ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-10-6435-2010 Cluster analysis of midlatitude oceanic cloud regimes: mean properties and temperature sensitivity Gordon N. D. 1 2 Norris J. R. 1 Scripps Institution of Oceanography, University of California, San Diego La Jolla, CA, USA current address: School of Earth and Environment, University of Leeds Leeds, UK 14 07 2010 10 13 6435 6459 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys.net/10/6435/2010/acp-10-6435-2010.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/10/6435/2010/acp-10-6435-2010.pdf

Clouds play an important role in the climate system by reducing the amount of shortwave radiation reaching the surface and the amount of longwave radiation escaping to space. Accurate simulation of clouds in computer models remains elusive, however, pointing to a lack of understanding of the connection between large-scale dynamics and cloud properties. This study uses a k-means clustering algorithm to group 21 years of satellite cloud data over midlatitude oceans into seven clusters, and demonstrates that the cloud clusters are associated with distinct large-scale dynamical conditions. Three clusters correspond to low-level cloud regimes with different cloud fraction and cumuliform or stratiform characteristics, but all occur under large-scale descent and a relatively dry free troposphere. Three clusters correspond to vertically extensive cloud regimes with tops in the middle or upper troposphere, and they differ according to the strength of large-scale ascent and enhancement of tropospheric temperature and humidity. The final cluster is associated with a lower troposphere that is dry and an upper troposphere that is moist and experiencing weak ascent and horizontal moist advection. <br><br> Since the present balance of reflection of shortwave and absorption of longwave radiation by clouds could change as the atmosphere warms from increasing anthropogenic greenhouse gases, we must also better understand how increasing temperature modifies cloud and radiative properties. We therefore undertake an observational analysis of how midlatitude oceanic clouds change with temperature when dynamical processes are held constant (i.e., partial derivative with respect to temperature). For each of the seven cloud regimes, we examine the difference in cloud and radiative properties between warm and cold subsets. To avoid misinterpreting a cloud response to large-scale dynamical forcing as a cloud response to temperature, we require horizontal and vertical temperature advection in the warm and cold subsets to have near-median values in three layers of the troposphere. Across all of the seven clusters, we find that cloud fraction is smaller and cloud optical thickness is mostly larger for the warm subset. Cloud-top pressure is higher for the three low-level cloud regimes and lower for the cirrus regime. The net upwelling radiation flux at the top of the atmosphere is larger for the warm subset in every cluster except cirrus, and larger when averaged over all clusters. This implies that the direct response of midlatitude oceanic clouds to increasing temperature acts as a negative feedback on the climate system. Note that the cloud response to atmospheric dynamical changes produced by global warming, which we do not consider in this study, may differ, and the total cloud feedback may be positive.

 References Betts, A. K. and Harshvardhan: Thermodynamic constraint on the cloud liquid water feedback in climate models, J. Geophys. Res., 92, 8483–8485, 1987. Bony, S., Dufresne, J.-L., Le Treut, H., Morcrette, J.-J., and Senior, C.: On dynamic and thermodynamic components of cloud changes, Clim. Dyn., 22, 71–86, 2004. Cess, R. D. and Udelhofen, P. M.: Climate change during 1985–1999: cloud interactions determined from satellite measurements, Geophys. Res. Lett., 30, 1019, doi:10.1029/2002GL016128, 2003. Chang, F.-L. and Coakley, J. A.: Relationships between marine stratus cloud optical depth and temperature: Inferences from AVHRR observations, J. Climate, 20, 2022–2036, 2007. Charlock, T. P. and Ramanathan, V.: The Albedo Field and Cloud Radiative Forcing Produced by a General Circulation Model with Internally Generated Cloud Optics, J. Atmos. Sci., 42, 1408–1429, 1985. Clement, A. C., Burgman, R., and Norris, J. R.: Observational and model evidence for positive low-level cloud feedback, Science, 325, 460–426, 2009. Gordon, N. D., Norris, J. R., Weaver, C. P., and Klein, S. A.: Cluster analysis of cloud regimes and characteristic dynamics of midlatitude synoptic systems in observations and a model, J. Geophys. Res., 110, D15S17, doi:10.1029/2004JD005027, 2005. Hahn, C. J. and Warren, S. G.: Extended Edited Cloud Reports from Ships and Land Stations over the Globe, 1952–1996, Numerical Data Package NDP-026C, Carbon Dioxide Information Analysis Center (CDIAC), Department of Energy, Oak Ridge, Tennessee (79 pp.), 1999. Hartigan, J. A.: Clustering Algorithms, Wiley Press, New York, NY, 351 pp., 1975.5 IPCC Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change edited by: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M., and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp., 2007. Jakob, C.: An improved strategy for the evaluation of cloud parameterizations in GCMs, B. Am. Meteor. Soc., 84, 1387–1401, 2003. Jakob, C. and G. Tselioudis: Objective Identification of Cloud Regimes in the Tropical West Pacific, Geophys. Res. Lett., 30(21), 2082, doi:10.1029/2003GL018367, 2003. Jakob, C., Tselioudis, G., and Hume, T.: The radiative, cloud and thermodynamic properties of the major Tropical Western Pacific cloud regimes, J. Climate, 18, 1203–1215, 2005. Kalnay E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-year reanalysis project, B. Am. Meteor. Soc., 77, 437–470, 1996. Klein, S. A., and Jakob, C.: Validation and sensitivities of frontal clouds simulated by the ECMWF model, Mon. Wea. Rev., \textbf127, 2514-2531, 1999. Lau, N.-C. and Crane, M. W.: A satellite view of the synoptic-scale organization of cloud cover in midlatitude and tropical circulation systems, Mon. Wea. Rev., 123, 1984–2006, 1995. Mitchell, J. F. B., Senior, C. A., and Ingram, W. J.: CO<sub>2</sub> and climate: a missing feedback?, Nature, 341, 132–134, 1989. Norris, J. R.: Low cloud type over the ocean from surface observations. Part I: relationship to surface meteorology and the vertical distribution of temperature and moisture, J. Climate, 11, 369–382, 1998a. Norris, J. R.: Low cloud type over the ocean from surface observations. Part II: geographical and seasonal variations, J. Climate, 11, 383–403, 1998b. Norris, J. R. and Leovy, C. B.: Interannual variability in stratiform cloudiness and sea surface temperature, J. Climate, 7, 1915–1925, 1994. Norris, J. R. and Klein, S. A.: Low cloud type over the ocean from surface observations. Part III: relationship to vertical motion and the regional surface synoptic environment, J. Climate, 13, 245–256, 2000. Norris, J. R. and Weaver, C. P.: Improved Techniques for Evaluating GCM Cloudiness Applied to the NCAR CCM3, J. Climate, 14, 2540–2550, 2001. Norris, J. R. and Iacobellis, S. F.: North Pacific cloud feedbacks inferred from synoptic-scale dynamic and thermodynamic relationships, J. Climate, 18, 4862–4878, 2005. Ramanathan, V., Barkstrom, B. R., and Harrison, E. F.: Climate and the Earth's Radiation Budget, Physics Today, 42(5), 22–33, 1989. Raval, A. and Ramanathan, V.: Observational determination of the greenhouse effect, Nature, 342, 758–761, 1989. Ringer, M. A., McAvaney, B. J., Andronova, N., Buja, L. E., Esch, M., Ingram, W. J., Li, B., Quaas, J., Roeckner, E., Senior, C. A., Soden, B. J., Volodin, E. M., Webb, M. J., and Williams, K. D.: Global mean cloud feedbacks in idealized climate change experiments, Geophys. Res. Lett., 33(7), L07718, doi:10.1029/2005GL025370, 2006. Rossow, W. B. and Garder, L. C.: Validation of ISCCP cloud detections, J. Climate, 6, 2370–2393, 1993. Rossow, W. B., Walker, A. W., Beuschel, D. E., and Roiter, M. D.: International Satellite Cloud Climatology Project (ISCCP) Documentation of New Cloud Datasets, WMO/TD-No 737, World Meteorological Organization, 115 pp., 1996. Rossow, W. B. and Schiffer, R. A.: Advances in Understanding ISCCP, B. Am. Meteor. Soc., 80, 2261–2287, 1999. Rossow, W. B., Tselioudis, G., Polak, A., and Jakob, C.: Tropical climate described as a distribution of weather states indicated by distinct mesoscale cloud property mixtures, Geophys. Res. Lett., 32, L21812, doi:10.1029/2005GL024584, 2005. Soden, B. J., Held, I. M., Colman, R., Shell, K. M., Kiehl, J. T., and Shields, C. A.: Quantifying climate feedbacks using radiative kernels, J. Climate, 21, 3504–3520, 2008. Somerville, R. C. J. and Remer, L. A.: Cloud optical thickness feedbacks in the CO2 climate problem, J. Geophys. Res., 89, 9668–9672, 1984. Tselioudis, G. and Jakob, C.: Evaluation of midlatitude cloud properties in a weather and a climate model: dependence on dynamic regime and spatial resolution, J. Geophys. Res., 107, 4781, doi:10.1029/2002JD002259, 2002. Wagner, T., Beirle, S., Deutschmann, T., Grzegorski, M., and Platt, U.: Dependence of cloud properties derived from spectrally resolved visible satellite observations on surface temperature, Atmos. Chem. Phys., 8, 2299–2312, doi:10.5194/acp-8-2299-2008, 2008. Weaver, C. P.: Efficiency of storm tracks an important climate parameter? The role of cloud radiative forcing in poleward heat transport, J. Geophys. Res., 108, 4018, doi:10.1029/2002JD002756, 2003. Weaver, C. P. and Ramanathan, V.: The link between summertime cloud radiative forcing and extratropical cyclones in the N. Pacific, J. Climate, 9, 2093–2109, 1996. Weaver, C. P. and Ramanathan, V.: Relationships between large-scale vertical velocity, static stability, and cloud radiative forcing over Northern Hemisphere extratropical oceans, J. Climate, 10, 2871–2887, 1997. Williams K. D. and Tselioudis, G.: GCM intercomparison of global cloud regimes: Present-day evaluation and climate change response, Clim. Dyn., 29(2–3), doi:10.1007/s00382-007-0232-2, 2007. Williams, K. D. and Webb, M. J.: A quantitative performance assessment of cloud regimes in climate models, Clim. Dyn., 33(1), doi:10.1007/s00382-008-0443-1, 2009. Zhang, Y., Rossow, W. B., Lacis, A. A., Oinas, V., and Mishchenko, M. I.: Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data, J. Geophys. Res., 109, D19105, doi:10.1029/2003JD004457, 2004.