Robust effects of cloud superparameterization on simulated daily rainfall intensity statistics across multiple versions of the Community Earth System Model

Journal of Advances in Modeling Earth Systems

Volumn 8, Issue 1, 2016, Pages 140-165

  Kooperman, Gabriel J ^a   Pritchard, Michael S ^a   Burt, Melissa A ^b   Branson, Mark D ^b   Randall, David A ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Engineering Research Center and Hydraulics Laboratory   (United States)

Author keywords

Community Atmosphere Model; extreme precipitation; Global Precipitation Climatology Project; rainfall intensity; superparameterization; Tropical Rainfall Measuring Mission

Indexed keywords

CAMS; CLIMATE MODELS; CLIMATOLOGY; PARAMETERIZATION; RAIN GAGES; SOIL MOISTURE;

COMMUNITY ATMOSPHERE MODEL; EXTREME PRECIPITATION; GLOBAL PRECIPITATION CLIMATOLOGY PROJECTS; RAINFALL INTENSITY; SUPERPARAMETERIZATION; TROPICAL RAINFALL MEASURING MISSIONS;

RAIN;

CLIMATE FORCING; CLIMATE MODELING; CLOUD; GLOBAL CLIMATE; MADDEN-JULIAN OSCILLATION; MONSOON; PARAMETERIZATION; PRECIPITATION INTENSITY; RAINFALL; REGIONAL PATTERN; SPATIAL RESOLUTION; STATISTICAL DATA; TRMM;

EID: 84956867463     PISSN: None     EISSN: 19422466     Source Type: Journal    
DOI: 10.1002/2015MS000574     Document Type: Article

References (91)

1. Alemohammad, S. H., K. A. McColl, A. G. Konings, D. Entekhabi, and, A. Stoffelen, (2015), Characterization of precipitation product errors across the United States using multiplicative triple collocation, Hydrol. Earth Syst. Sci., 19, 3489-3503.
2. Allan, R. P., C. Liu, M. Zahn, D. A. Lavers, E. Koukouvagias, and, A. Bodas-Salcedo, (2014), Physically consistent responses of the global atmospheric hydrological cycle in models and observations, Surv. Geophys., 35, 533-552.
3. Allen, M. R., and, W. J. Ingram, (2002), Constraints on future changes in climate and the hydrologic cycle, Nature, 419, 224-232.
4. Arakawa, A., and, W. H. Schubert, (1974), Interaction of a cumulus cloud ensemble with the large-scale environment, Part I, J. Atmos. Sci., 31, 674-701.
5. Behrangi, A., M. Lebsock, S. Wong, and, B. Lambrigtsen, (2012), On the quantification of oceanic rainfall using spaceborne sensors, J. Geophys. Res., 117, D20105, doi: 10.1029/2012JD017979.
6. 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.
7. Bretherton, C. S., and, S. Park, (2009), A new moist turbulence parameterization in the Community Atmosphere Model, J. Clim., 22, 3422-3448.
8. Campin, J.-M., C. Hill, H. Jones, and, J. Marshall, (2011), Super-parameterization in ocean modeling: Application to deep convection, Ocean Modell., 36, 90-101.
9. Cavanaugh, N. R., A. Gershunov, A. K. Panorska, and, T. J. Kozubowski, (2015), The probability distribution of intense daily precipitation, Geophys. Res. Lett., 42, 1560-1567, doi: 10.1002/2015GL063238.
10. Chou, C., C.-A. Chen, P.-H. Tan, and, K. T. Chen, (2012), Mechanisms for global warming impacts on precipitation frequency and intensity, J. Clim., 25 (9), 3291-3306.
11. Curtis, S., and, R. Adler, (2000), ENSO indices based on patterns of satellite-derived precipitation, J. Clim., 13, 2786-2793.
12. Dai, A., (2006), Precipitation characteristics in eighteen coupled climate models, J. Clim., 19, 4605-4630.
13. DeMott, C. A., D. A. Randall, and, M. Khairoutdinov, (2007), Convective precipitation variability as a tool for general circulation model analysis, J. Clim., 20, 91-112.
14. DeMott, C. A., C. Stan, D. A. Randall, J. L. Kinter III, and, M. Khairoutdinov, (2011), The Asian monsoon in the superparameterized CCSM and its relationship to tropical wave activity, J. Clim., 24, 5134-5156.
15. Dinku, T., P. Ceccato, and, S. J. Connor, (2011), Challenges of satellite rainfall estimation over mountainous and arid parts of east Africa, Int. J. Remote Sens., 30, 5965-5979.
16. Dirmeyer, P. A., C. A. Schlosser, and, K. L. Brubaker, (2009), Precipitation, recycling, and land memory: An integrated analysis, J. Hydrometeorol., 10, 278-288.
17. Gent, P. R., et al., (2011), The Community Climate System Model version 4, J. Clim., 24, 4973-4991.
18. Grabowski, W. W., (2001), Coupling cloud processes with the large-scale dynamics using the cloud-resolving convection parameterization (CRCP), J. Atmos. Sci., 58 (9), 978-997.
19. Gustafson, W. I., Jr,., L. K. Berg, R. C. Easter, and, S. J. 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, 1-7.
20. Gustafson, W. I., Jr., P.-L. Ma, and, B. Singh, (2014), Precipitation characteristics of CAM5 physics at mesoscale resolution during MC3E and the impact of convective timescale choice, J. Adv. Model. Earth Syst., 6, 1271-1287, doi: 10.1002/2014MS000334.
21. Held, I. M., and, B. J. Soden, (2006), Robust responses of the hydrological cycle to global warming, J. Clim., 19, 5686-5699.
22. Hennessy, K. J., J. M. Gregory, and, J. F. B. Mitchell, (1997), Changes in daily precipitation under enhanced greenhouse conditions, Clim. Dyn., 13, 667-680.
23. Huffman, G. J., et al., (1997), The global precipitation climatology project (GPCP) combined precipitation dataset, Bull. Am. Meteorol. Soc., 78, 5-20.
24. Huffman, G. J., R. F. Adler, M. M. Morrissey, S. Curtis, R. Joyce, B. McGavock, and, J. Susskind, (2001), Global precipitation at one-degree daily resolution from multi-satellite observations, J. Hydrometeorol., 2, 36-50.
25. Huffman, G. J., D. T. Bolvin, E. J. Nelkin, D. B. Wolff, R. F. Adler, G. Gu, Y. Hong, K. P. Bowman, and, E. F. Stocker, (2007), The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales, J. Hydrometeorol., 8, 38-55.
26. Huffman, G. J., D. T. Bolvin, and, R. F. Adler, (2012a), GPCP Version 1.2 1-Degree Daily (1DD) Precipitation Data Set, World Data Center A, National Climatic Data Center, Asheville, N. C. [Available at ftp://rsd.gsfc.nasa.gov/pub/1dd-v1.2/.]
27. Huffman, G. J., E. F. Stocker, D. T. Bolvin, E. J. Nelkin, and, R. F. Adler, (2012b), TRMM Version 7 3B42 and 3B43 Data Sets, National Aeronautics and Space Administration/Goddard Space Flight Center, Greenbelt, Md. [Available at http://mirador.gsfc.nasa.gov.]
28. Hunke, E. C., and, W. H. Lipscomb, (2008), CICE: The Los Alamos sea ice model user's manual, version 4, Tech. Rep. LA-CC-06-012, 76 pp., Los Alamos Natl. Lab., Los Alamos, NM.
29. Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and, W. D. Collins, (2008), Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res., 113, D13103, doi: 10.1029/2008JD009944.
30. Jones, C. R., C. S. Bretherton, and, M. S. Pritchard, (2015), Mean state acceleration of cloud resolving models and large eddy simulations, J. Adv. Model. Earth Syst., 7, 1-18, doi:10.1002/2015MS000488.
31. 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.
32. 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 (18), 3617-3620.
33. 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, 607-625.
34. Kooperman, G. J., M. S. Pritchard, and, R. C. J. Somerville, (2013), Robustness and sensitivities of Central U.S. summer convection in the super-parameterized CAM: Multi-model intercomparison with a new regional EOF index, Geophys. Res. Lett., 40, 3287-3291, doi: 10.1002/grl.50597.
35. 2 climate change in conventional and super-parameterized versions of the NCAR Community Atmosphere Model, J. Adv. Model. Earth Syst., 6, 859-882, doi:10.1002/2014MS000306.
36. Kopparla, P., E. M. Fischer, C. Hannay, and, R. Knutti, (2013), Improved simulation of extreme precipitation in a high-resolution atmosphere model, Geophys. Res. Lett., 40, 5803-5808, doi: 10.1002/2013GL057866.
37. Koster, R. D., et al., (2004), Regions of strong coupling between soil moisture and precipitation, Science, 305 (5687), 1138-1140.
38. Lawrence, D. M., et al., (2011), Parameterization improvements and functional and structural advances in version 4 of the Community Land Model, J. Adv. Model. Earth Syst., 3, M03001, doi: 10.1029/2011MS000045.
39. Li, F., D. Rosa, W. D. Collins, and, M. F. Wehner, (2012), "Super-parameterization": A better way to simulate regional extreme precipitation?, J. Adv. Model. Earth Syst., 4, M04002, doi: 10.1029/2011MS000106.
40. Liu, C., and, R. P. Allan, (2012), Multi-satellite observed responses of precipitation and its extremes to interannual climate variability, J. Geophys. Res., 117, D03101, doi: 10.1029/2011JD016568.
41. Liu, X., et al., (2012), Toward a minimal representation of aerosols in climate models: Description and evaluation in the Community Atmosphere Model CAM5, Geosci. Model Dev., 5 (3), 709-739.
42. Mahlstein, I., R. W. Portmann, J. S. Daniel, S. Solomon, and, R. Knutti, (2012), Perceptible changes in regional precipitation in a future climate, Geophys. Res. Lett., 39, L05701, doi: 10.1029/2011GL050738.
43. Marchand, R., and, T. 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.
44. McCrary, R. R., D. A. Randall, and, C. Stan, (2014), Simulations of the West African monsoon with a superparameterized climate model. Part II: African easterly waves, J. Clim., 27, 8323-8341.
45. Morrison, H., and, A. Gettelman, (2008), A new two-moment bulk stratiform cloud microphysics scheme in the Community Atmosphere Model, version 3 (CAM3). Part I: Description and numerical tests, J. Clim., 21 (15), 3642-3659.
46. Morrison, H., J. A. Curry, and, V. I. Khvorostyanov, (2005), A new double-moment microphysics parameterization for application in cloud and climate models. Part I: Description, J. Atmos. Sci., 62 (6), 1665-1677.
47. Neale, R. B., et al., (2010a), Description of the NCAR Community Atmosphere Model (CAM 4.0), NCAR Technical Note: NCAR/TN-485+STR, Natl. Cent. for Atmos. Res., Boulder, Colo.
48. Neale, R. B., et al., (2010b), Description of the NCAR Community Atmosphere Model (CAM 5.0), NCAR Technical Note: NCAR/TN-486+STR, Natl. Cent. for Atmos. Res., Boulder, Colo.
49. O'Gorman, P. A., (2012), Sensitivity of tropical precipitation extremes to climate change, Nat. Geosci., 5, 697-700.
50. O'Gorman, P. A., (2015), Precipitation extremes under climate change, Curr. Clim. Change Rep., 1, 49-59.
51. O'Gorman, P. A., and, T. Schneider, (2009), The physical basis for increases in precipitation extremes in simulations of 21st-century climate change, Proc. Natl. Acad. Sci. U. S. A., 106 (35), 14,773-14,777.
52. Panorska, A. K., A. Gershunov, and, T. J. Kozubowski, (2007), From diversity to volatility: Probability of daily precipitation extremes, in Nonlinear Dynamics in Geophysics, edited by, A. A. Tsonis, and, J. B. Elsner, pp. 465-484, Springer, N. Y.
53. 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 (12), 3449-3469.
54. Peel, M. C., B. L. Finlayson, and, T. A. McMahon, (2007), Updated world map of the Koppen-Geiger climate classification, Hydrol. Earth Syst. Sci., 11, 1633-1644.
55. Pendergrass, A. G., and, D. L. Hartmann, (2014a), The atmospheric energy constraint on global-mean precipitation change, J. Clim., 27, 757-768.
56. Pendergrass, A. G., and, D. L. Hartmann, (2014b), Two modes of change of the distribution of rain, J. Clim., 27, 8357-8371.
57. Pendergrass, A. G., and, D. L. Hartmann, (2014c), Changes in the distribution of rain frequency and intensity in response to global warming, J. Clim., 27, 8372-8383.
58. Polade, S. D., D. W. Pierce, D. R. Cayan, A. Gershunov, and, M. D. Dettinger, (2014), The key role of dry days in changing regional climate and precipitation regimes, Nat. Sci. Rep., 4, 4364, 1-8.
59. Pritchard, M. S., and, C. S. Bretherton, (2014), Causal evidence that rotational moisture advection is critical to the superparameterized Madden-Julian oscillation, J. Atmos. Sci., 71, 800-815.
60. Pritchard, M. S., and, R. C. J. Somerville, (2009a), Assessing the diurnal cycle of precipitation in a multi-scale climate model, J. Adv. Model. Earth Syst., 1, 12, 1-16, doi:10.3894/JAMES.2009.
61. Pritchard, M. S., and, R. C. J. Somerville, (2009b), 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.
62. Pritchard, M. S., M. W. Moncrieff, and, R. C. J. Somerville, (2011), Orogenic propagating precipitation systems over the United States in a global climate model with embedded explicit convection, J. Atmos. Sci., 68 (8), 1821-1840.
63. 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.
64. Ramirex, J. A., and, S. U. S. Senarath, (2000), A statistical-dynamical parameterization of interception and land surface-atmosphere interactions, J. Clim., 13, 4050-4063.
65. Randall, D., M. Khairoutdinov, A. Arakawa, and, W. Grabowski, (2003), Breaking the cloud parameterization deadlock, Bull. Am. Meteorol. Soc., 84 (11), 1547-1564.
66. Rasch, P. J., M. J. Stevens, L. Ricciardulli, A. Dai, A. Negri, R. Wood, B. A. Boville, B. Eaton, and, J. J. Hack, (2006), A characterization of tropical transient activity in the CAM3 atmospheric hydrologic cycle, J. Clim., 19, 2222-2242.
67. Raymond, D. J., and, A. M. Blyth, (1992), Extension of the stochastic mixing model to cumulonimbus clouds, J. Atmos. Sci., 49 (21), 1968-1983.
68. Richter, J. H., and, P. J. Rasch, (2008), Effects of convective momentum transport on the atmospheric circulation in the Community Atmosphere Model, version 3, J. Clim., 21, 1487-1499.
69. Rosa, D., and, W. D. Collins, (2013), A case study of sub-daily simulated and observed continental convective precipitation: CMIP5 and multiscale global climate models comparison, Geophys. Res. Lett., 40, 5999-6003, doi:10.1002/2013GL057987.
70. Rossow, W. B., A. Mekonnen, C. Pearl, and, W. Goncalves, (2013), Tropical precipitation extremes, J. Clim., 26, 1457-1466.
71. Seager, R., N. Naik, and, G. A. Vecchi, (2010), Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming, J. Clim., 23, 4651-4668.
72. Seneviratne, S. I., T. Corti, E. L. Davin, M. Hirschi, E. B. Jaeger, I. Lehner, B. Orlowsky, and, A. J. Teuling, (2010), Investigating soil moisture-climate interactions in a changing climate: A review, Earth Sci. Rev., 99, 125-161.
73. Smith, R. D., et al., (2010), The parallel ocean program (POP) reference manual, Tech. Rep. LAUR-10-01853, 140 pp., Los Alamos Natl. Lab., Los Alamos, NM.
74. Stan, C., and, L. Xu, (2014), Climate simulations and projections with a super-parameterized climate model, Environ. Modell. Software, 60, 134-152.
75. Stan, C., M. Khairoutdinov, C. A. DeMott, V. Krishnamurthy, D. M. Straus, D. A. Randall, J. L. Kinter III, and, J. Shukla, (2010), An ocean-atmosphere climate simulation with an embedded cloud resolving model, Geophys. Res. Lett., 37, L01702, doi: 10.1029/2009GL040822.
76. Stephens, G. L., and, T. D. Ellis, (2008), Controls of global-mean precipitation increases in global warming GCM experiments, J. Clim., 21, 6141-6155.
77. Stocker, T. F., D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and, P. M. Midgley, (Eds.) (2013), Climate change 2013: The physical science basis, in Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge Univ. Press, Cambridge, U. K.
78. Sun, Y., S. Solomon, A. Dai, and, R. W. Portmann, (2006), How often does it rain?, J. Clim., 19, 916-934.
79. Sun, Y., S. Solomon, A. Dai, and, R. W. Portmann, (2007), How often will it rain?, J. Clim., 20, 4801-4818.
80. Susskind, J., P. Piraino, L. Rokke, L. Iredell, and, A. Mehta, (1997), Characteristics of the TOVS pathfinder path A dataset, Bull. Am. Meteorol. Soc., 78, 1449-1472.
81. Tan, J., C. Jakob, W. B. Rossow, and, G. Tselioudis, (2015), Increases in tropical rainfall driven by changes in frequency of organized deep convection, Nature, 519, 451-454.
82. Tao, W.-K., et al., (2009), The Goddard multi-scale modeling system with unified physics, Ann. Geophys., 27, 3055-3064.
83. Taylor, K. E., R. J. Stouffer, and, G. A. Meehl, (2012), An overview of CMIP5 and the experiment design, Bull. Am. Meteorol. Soc., 93, 485-498.
84. Trenberth, K. E., (2011), Changes in precipitation with climate change, Clim. Res., 47, 123-138.
85. Trenberth, K. E., A. Dai, R. M. Rasmussen, and, D. B. Parsons, (2003), The changing character of precipitation, Bull. Am. Meteorol. Soc., 84, 1205-1217.
86. Tulich, S. N., (2015), A strategy for representing the effects of convective momentum transport in multiscale models: Evaluation using a new superparameterized version of the Weather Research and Forecast model (SP-WRF), J. Adv. Model. Earth Syst., 7, 938-962, doi: 10.1002/2014MS000417.
87. Wang, M., et al., (2011), The multi-scale aerosol-climate model PNNL-MMF: Model description and evaluation, Geosci. Model Dev., 4 (1), 137-168.
88. Watterson, I., and, M. Dix, (2003), Simulated changes due to global warming in daily precipitation means and extremes and their interpretation using the gamma distribution, J. Geophys. Res., 108 (D13), 4379, doi: 10.1029/2002JD002928.
89. Wolff, D. B., and, B. L. Fisher, (2009), Assessing the relative performance of microwave-based satellite rain-rate retrievals using TRMM ground validation data, J. Appl. Meteorol. Climatol., 48 (6), 1069-1099.
90. Yang, Q., L. R. Leung, S. A. Rauscher, T. D. Ringler, and, M. A. Taylor, (2014), Atmospheric moisture budget and spatial resolution dependence of precipitation extremes in aquaplanet simulations, J. Clim., 27, 3565-3581.
91. Zhang, G. J., and, N. A. McFarlane, (1995), Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian climate center general-circulation model, Atmos. Ocean, 33 (3), 407-446.