOI
  87. Ullrich, R., Hoose, C., Möhler, O., Niemand, M., Wagner, R., Höhler, K., Hiranuma, N., Saathoff, H., and Leisner, T.: A New Ice Nucleation Active Site Parameterization for Desert Dust and Soot, J. Atmos. Sci., 74, 699–717, https://doi.org/10.1175/JAS-D-16-0074.1, 2017. a · DOI
  88. 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 · DOI · Paper page
  89. Vaughan, N. E. and Lenton, T. M.: A review of climate geoengineering proposals, Climate Change, 109, 745–790, https://doi.org/10.1007/s10584-011-0027-7, 2011. a, b · DOI · Paper page
  90. Villanueva, D., Neubauer, D., Gasparini, B., Ickes, L., and Tegen, I.: Constraining the Impact of Dust-Driven Droplet Freezing on Climate Using Cloud-Top-Phase Observations, Geophys. Res. Lett., 48, e2021GL092687, https://doi.org/10.1029/2021GL092687, 2021. a, b · DOI
  91. Wilks, D. S.: 11The Stippling Shows Statistically Significant Grid Points”: How Research Results are Routinely Overstated and Overinterpreted, and What to Do about It, B. Am. Meteorol. Soc., 97, 2263–2273, https://doi.org/10.1175/BAMS-D-15-00267.1, 2016. a, b · DOI
  92. Zhang, K., O'Donnell, D., Kazil, J., Stier, P., Kinne, S., Lohmann, U., Ferrachat, S., Croft, B., Quaas, J., Wan, H., Rast, S., and Feichter, J.: The global aerosol-climate model ECHAM-HAM, version 2: sensitivity to improvements in process representations, Atmos. Chem. Phys., 12, 8911–8949, https://doi.org/10.5194/acp-12-8911-2012, 2012. a, b · DOI

Authors
Tully, C., Neubauer, D., Omanovic, N., & Lohmann, U.
Affiliations
ETH Zurich (CH)
Corresponding author
  • Tully, Colin
  • Neubauer, David
  • Lohmann, Ulrike
ORCID
Venue
Atmospheric Chemistry and Physics
Publisher
Copernicus GmbH
Published
2022-09-07
Volume
22
Issue
17
Pages
11455-11484
ISSN
  • 1680-7316 (ISSN-L)
  • 1680-7324
DOI
10.5194/acp-22-11455-2022
OpenAlex
W4297826325
Cited by
26
References
97
Citations by year
2026: 3 · 2025: 8 · 2024: 7 · 2023: 4 · 2022: 4
FWCI
2.29
Type
journal article
Language
en
Open access
Licence
Locations
  • Atmospheric chemistry and physics (publishedVersion, cc-by)
  • Repository for Publications and Research Data (ETH Zurich) (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • ETH Zürich Research Collection
Funders
  • Horizon 2020 Framework Programme
  • Centro Svizzero di Calcolo Scientifico (s903, s1144)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric aerosols and clouds
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate Change and Geoengineering
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
Keywords
cirrus cloud thinning, radiation management, ice microphysics, ECHAM-HAM, cloud fraction, relative humidity threshold, ice nucleation, homogeneous nucleation, heterogeneous nucleation, mineral dust, ice crystal size, climate warming mitigation, radiative forcing

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review