References

ACP

Atmospheric Chemistry and Physics

ACP

Atmos. Chem. Phys.

1680-7324

Copernicus Publications

Göttingen, Germany

10.5194/acp-13-7551-2013

Monte Carlo-based subgrid parameterization of vertical velocity and stratiform cloud microphysics in ECHAM5.5-HAM2

Tonttila

¹ ² Räisänen

https://orcid.org/0000-0003-4466-213X

¹ Järvinen

https://orcid.org/0000-0003-1879-6804

Finnish Meteorological Institute, P.O. Box 503, 00101, Helsinki, Finland

Division of Atmospheric Sciences, Department of Physics, University of Helsinki, 00014, Helsinki, Finland

06 08 2013

13 15 7551 7565

2013

This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/

This article is available from https://acp.copernicus.org/articles/13/7551/2013/acp-13-7551-2013.html

The full text article is available as a PDF file from https://acp.copernicus.org/articles/13/7551/2013/acp-13-7551-2013.pdf

A new method for parameterizing the subgrid variations of vertical velocity and cloud droplet number concentration (CDNC) is presented for general circulation models (GCMs). These parameterizations build on top of existing parameterizations that create stochastic subgrid cloud columns inside the GCM grid cells, which can be employed by the Monte Carlo independent column approximation approach for radiative transfer. The new model version adds a description for vertical velocity in individual subgrid columns, which can be used to compute cloud activation and the subgrid distribution of the number of cloud droplets explicitly. Autoconversion is also treated explicitly in the subcolumn space. This provides a consistent way of simulating the cloud radiative effects with two-moment cloud microphysical properties defined at subgrid scale. The primary impact of the new parameterizations is to decrease the CDNC over polluted continents, while over the oceans the impact is smaller. Moreover, the lower CDNC induces a stronger autoconversion of cloud water to rain. The strongest reduction in CDNC and cloud water content over the continental areas promotes weaker shortwave cloud radiative effects (SW CREs) even after retuning the model. However, compared to the reference simulation, a slightly stronger SW CRE is seen e.g. over mid-latitude oceans, where CDNC remains similar to the reference simulation, and the in-cloud liquid water content is slightly increased after retuning the model.

References 1

Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation.2. Multiple aerosol types, J. Geophys. Res., 105, 6837–6844, 2000.

Abdul-Razzak, H., Ghan, S. J., and Rivera-Carpio, C.: A parameterization of aerosol activation. 1. Single aerosol type, J. Geophys. Res., 103, 6123–6131, 1998.

Cagnazzo, C., Manzini, E., Giorgetta, M. A., Forster, P. M. De F., and Morcrette, J. J.: Impact of an improved shortwave radiation scheme in the MAECHAM5 General Circulation Model, Atmos. Chem. Phys., 7, 2503–2515, <a href="http://dx.doi.org/10.5194/acp-7-2503-2007">https://doi.org/10.5194/acp-7-2503-2007</a>, 2007.

Fountoukis, C., Nenes, A., Meskhidze, N., Bahreini, R., Conant, W. C., Jonsson, H., Murphy, S., Sorooshian, A., Varutbangkul, V., Brechtel, F., Flagan, R. C., and Seinfeld, J. H.: Aerosol-cloud drop concentration closure for clouds sampled during the International Consortium for Atmospheric Research on Transport and Transformation 2004 campaign, J. Geophys. Res., 112, D10S30, <a href="http://dx.doi.org/10.1029/2006JD007272">https://doi.org/10.1029/2006JD007272</a>, 2007.

Fouquart, Y. and Bonnel, B.: Computations of solar heating of the Earth"s atmosphere: a new parameterization, Beitr. Phys. Atmos. 53, 35–62, 1980.

Fountoukis, C. and Nenes, A.: Continued development of a cloud droplet formation parameterization for global climate models, J. Geophys. Res., 110, D11212, <a href="http://dx.doi.org/10.1029/2004JD005591">https://doi.org/10.1029/2004JD005591</a>, 2005.

Ghan, S. J., Leung, L. R., and Easter, R. C.: Prediction of cloud droplet number in a general circulation model, J. Geophys. Res., 102, 21777–21794, 1997.

Ghan, S. J., Abdul-Razzak, H., Nenes, A., Ming, Y., Liu, X., Ovchinnikov, M., Shipway, B., Meskhidze, N., Xu, J., and Shi, X.: Droplet nucleation: physically-based parameterizations and comparative evaluation, J. Adv. Model. Earth Syst., 3, M10001, <a href="http://dx.doi.org/10.1029/2011MS000074">https://doi.org/10.1029/2011MS000074</a>, 2011.

Ghate, V. P., Albrecht, B. A., and Kollias, P.: Vertical velocity structure of nonprecipitating continental boundary layer stratocumulus clouds, J. Geophys. Res., 115, D13204, <a href="http://dx.doi.org/10.1029/2009JD013091">https://doi.org/10.1029/2009JD013091</a>, 2010.

Golaz, J.-C., Salzmann, M., Donner, L. J., Horowitz, L., W., Ming, Y., and Zhao, M.: Sensitivity of the aerosol indirect effect to subgrid variability in the cloud parameterization of the GFDL atmosphere general circulation model AM3, J. Climate, 24, 3145–3160, <a href="http://dx.doi.org/10.1175/2010JCLI3945.1">https://doi.org/10.1175/2010JCLI3945.1</a>, 2011.

Guo, H., Liu, Y., Daum, P. H., Senum, G. I., and Tao, W.-K.: Characteristics of vertical velocity in marine stratocumulus: comparison of large eddy simulations with observations, Environ. Res. Lett., 3, 045020, <a href="http://dx.doi.org/10.1088/1748-9326/3/4/045020">https://doi.org/10.1088/1748-9326/3/4/045020</a>, 2008.

Guo, H., Golaz, J.-C., Donner, L. J., Larson, V. E., Schanen, D. P., and Griffin, B. M.: Multi-variate probability density functions with dynamics for cloud droplet activation in large-scale models: single column tests, Geosci. Model Dev., 3, 475–486, <a href="http://dx.doi.org/10.5194/gmd-3-475-2010">https://doi.org/10.5194/gmd-3-475-2010</a>, 2010.

Hogan, R. J. and Illingworth, A., J.: Deriving cloud overlap statistics from radar, Q. J. Roy. Meteorol. Soc., 128, 2903–2909, 2000.

Hoose, C., Kristjansson, J. E., Iversen, T., Kirkev\aa g, A., Seland, \O, and Gettelman, A.: Constraining cloud droplet number concentration in GCMs suppresses the aerosol indirect effect, Geophys. Res. Lett., 36, L12807, <a href="http://dx.doi.org/10.1029/2009GL038568">https://doi.org/10.1029/2009GL038568</a>, 2009.

Hoose, C., Kristjansson, J. E., Arabas, S., Boers, R., Pawlowska, H., Puygrenier, V., Siebert, H., and Thouron, O.: Parameterization of in-cloud vertical velocities for cloud droplet activation in coarse-grid models: analysis of observations and cloud resolving model results. Proceedings of the 13th AMS Conference on Atmospheric Radiation, Portland, OR, USA, 28 June–2 July 2010.

Khairoutdinov, M. and Kogan, Y.: A new cloud physics parameterization in a Large-Eddy Simulation model of marine stratocumulus, Mon. Weather Rev., 128, 229–243, 2000.

Khvorostyanov, V. I. and Curry, J.: Parameterization of cloud drop activation based on analytical asymptotic solutions to the supersaturation equation, J. Atmos. Sci., 66, 1905–1925, 2009.

Leaitch, W. R., Strapp, J. W., and Isaac, G. A.: Cloud droplet nucleation and cloud scavenging of aerosol sulphate in polluted atmospheres, Tellus B, 38, 328–344, 1986.

Lenschow, D. H., Lothon, M., Mayor, S. D., Sullivan, P. P., and Canut, G.: A comparison of higher-order vertical velocity moments in the convective boundary layer from lidar with in situ measurements and large-eddy simulation, Bound.-Lay. Meteorol., 143, 107–123, <a href="http://dx.doi.org/10.1007/s10546-011-9615-3">https://doi.org/10.1007/s10546-011-9615-3</a>, 2012.

Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F., Kato, S., Manalo-Smith, N., and Wong, T.: Toward optimal closure of the Earth's top-of-atmosphere radiation budget, J. Climate, 22, 748–766, <a href="http://dx.doi.org/10.1175/2008JCLI2637.1">https://doi.org/10.1175/2008JCLI2637.1</a>, 2009.

Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review, Atmos. Chem. Phys., 5, 715–737, <a href="http://dx.doi.org/10.5194/acp-5-715-2005">https://doi.org/10.5194/acp-5-715-2005</a>, 2005.

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, <a href="http://dx.doi.org/10.5194/acp-10-11373-2010">https://doi.org/10.5194/acp-10-11373-2010</a>, 2010.

Lohmann, U. and Roeckner, E.: Desing and performance of a new cloud microphysics scheme developed for the ECHAM general circulation model, Clim. Dynam., 12, 557–572, 1996.

Lohmann, U., Feichter, J., Chuang, C. C., and Penner, J. E.: Prediction of the number of cloud droplets in the ECHAM GCM, J. Geophys. Res., 104, 9169–9198, 1999.

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, <a href="http://dx.doi.org/10.5194/acp-7-3425-2007">https://doi.org/10.5194/acp-7-3425-2007</a>, 2007.

Ming, Y., Ramaswamy, V., Donner, L. J., and Phillips, V. T. J.: A new parameterization of cloud droplet activation applicable to general circulation models, J. Atmos. Sci., 63, 1348–1356, 2006.

Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res., 102, 16663–16682, 1997.

Moeng, C.-H. and Rotunno, R.: Vertical-velocity skewness in the buoyancy-driven boundary layer, J. Atmos. Sci., 47, 1149–1161, 1990.

Morales, R. and Nenes, A.: Characteristic updrafts for computing distribution averaged cloud droplet number and stratocumulus cloud properties, J. Geophys. Res., 115, D18220, <a href="http://dx.doi.org/10.1029/2009JD013233">https://doi.org/10.1029/2009JD013233</a>, 2010.

O'Donnell, D., Tsigaridis, K., and Feichter, J.: Estimating the direct and indirect effects of secondary organic aerosols using ECHAM5-HAM, Atmos. Chem. Phys., 11, 8635–8659, <a href="http://dx.doi.org/10.5194/acp-11-8635-2011">https://doi.org/10.5194/acp-11-8635-2011</a>, 2011.

Pincus, R., Barker, H. W., and Morcrette, J.-J.: A fast, flexible, approximate technique for computing radiative transfer in inhomogeneous cloud fields, J. Geophys. Res., 108, <a href="http://dx.doi.org/10.1029/2002JD003322">https://doi.org/10.1029/2002JD003322</a>, 2003.

Räisänen, P. and Järvinen, H.: Impact of cloud and radiation scheme modifications on climate simulated by the ECHAM5 atmospheric GCM, Q. J. Roy. Meteorol. Soc., 136, 1733–1752, <a href="http://dx.doi.org/10.1002/qj.674">https://doi.org/10.1002/qj.674</a>, 2010.

Räisänen, P., Barker, H. W., Khairoutdinov, M. F., Li, J., and Randall, D. A.: Stochastic generation of subgrid-scale cloudy columns for large-scale models, Q. J. Roy. Meteorol. Soc., 130, 2047–2067, 2004.

Räisänen, P., Järvenoja, S., Järvinen, H., Giorgetta, M., Roeckner, E., Jylhä, K., and Ruosteenoja, K.: Tests of Monte Carlo Independent Column Approximation in the ECHAM5 atmospheric GCM, J. Climate, 20, 4995–5011, 2007.

Räisänen, P., Järvenoja, S., and Järvinen, H.: Noise due to Monte Carlo independent-column approximation: short-term and long-term impacts in ECHAM5, Q. J. Roy. Meteorol. Soc., 134, 481–495, <a href="http://dx.doi.org/10.1002/qj.231">https://doi.org/10.1002/qj.231</a>, 2008.

Reutter, P., Su, H., Trentmann, J., Simmel, M., Rose, D., Gunthe, S. S., Wernli, H., Andreae, M. O., and Pöschl, U.: Aerosol- and updraft-limited regimes of cloud droplet formation: influence of particle number, size and hygroscopicity on the activation of cloud condensation nuclei (CCN), Atmos. Chem. Phys., 9, 7067–7080, <a href="http://dx.doi.org/10.5194/acp-9-7067-2009">https://doi.org/10.5194/acp-9-7067-2009</a>, 2009.

Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Koernblueh, L., Manzini, E., Rhodin A., Schlese, U., Schulzweida, U., and Tompkins, A.: The atmospheric general circulation model ECHAM5, Part I: model description. Rep. 349, Max Planck Institute for Meteorology, Hamburg, Germany, 127 pp., 2003.

Roeckner, E., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Koernblueh, 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, 2006.

Rotstayn, L. D.: On the "tuning" of autoconversion parameterizations in climate models, J. Geophys. Res., 105, 15495–15507, <a href="http://dx.doi.org/10.1029/2000JD900129">https://doi.org/10.1029/2000JD900129</a>, 2000.

Stephens, G. L., Li, J., Wild, M., Clayson, C. A., Loeb, N., Kato, S., L'Ecuyer, T., Stackhouse Jr, P. W., Lebsock, M., and Andrews, T.: An update on earth's energy balance in light of the latest global observations, Nat. Geosci., 5, 691–696, <a href="http://dx.doi.org/10.1038/NGEO1580">https://doi.org/10.1038/NGEO1580</a>, 2012.

Tompkins, A. M.: A prognostic parameterization for the subgrid-scale variability of water vapor and clouds in large-scale models and its use to diagnose cloud cover, J. Atmos. Sci., 59, 1917–1942, 2002.

Vignati, E., Wilson, J., and Stier, P.: M7: an efficient size-resolved aerosol microphysics module for large-scale aerosol transport models, J. Geophys. Res., 109, D22202, <a href="http://dx.doi.org/10.1029/2003JD004485">https://doi.org/10.1029/2003JD004485</a>, 2004.

Wang, M., Ghan, S., Liu, X., L'Ecuyer, T. S., Zhang, K., Morrison, H., Ovchinnikov, M., Easter, R., Marchand, R., Chand, D., Qian, Y., and Penner, J. E.: Constraining cloud lifetime effects of aerosols using A-Train satellite observations, Geophys. Res. Lett., 39, L15709, <a href="http://dx.doi.org/10.1029/2012GL052204">https://doi.org/10.1029/2012GL052204</a>, 2012.

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, <a href="http://dx.doi.org/10.5194/acp-12-8911-2012">https://doi.org/10.5194/acp-12-8911-2012</a>, 2012.