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Prognostic Precipitation with Three Liquid Water Classes in the Echam5-ham Gcm : Volume 15, Issue 5 (12/03/2015)

By Sant, V.

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Book Id: WPLBN0003997208
Format Type: PDF Article :
File Size: Pages 54
Reproduction Date: 2015

Title: Prognostic Precipitation with Three Liquid Water Classes in the Echam5-ham Gcm : Volume 15, Issue 5 (12/03/2015)  
Author: Sant, V.
Volume: Vol. 15, Issue 5
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Sant, V., Posselt, R., & Lohmann, U. (2015). Prognostic Precipitation with Three Liquid Water Classes in the Echam5-ham Gcm : Volume 15, Issue 5 (12/03/2015). Retrieved from

Description: Institute of Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland. In order to improve the global representation of rain formation in marine stratiform clouds a new parameterization with three prognostic liquid water classes was implemented into the general circulation model ECHAM5 with the aerosol module HAM. The additionally introduced drizzle class improves the physical representation of the droplet spectrum and more importantly, improves the microphysical processes relevant for precipitation formation compared to the standard parameterization. In order to avoid a mismatch of the liquid and ice phase, the prognostic treatment of snow has been introduced too. This has a significant effect on the amount and altitude of ice clouds, which in turn does not only affect in- and outgoing radiation, but also the parameterized collection rates. With the introduction of a prognostic precipitation scheme a more realistic representation of both liquid and ice phase large-scale precipitation is achieved compared to a diagnostic treatment. An encouraging finding is that the sensitivity of the liquid water path to the anthropogenic aerosol forcing with the prognostic treatment is reduced by about 25%. Although the total net radiative forcing is increased from 1.4±0.4 to 1.6±0.4 W m−2 from the control to the prognostic model version, the difference is within the interannual variability. Altogether the results suggest that the treatment of precipitation in global circulation models has a significant influence on the phase and lifetime of clouds, but also hints towards the uncertainties related to a prognostic precipitation scheme.

Prognostic precipitation with three liquid water classes in the ECHAM5-HAM GCM

Wentz, F.: A well-calibrated ocean algorithm for SSM/I, J. Geophys. Res., 102, 8703–8718, 1997.; Ackerman, A., Kirkpatrick, M., Stevens, D., and Toon, O.: The impact of humidity above stratiform clouds on indirect aerosol climate forcing, Nature, 432, 1014–1017, 2004.; Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P. P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeorol., 4, 1147–1167, 2003.; Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, 1989.; Barthazy, E. and Schefold, R.: Fall velocity of snowflakes of different riming degree and crystal types, Atmos. Res., 82, 391–398, 2006.; Bellouin, N., Quaas, J., Morcrette, J.-J., and Boucher, O.: Estimates of aerosol radiative forcing from the MACC re-analysis, Atmos. Chem. Phys., 13, 2045–2062, doi:10.5194/acp-13-2045-2013, 2013.; Bony, S. and Dufresne, J.: Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models, Geophys. Res. Lett., 32, L20806, doi:10.1029/2005GL023851, 2005.; 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.: 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., chap. 7, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 571–657, 2013.; 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, 2013.; Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, 2011.; 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, doi:10.5194/acp-6-4321-2006, 2006.; Eidhammer, T., Morrison, H., Bansemer, A., Gettelman, A., and Heymsfield, A. J.: Comparison of ice cloud properties simulated by the Community Atmosphere Model (CAM5) with in-situ observations, Atmos. Chem. Phys., 14, 10103–10118, doi:10.5194/acp-14-10103-2014, 2014.; Gettelman, A. and Morrison, H.: Advanced Two-Moment Bulk Microphysics for Global Models. Part I: Off-Line Tests and Comparison with Other Schemes. J. Climate, 28, 1268–1287, 2015.; Gettelman, A., Morrison, H., Terai, C. R., and Wood, R.: Microphysical process rates and global aerosol–cloud interactions, Atmos


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