Research Group
Clouds and Global Climate

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Die The research group "Clouds and global climate" uses and analyses climate models and satellite observations for a better anderstanding of cloud-climate feedbacks and the effect of anthropogenic aerosols on clouds and climate.


From outside the University, please add (0341) 97- as a prefix to the numbers. For international calls, please add +49 341 97-. The adress is Vor dem Hospitaltore 1 (first floor), D-04103 Leipzig Internal mail box no 232112; fax +49 341 97 31949

Scientific Staff

Name Room Phone E-Contact
Block, Karoline PhD Student 116r 32939 E-Mail, WWW
Cherian, Dr. Ribu Scientist 119r 32933 E-Mail, WWW
Goren, Dr. Tom Scientist 118r 32936 E-Mail, WWW
Kretzschmar, Jan PhD Student 115r 32941 E-Mail, WWW
Mülmenstädt, Dr. Johannes Scientist 117r 32937 E-Mail, WWW
Nair, Aswathy PhD Student 115r 32941 E-Mail, WWW
Nam, Dr. Christine Scientist in 118r 32935 E-Mail, WWW
Quaas, Prof. Johannes Professor 121r 32931, 32852 E-Mail, WWW
Salzmann, Dr. Marc Assistant professor 120r 32932 E-Mail, WWW
Sourdeval, Dr. Odran Scientist 117r 32938 E-Mail, WWW
Sudhakar, Dr. Dipu Scientist 119r 32934 E-Mail, WWW
Unglaub, Claudia PhD Student 116r 32940 E-Mail, WWW


Name Room Phone E-Contact
Hörnig, Sabine Student assistant   113r 32944  
Jungandreas, Leonore Student assistant   113r 32944  
Strehl, Pit Master's student   113r 32944  
Böhm, Christoph Master's student   113r 32944  
Hermes, Kilian Bachelor's student   113r 32944  
Metzner, Enrico Bachelor's student   113r 32944  
Sattig, Gabriel Bachelor's student   113r 32944  


Name Neue Stelle
Brueck, Matthias Max-Planck-Institut für Meteorologie
Gryspeerdt, Edward Imperial College London
Aswathy Nair Maternity leave, India


Brueck, M., J. Quaas, J.-C. Golaz, and H. Guo, Importance of subgrid temperature variability in cloud parameterizations, Mon. Wea. Rev., in revision.

Cherian, R., J. Quaas, M. Salzmann, and L. Tomassini, Black carbon indirect radiative effects in a climate model, Tellus, revised.

Jing, Xianwen, Kentaroh Suzuki, H. Guo, D Goto, Tomo'o Ogura, Tsuyoshi Koshiro, and J. Mülmenstädt, A multi-model study on warm precipitation biases in global models compared to satellite observations, J. Geophys. Res., submitted.

Schemann, V., and J. Quaas, Improving the representation of subgrid-scale variability of total water in GCMs., J. Adv. Model. Earth Syst., in revision.

White, Bethan, Edward Gryspeerdt, P. Stier, Hugh Morisson, and Gregory Thompson, Can models robustly represent aerosolâ, Atmos.Chem. Phys. Discuss, submitted, doi:10.5194/acp-2016-760.

70. Dipu S., , J. Quaas, R. Wolke, J. Stoll, A. Muhlbauer, M. Salzmann, B. Heinold, and Ina Tegen, Implementation of aerosol-cloud interactions in the regional atmosphere-aerosol model COSMO-MUSCAT and evaluation using satellite data, Geosci. Model Devel., 10, 2231-2246, doi:10.5194/gmd-10-2231-2017, 2017.

69. Gryspeerdt, Edward, J. Quaas, S. Ferrachat, A. Gettelman, S. Ghan, U. Lohmann, H. Morrison, D. Neubauer, D. G. Partridge, P. Stier, T. Takemura, Hailong Wang, M. Wang, and K. Zhang, Constraining the instantaneous aerosol influence on cloud albedo, Proc. Nat. Acad. Sci. USA, 119, 4899-4904, doi:10.1073/pnas.1617765114, 2017.

68. Heinze, R., A. Dipankar, C. Carbajal Henken, C. Moseley, O. Sourdeval, S. Trömel, X. Xie, P. Adamidis, F. Ament, H. Baars, C. Barthlott, A. Behrendt, U. Blahak, S. Bley, Slavko Brdar, M. Brueck, Susanne Crewell, H. Deneke, P. Di Girolamo, R. Evaristo, J. Fischer, C. Frank, P. Friederichs, T. Göcke, K. Gorges, L. Hande, M. Hanke, A. Hansen, H.-C. Hege, C. Hoose, T. Jahns, N. Kalthoff, D. Klocke, S. Kneifel, P. Knippertz, A. Kuhn, T. Laar, Andreas Macke, V. Maurer, B. Mayer, C. I. Meyer, S. K. Muppa, R. A. J. Neggers, E. Orlandi, F. Pantillon, B. Pospichal, N. Röber, L. Scheck, A. Seifert, P. Seifert, F. Senf, P. Siligam, C. Simmer, S. Steinke, B. Stevens, K. Wapler, M. Weniger, V. Wulfmeyer, G. Zängl, D. Zhang, and J. Quaas, Large-eddy simulations over Germany using ICON: A comprehensive evaluation, Quart. J. Roy. Meteorol. Soc., 143, 69-100, doi:10.1002/qj.2947, 2017.

67. Heyn, I., K. Block, J. Mülmenstädt, Edward Gryspeerdt, P. Kühne, M. Salzmann, and J. Quaas, Assessment of simulated aerosol effective radiative forcings in the terrestrial spectrum, Geophys. Res. Lett., 44, 1001-1007, doi:10.1002/2016GL071975, 2017.

66. Heyn, I., M. Salzmann, J. Quaas, and J. Mülmenstädt, Effects of diabatic and adiabatic processes on relative humidity in a GCM, and relationship between mid-tropospheric vertical wind and cloud-forming and cloud-dissipating processes, Tellus, 69, 1272753, doi:10.1080/16000870.2016.1272753, 2017.

65. Kretzschmar, Jan, M. Salzmann, J. Mülmenstädt, O. Boucher, and J. Quaas, Comment on ``Rethinking the lower bound on aerosol radiative forcing'', J. Climate, in press, doi:10.1175/JCLI-D-16-0668.1, 2017.

64. Myhre, G., W. Aas, R. Cherian, W. Collins, G. Faluvegi, M. Flanner, P. Forster, Ø. Hodnebrog, Z. Klimont, J. Mülmenstädt, C. Lund Myhre, D. Olivié, M. Prather, J. Quaas, B. H. Samset, J. L. Schnell, M. Schulz, D. Shindell, R. B. Skeie, T. Takemura, and S Tsyro, Multi-model simulations of aerosol and ozone radiative forcing for the period 1990-2015, Atmos. Chem. Phys., 17, 2709-2720, doi:10.5194/acp-17-2709-2017, 2017.

63. Patel, P., J. Quaas, and R. Kumar, A new statistical approach to improve the satellite based estimation of the radiative forcing by aerosol- cloud interactions, Atmos. Chem. Phys., 17, 3687-3698, doi:10.5194/acp-17-3687-2017, 2017.

62. Quaas, M. F., J. Quaas, W. Rickels, and O. Boucher, Are there good reasons against research into solar radiation management? - A model of intergenerational decision-making under uncertainty, J. Environ. Econ. Manage., 84, 1-17, doi:10.1016/j.jeem.2017.02.002, 2017.

61. Salzmann, M., The polar amplification asymmetry: Role of antarctic surface height, Earth Syst. Dynam., 8, 323--336, doi:doi:10.5194/esd-8-323-2017, 2017.

60. Wendisch, Manfred, Marlen Brückner, John Burrows, Susanne Crewell, Klaus Dethloff, Kerstin Ebell, Christof Lüpkes, Andreas Macke, Justus Notholt, J. Quaas, Annette Rinke, and Ina Tegen, The Arctic Amplifier - Novel Science Planned in a New German Research Initiative, EOS, 98, doi:10.1029/2017EO064803, 2017.

59. Baraskar, A., M. Bhushan, C. Venkataraman, and R. Cherian, An offline constrained data assimilation technique for aerosols: Improving GCM simulations over South Asia using observations from two satellite sensors, Atmos. Environ., 132, 36 - 48, doi:10.1016/j.atmosenv.2016.02.026, 2016.

58. Bellouin, N., L. Baker, Ø. Hodnebrog, D. Olivié, R. Cherian, C. Macintosh, B. Samset, A. Esteve, B. Aamaas, J. Quaas, and G. Myhre, Regional and seasonal radiative forcing by perturbations to aerosol and ozone precursor emissions, Atmos. Chem. Phys., 16, 13885-13910, doi:10.5194/acp-16-13885-2016, 2016.

57. Boucher, O., Y. Balkanski, Ø. Hodnebrog, C. Lund Myhre, G. Myhre, J. Quaas, B. H. Samset, N Schutgens, P. Stier, and R. Wang, The jury is still out on the radiative forcing by black carbon, Proc. Nat. Acad. Sci. USA, 113, E5092-E5093, doi:10.1073/pnas.1607005113, 2016.

56. Gross, A, B. L. Turner, Tom Goren, A. Berry, and A Angert, Tracing the Sources of Atmospheric Phosphorus Deposition to a Tropical Rain Forest in Panama Using Stable Oxygen Isotopes, Environ. Sci. Technol., 50, 1147-1156, doi:10.1021/acs.est.5b04936, 2016.

55. Gryspeerdt, Edward, J. Quaas, and N. Bellouin, Constraining the aerosol influence on cloud fraction, J. Geophys. Res., 121, 3566-3583, doi:10.1002/2015JD023744, 2016.

54. Kedia, S., R. Cherian, S. Islam, S. K. Das, and A. Kaginalkar, Regional simulation of aerosol radiative effects and their influence on rainfall over India using WRFChem model, Atmos. Res., 182, 232 - 242, doi:10.1016/j.atmosres.2016.07.008, 2016.

53. Quaas, J., M. F. Quaas, O. Boucher, and W. Rickels, Regional climate engineering by radiation management: Prerequisites and prospects, Earth's Future, 4, 618-625, doi:10.1002/2016EF000440, 2016.

52. Quennehen, B., J.-C. Raut, K. S. Law, N. Daskalakis, G. Ancellet, C. Clerbaux, S.-W. Kim, M. T. Lund, G. Myhre, D. J. L. Olivié, S. Safieddine, R. B. Skeie, J. L. Thomas, S Tsyro, A. Bazureau, N. Bellouin, M. Hu, M. Kanakidou, Z. Klimont, K. Kupiainen, S. Myriokefalitakis, J. Quaas, S. T. Rumbold, M. Schulz, R. Cherian, A. Shimizu, J. Wang, S.-C. Yoon, and T. Zhu, Multi-model evaluation of short-lived pollutant distributions over East Asia during summer 2008, Atmos. Chem. Phys. , 16, 10765-10792, doi:10.5194/acp-16-10765-2016, 2016.

51. Sadavarte, P., C. Venkataraman, R. Cherian, N. Patil, B.L. Madhavan, T. Gupta, S. Kulkarni, G. R. Carmichael, and B. Adhikary, Seasonal differences in aerosol abundance and radiative forcing in months of contrasting emissions and rainfall over northern South Asia, Atmos. Environ., 125, Part B, 512 - 523, doi:10.1016/j.atmosenv.2015.10.092, 2016.

50. Salzmann, M., Global warming without global mean precipitation increase?, Sci. Adv., 2, e1501572, doi:10.1126/sciadv.1501572, 2016.

49. Schutgens, N, Edward Gryspeerdt, N. Weigum, S Tsyro, D Goto, M. Schulz, and P. Stier, Will a perfect model agree with perfect observations? The impact of spatial sampling., Atmos. Chem. Phys., doi:10.5194/acp-16-6335-2016, 2016.

48. Sourdeval, O., L.-C. Labonnote, A. J. Baran, J. Mülmenstädt, and G. Brogniez, A methodology for simultaneous retrieval of ice and liquid water cloud properties. Part 2: Near-global retrievals and evaluation against A-Train products, Q. J. R. Meteorol. Soc., 142, 3063-3081, doi:10.1002/qj.2889, 2016.

47. Watson-Parris, D, N Schutgens, N Cook, Z Kipling, P Kerhsaw, Edward Gryspeerdt, B Lawrence, and P. Stier, Community Intercomparison Suite (CIS) v1.4.0: A tool for intercomparing models and observations, Geosci. Model Dev., 9, doi:10.5194/gmd-9-3093-2016, 2016.

46. Aswathy, V. N., O. Boucher, M. Quaas, U. Niemeier, H. Muri, J. Mülmenstädt, and J. Quaas, Climate extremes in multi-model simulations of stratospheric aerosol- and marine cloud brightening climate engineering, Atmos. Chem. Phys., 15, 9593-9610, doi:10.5194/acp-15-9593-2015, 2015.

45. Baker, L. H., W. J. Collins, D. J. L. Olivié, R. Cherian, Ø. Hodnebrog, G. Myhre, and J. Quaas, Climate responses to anthropogenic emissions of short-lived climate pollutants, Atmos. Chem. Phys., 15, 8201-8216, doi:10.5194/acp-15-8201-2015, 2015.

44. Eckhardt, S., B. Quennehen, D. J. L. Olivié, T. K. Berntsen, R. Cherian, J.H. Christensen, W. Collins, S. Crepinsek, N. Daskalakis, M. Flanner, A. Herber, C. Heyes, Ø. Hodnebrog, L. Huang, M. Kanakidou, Z. Klimont, J. Langner, K. S. Law, M. T. Lund, R. Mahmood, A. Massling, S. Myriokefalitakis, I.E. Nielsen, J.K. Nøjgaard, J. Quaas, P.K. Quinn, J.-C. Raut, S. T. Rumbold, M. Schulz, S. Sharma, R. B. Skeie, H. Skov, T. Uttal, K. Salzen, and A. Stohl, Current model capabilities for simulating black carbon and sulfate concentrations in the Arctic atmosphere: a multi-model evaluation using a comprehensive measurement data set, Atmos. Chem. Phys., 15, 9413-9433, doi:10.5194/acp-15-9413-2015, 2015.

43. Gryspeerdt, Edward, P. Stier, B. A. White, and Z Kipling, Wet scavenging limits the detection of aerosol effects on precipitation, Atmos. Chem. Phys., 15, 7557-7570, doi:10.5194/acp-15-7557-2015, 2015.

42. Mülmenstädt, J., O. Sourdeval, J. Delanoë, and J. Quaas, Frequency of occurrence of rain from liquid-, mixed- and ice-phase clouds derived from A-Train satellite retrievals, Geophys. Res. Lett., 42, 6502-6509, doi:10.1002/2015GL064604, 2015.

41. Quaas, J., Approaches to observe effects of anthropogenic aerosols on clouds and radiation, Current Climate Change Reports, 1, 297-304, doi:10.1007/s40641-015-0028-0, 2015.

40. Quaas, J., and P. Stier, Satellite observations of convection and their implications for parameterizations, Parameterization of Atmospheric Convection, Vol. 2: Current Issues and New Theories, World Scientific Publishing, ISBN 978-1-78326-690-6, 47-58, doi:10.1142/9781783266913_0019, 2015.

39. Rosch, J., T. Heus, H. M. Brueck, M. Salzmann, J. Mülmenstädt, L. Schlemmer, and J. Quaas, Analysis of diagnostic climate model cloud parameterisations using large-eddy simulations, Q. J. R. Meteorol. Soc., 141, 2199-2205, doi:10.1002/qj.2515, 2015.

38. Salzmann, M., and R. Cherian, On the enhancement of the Indian summer monsoon drying by Pacific multidecadal variability during the latter half of the 20th century, J. Geophys. Res. Atmos., 120, 9103-9118, doi:10.1002/2015JD023313, 2015.

37. Stohl, A., B. Aamaas, M. Amann, L. H. Baker, N. Bellouin, T. K. Berntsen, O. Boucher, R. Cherian, W. Collins, N. Daskalakis, M. Dusinska, S. Eckhardt, J. S. Fuglestvedt, M. Harju, C. Heyes, Ø. Hodnebrog, J. Hao, U. Im, M. Kanakidou, Z. Klimont, K. Kupiainen, K. S. Law, M. T. Lund, R. Maas, C. R. MacIntosh, G. Myhre, S. Myriokefalitakis, D. J. Olivie, J. Quaas, B. Quennehen, J.-C. Raut, S. Rumbold, B. H. Samset, M. Schulz, Ø. Seland, K. P. Shine, R. B. Skeie, S. Wang, K. E. Yttri, and T. Zhu, Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants, Atmos. Chem. Phys., 15, 10529-10566, doi:10.5194/acp-15-10529-2015, 2015.

36. Cherian, R., J. Quaas, M. Salzmann, and M. Wild, Pollution trends over Europe constrain global aerosol forcing as simulated by climate models, Geophys. Res. Lett., 41, 2176-2181, doi:10.1002/2013GL058715, 2014.

35. Ma, X., F. Yu, and J. Quaas, Reassessment of satellite-based estimate of aerosol-climate forcing, J. Geophys. Res., 119, 10394-10409, doi:10.1002/2014JD021670, 2014.

34. Nam, C., J. Quaas, R. Neggers, C. Siegenthaler-Le Drian, and F. Isotta, Evaluation of boundary layer cloud parameterizations in the ECHAM5 general circulation model using CALIPSO and CloudSat satellite data, J. Adv. Model. Earth Syst., 6, 300-314, doi:10.1002/2013MS000277, 2014.

33. Peters, K., J. Quaas, P. Stier, and H. Graßl, Processes limiting the emergence of detectable aerosol indirect effects on tropical warm clouds in global aerosol-climate model and satellite data, Tellus B, 66, 24054, doi:10.3402/tellusb.v66.24054, 2014.

32. Rosenfeld, D., M. O. Andreae, A. Asmi, M. Chin, G. Leeuw, D. P. Donovan, R. Kahn, S. Kinne, N. Kivekäs, M. Kulmala, W. Lau, S. Schmidt, T. Suni, T. Wagner, M. Wild, and J. Quaas, Global observations of aerosol-cloud-precipitation-climate interactions, Reviews Geophys., 52, 750-808, doi:10.1002/2013RG000441, 2014.

31. Salzmann, M., H. Weser, and R. Cherian, Robust response of Asian summer monsoon to anthropogenic aerosols in CMIP5 models, J. Geophys. Res. Atmos., 119, 11321â, doi:10.1002/2014JD021783, 2014.

30. Sourdeval, O., L.-C. Labonnote, A. J. Baran, and G. Brogniez, A methodology for simultaneous retrieval of ice and liquid water cloud properties. I: Information content and case study, doi:10.1002/qj.2405, 2014.

29. Yano, J.-I., J.-F. Geleyn, M. Köhler, D. Mironov, J. Quaas, P. Soares, V. T. J. Phillips, R. S. Plant, A. Deluca, P. Marquet, L. Stulic, and Z. Fuchs, Basic concepts for convection parameterization in weather forecast and climate models: COST Action ES0905 final report, Atmosphere, 6, 88-147, doi:10.3390/atmos6010088, 2014.

28. Bellouin, N., J. Quaas, J.-J. Morcrette, and O. Boucher, Estimates of aerosol radiative forcing from the MACC re-analysis, Atmos. Chem. Phys., 13, 2045-2062, doi:10.5194/acp-13-2045-2013, 2013.

27. Block, K., and T. Mauritsen, Feedback and Forcing in the MPI-ESM-LR coupled model under abruptly quadrupled CO2, J. Adv. Model. Earth Syst., 5, doi:10.1002/jaime20041, 2013.

26. Boucher, O., and J. Quaas, Water vapour affects both rain and aerosol optical depth, Nature Geosci., 6, 4-5, doi:10.1038/ngeo1692, 2013.

25. Cherian, R., C. Venkataraman, J. Quaas, and S. Ramachandran, GCM simulations of aerosol extinction, heating and effects on precipitation over India, J. Geophys. Res., 118, 2938-2955, doi:10.1002/jgrd.50298, 2013.

24. Grützun, V., J. Quaas, F. Ament, and C. Morcrette, Evaluating statistical cloud schemes - what can we gain from ground based remote sensing?, J. Geophys. Res., 118, 10507-10517, doi:10.1002/jgrd.50813, 2013.

23. Klocke, D., J. Quaas, and B. Stevens, Assessment of different metrics for physical climate feedbacks, Clim. Dyn., 41, 1173-1185, doi:10.1007/s00382-013-1757-1, 2013.

22. Nam, C., and J. Quaas, Geographical versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterisations, Geophys. Res. Lett., 40, 4951-4956, doi:10.1002/grl.50945, 2013.

21. Randles, C. A., S. Kinne, G. Myhre, M. Schulz, P. Stier, J. Fischer, L. Doppler, E. Highwood, C. Ryder, B. Harris, J. Huttunen, Y. Ma, R. T. Pinker, B. Mayer, D. Neubauer, R. Hitzenberger, L. Oreopoulos, D. Lee, G. Pitari, G. Di Genova, J. Quaas, F. G. Rose, S. Kato, S. T. Rumbold, I. Vardavas, N. Hatzianastassiou, C. Matsoukas, H. Yu, H. Zhang, and P. Lu, Intercomparison of shortwave radiative transfer schemes in global aerosol modeling: Results from the AeroCom Radiative Transfer Experiment, Atmos. Chem. Phys., 13, 2347-2379, doi:10.5194/acp-13-2347-2013, 2013.

20. Rennó, N. O., E. Williams, D. Rosenfeld, D. G. Fischer, J. Fischer, T. Kremic, A. Agrawal, M. O. Andreae, R. Bierbaum, R. Blakeslee, A. Boerner, N. Bowles, H. Christian, A. Cox, J. Dunion, Á. Horváth, X. Huang, A. Khain, S. Kinne, M. C. Lemos, J. Penner, U. Pöschl, J. Quaas, E. Seran, B. Stevens, T. Walati, and T. Wagner, CHASER: An Innovative Satellite Mission Concept to Measure the Effects of Aerosols on Clouds and Climate, Bull. Amer. Meteor. Soc., 94, 685-694, doi:10.1175/BAMS-D-11-00239, 2013.

19. Schemann, V., B. Stevens, V. Grützun, and J. Quaas, Scale dependency of total water variance, and its implication for cloud parameterizations, J. Atmos. Sci., 70, 3615-3630, doi:10.1175/JAS-D-13-09.1, 2013.

18. Schirber, S., D. Klocke, R. Pincus, J. Quaas, and J. Anderson, Parameter estimation using data assimilation in an atmospheric general circulation model: From a perfect towards the real world, J. Adv. Model. Earth Syst., 5, 58-70, doi:10.1029/2012MS000167, 2013.

17. Schneider, N., J. Quaas, M. Claussen, and C. Reick, Satellite-based analysis of clouds and radiation properties of different vegetation types in the Brazilian Amazon region, AIP Conf. Proc. 1531, 428, doi:10.1063/1.4804798, 2013.

16. Stevens, B., M. Giorgetta, M. Esch, T. Mauritsen, T. Crueger, S. Rast, M. Salzmann, H. Schmidt, J. Bader, K. Block, R. Brokopf, I. Fast, S. Kinne, L. Kornblueh, U. Lohmann, R. Pincus, R. Reichler, and E. Roeckner, Atmospheric component of the MPI-M Earth System Model: ECHAM6, J. Adv. Model. Earth Syst., 5, 146-172, doi:10.1002/jame.20015, 2013.

15. Tomassini, L., O. Geoffroy, J.-L. Dufresne, A. Idelkadi, C. Cagnazzo, K. Block, T. Mauritsen, M. Giorgetta, and J. Quaas, The respective roles of surface temperature driven feedbacks and tropospheric adjustment to CO2 in CMIP5 transient climate simulations, Clim. Dyn., 41, 3103-3126, doi:10.1007/s00382-013-1682-3, 2013.

14. Cherian, R., C. Venkataraman, S. Ramachandran, J. Quaas, and S. Kedia, Examination of aerosol distributions and radiative effects over the Bay of Bengal and the Arabian Sea region during ICARB using satellite data and a general circulation model, Atmos. Chem. Phys., 12, 1287-1305, doi:10.5194/acp-12-1287-2012, 2012.

13. Devasthale, A., K. Karlsson, J. Quaas, and H. Graßl, Correcting orbital drift signal in the time series of AVHRR derived convective cloud fraction using rotated empirical orthogonal function, Atmos. Meas. Tech., 5, 267-273, doi:10.5194/amt-5-267-2012, 2012.

12. Gehlot, S., and J. Quaas, Convection-climate feedbacks in ECHAM5 general circulation model: A Lagrangian trajectory perspective of cirrus cloud life cycle, J. Clim., 25, 5241-5259, doi:10.1175/JCLI-D-11-00345.1, 2012.

11. Nam, C., and J. Quaas, Evaluation of clouds and precipitation in the ECHAM5 general circulation model using CALIPSO and CloudSat , J. Clim., 25, 4975-4992, doi:10.1175/JCLI-D-11-00347.1, 2012.

10. Peters, K., P. Stier, J. Quaas, and H. Graßl, Aerosol indirect effects from shipping emissions: Sensitivity studies with the global aerosol-climate model ECHAM-HAM, Atmos. Chem. Phys., 12, 5985-6007, doi:10.5194/acp-12-5985-2012, 2012.

9. Quaas, J., Evaluating the "critical relative humidity" as a measure of subgrid-scale variability of humidity in general circulation model cloud cover parameterizations using satellite data, J. Geophys. Res., 117, D09208, doi:10.1029/2012JD017495, 2012.

8. Sanchez-Lorenzo, A., P. Laux, H.-J. Hendricks-Franssen, A. K. Georgoulias, J. Calbó, S. Vogl, and J. Quaas, Assessing large-scale weekly cycles in meteorological variables: a review, Atmos. Chem. Phys., 12, 5755-5771, doi:10.5194/acp-12-5755-2012, 2012.

7. Weber, T., and J. Quaas, Incorporating the subgrid-scale variability of clouds in the autoconversion parameterization, J. Adv. Model. Earth Syst., 4, M11003, doi:10.1029/2012MS000156, 2012.

6. Zhang, K., D. O'Donnell, J. Kazil, P. Stier, S. Kinne, U. Lohmann, S. Ferrachat, B. Croft, J. Quaas, H. Wan, S. Rast, and J. Feichter, The global aerosol-climate model ECHAM5-HAM, version 2: sensitivity to improvements in process representations, Atmos. Chem. Phys., 12, 8911-8949, doi:10.5194/acp-12-8911-2012, 2012.

5. Zygmuntowska, M., T. Mauritsen, J. Quaas, and L. Kaleschke, Artcic clouds and surface radiation - a critical comparison of satellite retrievals and the ERA-INTERIM reanalysis, Atmos. Chem. Phys., 12, 6667-6677, doi:10.5194/acp-12-6667-2012, 2012.

4. Klocke, D., R. Pincus, and J. Quaas, On constraining estimates of climate sensitivity with present-day observations through model weighting, J. Clim., 24, 6092-6099, doi:10.1175/2011JCLI4193.1, 2011.

3. Peters, K., J. Quaas, and H. Graßl, A search for large-scale effects of ship emissions on clouds and radiation in satellite data, J. Geophys. Res., 116, D24205, doi:10.1029/2011JD016531, 2011.

2. Quaas, J., O. Boucher, N. Bellouin, and S. Kinne, Which of satellite- or model-based estimates is closer to reality for aerosol indirect forcing? - Reply to Penner et al., Proc. Nat. Acad. Sci. USA, 108, E1099, doi:10.1073/pnas.1114634108, 2011.

1. Weber, T., J. Quaas, and P. Räisänen, Evaluation of the subgrid-scale variability scheme for water vapor and cloud condensate in the ECHAM5 model using satellite data, Q. J. R. Meteorol. Soc., 137, 2079-2091, doi:10.1002/qj.887, 2011.


ERC Starting Grant Quantifying Aerosol-Cloud-Climate Effects by Regime (QUAERERE)

Quantification of the radiative forcing by the effect of anthropogenic aerosols on clouds, using statistical analysis of satellite data and using climate modelling

BMBF-Verbundprojekt High Definition Clouds and Climate for Advancing Climate Prediction (HD(CP)²) - zweite Phase (2016-2019)

Use of the high-resolution ICON-Model and the HD(CP)²-observation data for the investigation of fast adjustments of clouds to the anthropogenic emissions of aerosols (Project S1) and of CO2 (Project S2).
Main Partners: Max-Planck-Institut für Meteorologie, Hamburg; Institut für Geophysik und Meteorologie, Universität zu Köln; Institut für Weltraumwissenschaften, Freie Universität Berlin; Leibniz-Institut für Troposphärenforschung, Leipzig

ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms, (AC)³

Main task: Investigation of radiative forcing due to aerosol-cloud-interactions and their impacts in the Arctic (Project D02), analysis and qunatification of the climate feedbacks in the Arctic (Project E01).
collaborative research centre/transregional at the Universities Leipzig, Köln und Bremen with Alfred-Wegener-Institute (Bremerhaven and Potsdam) and Leibniz-Institute of Troposperic Research (Leipzig)

Forcing in the long-wave spectrum due to aerosol-cloud interactions: satellite and climate modelling vs. HALO, FLASH, DFG, SPP 1294 "HALO"

Evaluation of a new satellite-based data set for ice crystal concentrations by the use of HALO-observations, analysis of the aerosol interactions.

EU FP7-Project Monitoring Atmospheric Composition and Climate - Interim Implementation (MACC-II)

Main task: monitoring of aerosol direct and indirect radiative forcings, based on assimilated aerosol fields in the ECMWF IFS model.
Main Partners: ECMWF, Reading, UK; University Reading, UK; LMD/CNRS, Paris, France

EU FP7-Project Evaluating the CLimate and Air Quality ImPacts of Short-livEd Pollutants (ECLIPSE)

Main task: Assessing climate impacts of emission cuts for short-lived pollutants, in particular black carbon in the context of the coupled climate system and evaluation using historical observations.
Main Partners: UK Met Office, Exeter, UK; Norwegian Institute for Air Research, Kjeller, Norwegen

COST Activity ES0905 Basic concepts for convection parameterization in weather forecast and climate models

Main contribution: Vice chair, Co-leader of Working group 4 "Physics and Observations"

Learning about cloud brightening: When and how to do experiments (LEAC), DFG-Schwerpunkt-programm 1689 Climate Engineering: Risks, Challenges, Opportunities?

Analysis of satellite data and model results to assess the size in space and time of a potential field experiment needed for statistically significant results on the effectiveniss of cloud seeding for climate mitigation.
Partners: Group of Environmental, Resource and Ecological Economics at the Christian-Albrechts-University Kiel.

BMBF project High Definition Clouds and Climate for Advancing Climate Prediction (HD(CP)2)

Main contributions: Synchronising model and observational data for full-domain observations; Application of these data for climate model parameterisation evaluation; Use of HD(CP)2 data to evaluate and develop statistical cloud schemes.
Main Partners: Max Planck Institute for Meteorology, Hamburg; Institute for Geophysics and Meteorology, University of Cologne; Meteorological Institute, University of Bonn; Institute for Space Studies, Free University Berlin; Leibniz-Institute for Tropospheric Research, Leipzig