Stochastic parameterization of shallow cumulus convection estimated from high-resolution model data

Theoretical and Computational Fluid Dynamics

Volumn 27, Issue 1-2, 2013, Pages 133-148

  Dorrestijn, Jesse ^a   Crommelin, Daan T ^a   Siebesma, A Pier ^b,c   Jonker, Harm J J ^b  

^a CWI   (Netherlands)

^b DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^c ROYAL NETHERLANDS METEOROLOGICAL INSTITUTE KNMI   (Netherlands)

Author keywords

Atmospheric convection; Clustering; Grey zone; Large Eddy Simulation; Markov chain; Stochastic parameterization

Indexed keywords

ATMOSPHERIC CONVECTION; CLUSTERING; CONVECTIVE TRANSPORT; FINITE NUMBER; GREY ZONE; HIGH-RESOLUTION MODELS; MOISTURE FLUXES; PARAMETERIZATION SCHEMES; SHALLOW CUMULUS CONVECTION; SINGLE-COLUMN MODEL; TRANSITION PROBABILITIES; TURBULENT FLUX;

CLOUDS; LARGE EDDY SIMULATION; MARKOV PROCESSES; MOISTURE; PARAMETERIZATION; STOCHASTIC SYSTEMS;

STOCHASTIC MODELS;

CLIMATE MODELING; CONVECTION; CUMULUS; DATA SET; EDDY; HUMIDITY; MARKOV CHAIN; NUMERICAL MODEL; PARAMETERIZATION; RESOLUTION; STATISTICAL ANALYSIS; STOCHASTICITY; TEMPERATURE EFFECT; TURBULENCE;

EID: 84873405011     PISSN: 09354964     EISSN: 14322250     Source Type: Journal    
DOI: 10.1007/s00162-012-0281-y     Document Type: Article

References (33)

1. Arakawa, A., Schubert, W.H.: Interaction of a cumulus cloud ensemble with the large-scale environment, part I. J. Atmos. Sci. 31, 674-701 (1974)
2. Arakawa, A.: The cumulus parameterization problem: past, present, and future. J. Clim. 17, 2493-2525 (2004)
3. Arthurm, D., Vassilvitskii, S.: k-means++: the advantages of careful seeding. Proceedings of the 18th Annual ACMSIAM Symposium on Discrete Algorithms, pp. 1027-1035 (2007)
4. Buizza, R., Miller, M., Palmer, T.N.: Stochastic representation of model uncertainties in the ECMWF ensemble prediction system. Q. J. R. Meteorol. Soc. 125, 2887-2908 (1999)
5. Crommelin, D., Vanden Eijnden, E.: Subgrid-scale parametrization with conditional Markov chains. J. Atmos. Sci. 65, 2661-2675 (2008)
6. Gan, G., Ma, C., Wu, J.: Data clustering: theory, algorithms, and applications. SIAM, Alex, VA (2007)
7. Gerard, L.: An integrated package for subgrid convection, clouds and precipitation compatible with meso-gamma scales. Q. J. R. Meteorol. Soc. 00, 1-19 (2007)
8. Heus, T., van Dijk, G., Jonker, H.J.J., van den Akker, H.E.A.: Mixing in shallow cumulus clouds studied by Lagrangian particle tracking. J. Atmos. Sci. 65, 2581-2597 (2008)
9. Heus, T., van Heerwaarden, C.C., Jonker, H.J.J., Siebesma, A.P., Axelsen, S., van den Dries, K., Geoffroy, O., Moene, A.F., Pino, D., de Roode, S.R., Vil-Gueraude Arellano, J.: Formulation of and numerical studies with the Dutch Atmospheric Large-Eddy Simulation (DALES). Geosci. Model Dev. 3, 415-444 (2010)
10. Holland, J.Z., Rasmusson, E.M.: Measurement of atmospheric mass, energy, and momentum budgets over a 500-km square of tropical ocean. Mon. Weather Rev. 101, 44-55 (1973)
11. Honnert, R., Masson, V., Couvreux, F.: A diagnostic for evaluating the representation of turbulence in atmospheric models at the kilometric scale. J. Atmos. Sci. 68, 3112-3131 (2011)
12. Jakob, C.: Accelerating progress in global atmospheric model development through improved parametrizations. Bull. Am. Met. Soc. 91, 869-875 (2010)
13. Jones, T.R., Randall, D.A.: Quantifying the limits of convective parameterizations. J. Geophys. Res. 116, 1-19 (2011)
14. Khouider, B., Majda, A.J., Katsoulakis, A.: Coarse grained stochastic models for tropical convection and climate. Proc. Natl. Acad. Sci. 100, 11941-11946 (2003)
15. Khouider, B., Biello, J., Majda, A.J.: A stochastic multicloud model for tropical convection. Commun. Math. Sci. 8, 187-216 (2010)
16. Lin, J.W.-B., Neelin, J.D.: Influence of a stochastic moist convective parameterization on tropical climate variability. Geophys. Res. Lett. 27, 3691-3694 (2000)
17. Lin, J.W.-B., Neelin, J.D.: Considerations for stochastic convective parameterization. J. Atmos. Sci. 59, 959-975 (2002)
18. Lin, J.W.-B., Neelin, J.D.: Toward stochastic moist convective parameterization in general circulation models. Geophys. Res. Lett. 30, 1162 (2003)
19. Lorenz, E.N.: Predictability a problem partly solved. Proc. 1995 ECMWF Seminar on Predictability, Read, UK, ECMWF, pp. 1-18 (1995)
20. MacQueen, J.B.: Some methods for classification and analysis of multivariate observations. Proc. 5th Berkeley Symp. Math. Stat. Probab. 1, 281-297 (1967)
21. Majda, A.J., Khouider, B.: Stochastic and mesoscopic models for tropical convection. Proc. Natl. Acad. Sci. 99, 1123-1128 (2002)
22. Nimsaila, K., Timofeyev, I.: Markov chain stochastic parameterizations of essential variables. Multiscale Model. Simul. 8, 2079-2096 (2010)
23. Palmer, T.N.: A nonlinear dynamical perspective on model error: A proposal for non-local stochastic-dynamic parametrization in weather and climate prediction models. Q. J. R. Meteorol. Soc. 127, 279-304 (2001)
24. Plant, R.S., Craig, G.C.: A stochastic parameterization for deep convection based on equilibrium statistics. J. Atmos. Sci. 65, 10-87 (2008)
25. Shutts, G.J., Palmer, T.N.: Convective forcing fluctuations in a cloud-resolving model: relevance to the stochastic parameterization problem. J. Clim. 20, 187-202 (2007)
26. Siebesma, A.P., Bretherton, C.S., Brown, A., Chlond, A., Cuxart, J., Duynkerke, P.G., Jiang, H., Khairoutdinov, M., Lewellen, D., Moeng, C.-H., Sanchez, E., Stevens, B., Stevens, D.E.: A Large-Eddy Simulation intercomparison study of shallow cumulus convection. J. Atmos. Sci. 60, 1201-1219 (2003)
27. Siebesma, A.P., Cuijpers, J.W.M.: Evaluation of parametric assumptions for shallow cumulus convection. J. Atmos. Sci. 52, 650-666 (1995)
28. Siebesma, A.P., Soares, P.M.M., Teixeira, J.: A combined Eddy-Diffusivity mass-flux approach for the convective boundary layer. J. Atmos. Sci. 64, 1230-1248 (2007)
29. Siebesma, A.P.: Shallow cumulus convection. In: Siebesma, A.P., Plate, E.J., Fedorovich, E.E., Viegas, X.V., Wyngaard, J.C. (eds.) Buoyant Convection in Geophysical Flows, pp. 441-486. Kluwer, Pforzheim (1998)
30. Teixeira, J., Reynolds, C.A.: Stochastic nature of physical parameterizations in ensemble prediction: a stochastic convection approach. Mon. Weather Rev. 136, 483-496 (2008)
31. Tsai, W.H.: Moment-preserving thresholding: a new approach. Comput. Vis. Graph. Image Process. 29, 377-393 (1985)
32. Wyngaard, J.C.: Toward numerical modeling in the "Terra Incognita". J. Atmos. Sci. 61, 1816-1826 (2004)
33. Yu, X., Lee, T.-Y.: Role of convective parameterization in simulations of a convection band at grey-zone resolutions. Tellus A 62, 617-632 (2010)