Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

Journal of Advances in Modeling Earth Systems

Volumn 9, Issue 3, 2017, Pages 1542-1571

  Parishani, Hossein ^a   Pritchard, Michael S ^a   Bretherton, Christopher S ^b   Wyant, Matthew C ^b   Khairoutdinov, Marat ^c  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

^c STONY BROOK UNIVERSITY   (United States)

Author keywords

cloud resolving model; general circulation model; marine boundary layer; shallow clouds; superparameterization; ultraparameterization

Indexed keywords

ATMOSPHERIC THERMODYNAMICS; BOUNDARY LAYERS; COASTAL ZONES; TURBULENCE;

CLOUD RESOLVING MODEL; GENERAL CIRCULATION MODEL; MARINE BOUNDARY LAYERS; SHALLOW CLOUDS; SUPERPARAMETERIZATION; ULTRAPARAMETERIZATION;

CLIMATE MODELS;

BOUNDARY LAYER; CLIMATE MODELING; CLOUD MICROPHYSICS; CONVECTION; GENERAL CIRCULATION MODEL; GLOBAL CLIMATE; PARAMETERIZATION; SATELLITE DATA; SIMULATION; SPACING; STRATOCUMULUS; TURBULENCE; VOLCANIC CLOUD;

EID: 85021736685     PISSN: None     EISSN: 19422466     Source Type: Journal    
DOI: 10.1002/2017MS000968     Document Type: Article

References (67)

1. Ackerman, A., O. Toon, D. Stevens, and J. Coakley Jr. (2003), Enhancement of cloud cover and suppression of nocturnal drizzle in stratocumulus polluted by haze, Geophys. Res. Lett., 30(7), 1381, doi:10.1029/2002GL016634.
2. Benedict, J. J., and D. A. Randall (2009), Structure of the Madden-Julian Oscillation in the superparameterized CAM, J. Atmos. Sci., 66(11), 3277–3296, doi:10.1175/2009JAS3030.1.
3. Berner, A., C. Bretherton, and R. Wood (2011), Large-eddy simulation of mesoscale dynamics and entrainment around a pocket of open cells observed in VOCALS-REx RF06, Atmos. Chem. Phys., 11, 10,525–10,540.
4. Bogenschutz, P., and S. Krueger (2013), A simplified PDF parameterization of subgrid-scale clouds and turbulence for cloud-resolving models, J. Adv. Model. Earth Syst., 5, 195–211, doi:10.1002/jame.20018.
5. Bogenschutz, P., A. Gettelman, H. Morrison, V. Larson, C. Craig, and D. Schanen (2013), Higher-order turbulence closure and its impact on climate simulations in the Community Atmosphere Model, J. Clim., 26, 9655–9676.
6. Bony, S., and J. Dufresne (2005), Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models, Geophys. Res. Lett., 32, L20806, doi:10.1029/2005GL023851.
7. Bretherton, C., et al. (1999), An intercomparison of radiatively-driven entrainment and turbulence in a smoke cloud, as simulated by different numerical models, Q. J. R. Meteorol. Soc., 125, 391–423.
8. Bretherton, C., R. Wood, R. George, D. Leon, G. Allen, and X. Zheng (2010), Southeast Pacific stratocumulus clouds, precipitation and boundary layer structure sampled along 20 S during VOCALS-REx, Atmos. Chem. Phys., 10, 10,639–10,654.
9. Bretherton, C. S., and M. C. Wyant (1997), Moisture transport, lower tropospheric stability and decoupling of cloud-topped boundary layers, J. Atmos. Sci., 54, 148–167.
10. Burleyson, C., S. de Szoeke, S. Yuter, M. Wilbanks, and W. A. Brewer (2013), Observations of the diurnal cycle of Southeast Pacific marine stratocumulus clouds and precipitation, J. Atmos. Sci., 70, 3876–3894.
11. Cheng, A., and K. Xu (2008), Simulation of boundary-layer cumulus and stratocumulus clouds using a cloud-resolving model with low- and third-order turbulence closures, J. Meteorol. Soc. Jpn., 86A, 67–86.
12. Cheng, A., and K. Xu (2013a), Diurnal variability of low clouds in the Southeast Pacific simulated by a multiscale modeling framework model, J. Geophys. Res. Atmos., 118, 9191–9208, doi:10.1002/jgrd.50683.
13. Cheng, A., and K. Xu (2013b), Evaluating low cloud simulation from an upgraded multiscale modeling framework. Part III: Tropical and subtropical cloud transitions over the northern Pacific, J. Clim., 26, 5761–5781.
14. Cheng, A., and K.-M. Xu (2011), Improved low-cloud simulation from a multiscale modeling framework with a third-order turbulence closure in its cloud-resolving model component, J. Geophys. Res., 116, D14101, doi:10.1029/2010JD015362.
15. Cheng, A., and K.-M. Xu (2015), Improved low-cloud simulation from the Community Atmosphere Model with an advanced third-order turbulence closure, J. Clim., 28, 5737–5762.
16. Cheng, A., X. K-M., and B. Stevens (2010), Effects of resolution on the simulation of boundary-layer clouds and the partition of kinetic energy to subgrid scales, J. Adv. Model. Earth Syst., 2, 3, doi:10.3894/JAMES.2010.2.3.
17. Demott, C. A., D. A. Randall, and M. Khairoutdinov (2007), Convective precipitation variability as a tool for general circulation model analysis, J. Clim., 20(1), 91–112.
18. de Szoeke, S., et al. (2012), Observations of stratocumulus and their effect on the eastern Pacific surface heat budget along 20S, J. Clim., 25, 8542–8567.
19. Flato, G., et al. (2013), Evaluation of climate models, Chapter 9, 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 T. F. Stocker, eds., Cambridge University Press, Cambridge, U. K. and New York.
20. Gettelman, A., and S. C. Sherwood (2016), Processes responsible for cloud feedback, Curr. Clim. Change Rep., 2, 179–189, doi:10.1007/s40641-016-0052-8.
21. Grabowski, W. (2001), Coupling cloud processes with the large-scale dynamics using the cloud-resolving convection parameterization (CRCP), J. Atmos. Sci., 58(9), 978–997.
22. Grabowski, W. (2016), Towards global large eddy simulation: Super-parameterization revisited, J. Meteorol. Soc. Jpn., 94, 327–344.
23. Gustafson, W., L. Berg, R. Easter, and S. Ghan (2008), The explicit-cloud parameterized-pollutant hybrid approach for aerosol-cloud interactions in multiscale modeling framework models: Tracer transport results, Environ. Res. Lett., 3, 025005.
24. Jones, C., C. Bretherton, and D. Leon (2011), Coupled vs. decoupled boundary layers in VOCALS-REx, Atmos. Chem. Phys., 11, 7143–7153.
25. Jones, C., C. Bretherton, and M. Pritchard (2015), Mean-state acceleration of cloud-resolving models and large eddy simulations, J. Adv. Model. Earth Syst., 7, 1643–1660, doi:10.1002/2015MS000488.
26. Kato, S., S. Sun-Mack, W. F. Miller, F. G. Rose, Y. Chen, P. Minnis, and B. A. Wielicki (2010), Relationships among cloud occurrence frequency, overlap, and effective thickness derived from CALIPSO and CloudSat merged cloud vertical profiles, J. Geophys. Res., 115, D00H28, doi:10.1029/2009JD012277.
27. Kato, S., et al. (2011), Improvements of top-of-atmosphere and surface irradiance computations with CALIPSO-, CloudSat-, and MODIS-derived cloud and aerosol properties, J. Geophys. Res., 116, D19209, doi:10.1029/2011JD016050.
28. Kay, J., et al. (2012), Exposing global cloud biases in the Community Atmosphere Model (CAM) using satellite observations and their corresponding instrument simulators, J. Clim., 25, 5190–5207, doi:10.1175/JCLI-D-11-00469.1.
29. Khairoutdinov, M., D. Randall, and C. DeMott (2005), Simulations of the atmospheric general circulation using a cloud-resolving model as a superparameterization of physical processes, J. Atmos. Sci., 62(7), 2136–2154.
30. Khairoutdinov, M., C. DeMott, and D. Randall (2008), Evaluation of the simulated interannual and subseasonal variability in an AMIP-style simulation using the CSU multi-scale modeling framework, J. Clim., 21(3), 413–431.
31. Khairoutdinov, M. F., and D. A. Randall (2001), A cloud resolving model as a cloud parameterization in the NCAR community climate system model: Preliminary results, Geophys. Res. Lett., 28, 3617–3620.
32. Khairoutdinov, M. F., and D. A. Randall (2003), Cloud resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities, J. Atmos. Sci., 60(4), 607–625.
33. Kooperman, G., M. Pritchard, M. Burt, M. Branson, and D. Randall (2016), Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model, J. Adv. Model. Earth Syst., 8, 140–165, doi:10.1002/2015MS000574.
34. Lamarque, J.-F., et al. (2010), Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: Methodology and application, Atmos. Chem. Phys., 10(15), 7017–7039.
35. Marchand, R., and T. Ackerman (2010), An analysis of cloud cover in multiscale modeling framework global climate model simulations using 4 and 1 km horizontal grids, J. Geophys. Res., 115, D16207, doi:10.1029/2009JD013423.
36. Marchand, R., and T. Ackerman (2011), A cloud-resolving model with an adaptive vertical grid for boundary layer clouds, J. Atmos. Sci., 68, 1058–1074.
37. Marchand, R., J. Haynes, G. Mace, and T. Ackerman (2009), A comparison of simulated cloud radar output from the multiscale modeling framework global climate model with cloudsat cloud radar observations, J. Geophys. Res., 114, D00A20, doi:10.1029/2008JD009790.
38. Medeiros, B., and L. Nuijens (2016), Clouds at Barbados are representative of clouds across the trade wind regions in observations and climate models, Proc. Natl. Acad. Sci. U. S. A., 113, E3062–3070, doi:10.1073/pnas.1521494113.
39. Mellado, J. (2017), Cloud-top entrainment in stratocumulus clouds, Annu. Rev. Fluid Mech., 49, 145–169.
40. Moeng, C., S. Shen, and D. Randall (1992), Physical processes within the nocturnal stratus-topped boundary layer, J. Atmos. Sci., 49, 2384–2401.
41. Nicholls, S. (1984), The dynamics of stratocumulus: Aircraft observations and comparisons with a mixed layer model, Q. J. R. Meteorol. Soc., 110, 783–820.
42. Nuijens, L., I. Serikov, L. Hirsch, K. Lonitz, and B. Stevens (2014), The distribution and variability of low-level cloud in the North Atlantic trades, Q. J. R. Meteorol. Soc., 140, 2364–2374.
43. Nuijens, L., B. Medeiros, I. Sandu, and M. Ahlgrimm (2015), Observed and modeled patterns of covariability between low-level cloudiness and the structure of the trade-wind layer, J. Adv. Model. Earth Syst., 7, 1741–1764, doi:10.1002/2015MS000483.
44. Painemal, D., K. Xu, A. Cheng, P. Minnis, and R. Palikonda (2015), Mean structure and diurnal cycle of southeast Atlantic boundary layer clouds: Insights from satellite observations and Multiscale Modeling Framework simulations, J. Clim., 28, 324–341.
45. Park, S., and C. S. Bretherton (2009), The University of Washington shallow convection and moist turbulence schemes and their impact on climate simulations with the Community Atmosphere Model, J. Clim., 22, 3449–3469.
46. Pritchard, M. S., and R. C. J. Somerville (2009a), Empirical orthogonal function analysis of the diurnal cycle of precipitation in a multi-scale climate model, Geophys. Res. Lett., 36, L05812, doi:10.1029/2008GL036964.
47. Pritchard, M. S., and R. C. J. Somerville (2009b), Assessing the diurnal cycle of precipitation in a multi-scale climate model, J. Adv. Model. Earth Syst., 2, 12, doi:10.3894/JAMES.2009.1.12.
48. Pritchard, M. S., M. W. Moncrieff, and R. C. J. Somerville (2011), Orogenic propagating precipitation systems over the US in a global climate model with embedded explicit convection, J. Atmos. Sci., 68, 1821–1840.
49. Pritchard, M. S., C. S. Bretherton, and C. A. DeMott (2014), Restricting 32–128 km horizontal scales hardly affects the MJO in the Superparameterized Community Atmosphere Model v. 3.0 but the number of cloud resolving grid columns constrains vertical mixing, J. Adv. Model. Earth Syst., 6, 723–739, doi:10.1002/2014MS000340.
50. Randall, D., et al. (2007), Climate models and their evaluation, in Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, chap. 8, pp. 589–662, Cambridge Univ. Press, Cambridge, U. K.
51. Seifert, A., T. Heus, R. Pincus, and B. Stevens (2015), Large-eddy simulation of the transient and near-equilibrium behavior of precipitating shallow convection, J. Adv. Model. Earth Syst., 7, 1918–1937, doi:10.1002/2015MS000489.
52. Siebesma, A., et al. (2003), A large eddy simulation intercomparison study of shallow cumulus convection, J. Atmos. Sci., 60(10), 1201–1219.
53. Stevens, B., et al. (2003), On entrainment rates in nocturnal marine stratocumulus, Q. J. R. Meteorol. Soc., 129, 3469–3493.
54. Stevens, B., et al. (2005), Evaluation of large-eddy simulations via observations of nocturnal marine stratocumulus, Mon. Weather Rev., 133, 1443–1462.
55. Stubenrauch, C., et al. (2013), Assessment of global cloud datasets from satellites: Project and database initiated by the GEWEX radiation panel, Bull. Am. Meteorol. Soc., 94, 1031–1049.
56. Tompkins, A. M. (2001), Organization of tropical convection in low vertical wind shears: The role of cold pools, J. Atmos. Sci., 58, 1650–1672.
57. Van der Dussen, J. J., S. R. de Roode, A. S. Ackerman, P. N. Blossey, C. S. Bretherton, M. J. Kurowski, A. P. Lock, R. A. J. Neggers, I. Sandu, and A. P. Siebesma (2013), The GASS/EUCLIPSE model intercomparison of the stratocumulus transition as observed during ASTEX: LES results, J. Adv. Model. Earth Syst., 5, 483–499, doi:10.1002/jame.20033.
58. Waliser, D., et al. (2012), The year of tropical convection (May 2008–April 2010) climate variability and weather highlights, Bull. Am. Meteorol. Soc., 93, 1189–1218.
59. Wang, H., and G. Feingold (2009), Modeling mesoscale cellular structures and drizzle in marine stratocumulus. Part I: Impact of drizzle on the formation and evolution of open cells, J. Atmos. Sci., 66, 3257–3275, doi:10.1175/2009JAS3120.1.
60. Wang, M., et al. (2011), The multi-scale aerosol-climate model PNNL-MMF: Model description and evaluation, Geosci. Model Dev., 4, 137–168.
61. Wang, M., V. E. Larson, S. Ghan, M. Ovchinnikov, D. P. Schanen, H. Xiao, X. Liu, P. Rasch, and Z. Guo (2015), A multiscale modeling framework model (superparameterized CAM5) with a higher-order turbulence closure: Model description and low-cloud simulations, J. Adv. Model. Earth Syst., 7, 484–509, doi:10.1002/2014MS000375.
62. Williamson, D. L., J. G. Olson, and B. A. Boville (1998), A comparison of semi-Lagrangian and Eulerian tropical climate simulations, Mon. Weather Rev., 126, 1001–1012.
63. Wood, R. (2012), Stratocumulus clouds, Mon. Weather Rev., 140, 2373–2423.
64. Xu, K., and A. Cheng (2013a), Evaluating low-cloud simulation from an upgraded Multiscale Modeling Framework model. Part I: Sensitivity to spatial resolution and climatology, J. Clim., 26, 5717–5740.
65. Xu, K., and A. Cheng (2013b), Evaluating low-cloud simulation from an upgraded multiscale modeling framework model. Part II: Seasonal variations over the Eastern Pacific, J. Clim., 26, 5741–5760.
66. Yamaguchi, T., D. Randall, and K. M. F. (2011), Cloud modeling tests of the ULTIMATEMACHO scalar advection scheme, Mon. Weather Rev., 139, 3248–3264.
67. Zhang, Y., S. A. Klein, C. Liu, B. Tian, R. T. Marchand, J. M. Haynes, R. B. McCoy, Y. Zhang, and T. P. Ackerman (2008), On the diurnal cycle of deep convection, high-level cloud, and upper troposphere water vapor in the multiscale modeling framework, J. Geophys. Res., 113, D16105, doi:10.1029/2008JD009905.