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Climate Dynamics

, Volume 41, Issue 5–6, pp 1595–1613 | Cite as

Diagnosis and testing of low-level cloud parameterizations for the NCEP/GFS model using satellite and ground-based measurements

  • Hyelim Yoo
  • Zhanqing LiEmail author
  • Yu-Tai Hou
  • Steve Lord
  • Fuzhong Weng
  • Howard W. Barker
Article
Part of the following topical collections:
  1. Topical Collection on Climate Forecast System Version 2 (CFSv2)

Abstract

The objective of this study is to investigate the quality of clouds simulated by the National Centers for Environmental Prediction global forecast system (GFS) model and to examine the causes for some systematic errors seen in the simulations through use of satellite and ground-based measurements. In general, clouds simulated by the GFS model had similar spatial patterns and seasonal trends as those retrieved from passive and active satellite sensors, but large systematic biases exist for certain cloud regimes especially underestimation of low-level marine stratocumulus clouds in the eastern Pacific and Atlantic oceans. This led to the overestimation (underestimation) of outgoing longwave (shortwave) fluxes at the top-of-atmosphere. While temperature profiles from the GFS model were comparable to those obtained from different observational sources, the GFS model overestimated the relative humidity field in the upper and lower troposphere. The cloud condensed water mixing ratio, which is a key input variable in the current GFS cloud scheme, was largely underestimated due presumably to excessive removal of cloud condensate water through strong turbulent diffusion and/or an improper boundary layer scheme. To circumvent the problem associated with modeled cloud mixing ratios, we tested an alternative cloud parameterization scheme that requires inputs of atmospheric dynamic and thermodynamic variables. Much closer agreements were reached in cloud amounts, especially for marine stratocumulus clouds. We also evaluate the impact of cloud overlap on cloud fraction by applying a linear combination of maximum and random overlap assumptions with a de-correlation length determined from satellite products. Significantly better improvements were found for high-level clouds than for low-level clouds, due to differences in the dominant cloud geometry between these two distinct cloud types.

Keywords

Marine stratocumulus cloud NCEP global forecast system Cloud parameterization scheme Cloud overlap 

Notes

Acknowledgments

We are grateful to Drs. Brad Ferrier and Shrinivas Moorthi of NOAA/NCEP for their helps with the GFS model. The authors have been supported by grants of the National Basic Research Program (2013CB955804), NSF(AGS1118325), NASA (NNX08AH71G) and DOE (DESC0007171), and NOAA GOES-R program.

References

  1. Ackerman SA, Strabala KI, Menzel WP, Frey RA, Moeller CC, Gumley LE (1998) Discriminating clear-sky from clouds with MODIS. J Geophys Res 103:32, 141–32, 158Google Scholar
  2. Ahlgrimm M, Forbes R (2012) The impact of low clouds on surface shortwave radiation in the ECMWF model. Mon Weather Rev. doi: 10.1175/MWR-D-11-00316.1
  3. Ahlgrimm M, Köhler M (2010) Evaluation of trade cumulus in the ECMWF model with observations from CALIPSO. Mon Weather Rev. doi: 10.1175/2010MWR3320.1
  4. Aumann HH et al (2003) AIRS/AMSU/HSB on the aqua mission: design, science objectives, data products, and processing systems. IEEE T Geosci Remote 41:253–264CrossRefGoogle Scholar
  5. Barker HW (2008) Overlap of fractional cloud for radiation calculations in GCMs: a global analysis using CloudSat and CALIPSO data. J Geophys Res. doi: 10.1029/2007JD009677
  6. Barker HW, Stephens GL, Fu Q (1999) The sensitivity of domain averaged solar fluxes to assumptions about cloud geometry. Q J R Meteorol Soc 125:2127–2152CrossRefGoogle Scholar
  7. Barnes WL, Pagano TS, Salomonson VV (1998) Prelaunch characteristics of the moderate resolution imaging spectroradiometer (MODIS) on EOS-AM1. IEEE T Geosci Remote 36:1088–1100CrossRefGoogle Scholar
  8. Bony S, Dufresne JL (2005) Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophys Res Lett. doi: 10.1029/2005GL023851
  9. Boutle IA, Abel SJ (2012) Microphysical controls on the stratocumulus topped boundary-layer structure during VOCALS-REx. Atmos Chem Phys. doi: 10.5194/acp-12-2849-2012
  10. Boutle IA, Morcrette CJ (2010) Parametrization of area cloud fraction. Atmos Sci Lett. doi:  10.1002/asl.293
  11. Brent RP (1973) Algorithms for minimization without derivatives. Englewood Cliffs, New JerseyGoogle Scholar
  12. Chahine MT et al (2006) The atmospheric infrared sounder (AIRS): improving weather forecasting and providing new data on greenhouse gases. Bull Am Meteor Soc. doi: 10.1175/BAMS-87-7-911
  13. Chang FL, Li Z (2005a) A new method for detection of cirrus overlapping water clouds and determination of their optical properties. J Atmos Sci 62:3993–4009CrossRefGoogle Scholar
  14. Chang FL, Li Z (2005b) A near-global climatology of single-layer and overlapped clouds and their optical properties retrieved from Terra/MODIS data using a new algorithm. J Clim 18:4752–4771CrossRefGoogle Scholar
  15. Clothiaux EE, Ackerman TP, Mace GG, Moran KP, Marchand RT, Miller M, Martner BE (2000) Objective determination of cloud heights and radar reflectivities using a combination of active remote sensors at the ARM CART Sites. J Appl Meteor 39:645–665CrossRefGoogle Scholar
  16. Collins WD (2001) Parameterization of generalized cloud overlap for radiative calculations in general circulation models. J Atmos Sci 58:3224–3242CrossRefGoogle Scholar
  17. Dai A, Trenberth KE (2004) The diurnal cycle and its depiction in the community climate system model. J Clim 17:930–951CrossRefGoogle Scholar
  18. de Szoeke SP, Wang Y, Xie SP, Miyama T (2006) Effect of shallow cumulus convection on the eastern Pacific climate in a coupled model. Geophys Res Lett. doi: 10.1029/2006GL026715
  19. Divakarla MG, Barnet CD, Goldberg MD, McMillin LM, Maddy E, Wolf W, Zhou L, Liu X (2006) Validation of atmospheric infrared sounder temperature and water vapor retrievals with matched radiosonde measurements and forecasts. J Geophys Res. doi: 10.1029/2005JD006116
  20. Dupont JC, Haeffelin M, Morille Y, Comstock JM, Flynn C, Long CN, Sivaraman C, Newson RK (2011) Cloud properties derived from two lidars over the ARM SGP site. Geophys Res Lett doi: 10.1029/2010GL046274
  21. Geleyn JF, Hollingsworth A (1979) An economical analytical method for the computation of the interaction between scattering and line absorption of radiation. Contrib Atmos Phys 52:1–16Google Scholar
  22. Golaz JC, Larson VE, Cotton WR (2002) A PDF-based model for boundary layer clouds. Part I: method and model description. J Atmos Sci 59:3540–3551CrossRefGoogle Scholar
  23. Gordon CT (1992) Comparison of 30-day integrations with and without cloud-radiation interaction. Mon Weather Rev 120:1244–1277CrossRefGoogle Scholar
  24. Han J, Pan HL (2011) Revision of convection and vertical diffusion schemes in the NCEP global forecast system. Weather Forecast 26:520–533CrossRefGoogle Scholar
  25. Hannay C et al (2009) Evaluation of forecasted southeast Pacific stratocumulus in the NCAR, GFDL, and ECMWF models. J Clim 22:2871–2889CrossRefGoogle Scholar
  26. Hartmann DL et al (1992) The effect of cloud type on Earth’s energy balance: global analysis. J Clim 5:1281–1304CrossRefGoogle Scholar
  27. Hinkelman LM, Ackerman TP, Marchand RT (1999) An evaluation of NCEP Eta model predictions of surface energy budget and cloud properties by comparison with measured ARM data. J Geophys Res 104(16):19535–19594CrossRefGoogle Scholar
  28. Hogan RJ, Illingworth AJ (2000) Deriving cloud overlap statistics from radar. Q J R Meteorol Soc 128:2903–2909CrossRefGoogle Scholar
  29. Houghton JT (2001) The scientific basis. Contributions of working group i to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  30. King MD et al (2003) Cloud and aerosol properties, precipitable water, and profiles of temperature and humidity from MODIS. IEEE T Geosci Remote 41:442–458CrossRefGoogle Scholar
  31. Klein SA, Hartmann DL (1993) The seasonal cycle of low stratiform clouds. J Clim 6:1587–1606CrossRefGoogle Scholar
  32. Lazarus SM, Krueger SK, Frisch SA (1999) An evaluation of the Xu-Randall cloud fraction parameterization using ASTEX data. Preprints, 13th symposium on boundary layers and turbulence, Dallas, Texas, pp 582–585Google Scholar
  33. Liang XZ, Wu X (2005) Evaluation of a GCM subgrid cloud-radiation interaction parameterization using cloud-resolving model simulations. Geophys Res Lett. doi: 10.1029/2004GL022301
  34. Loeb NG et al (2007) Multi-instrument comparison of top-of-atmosphere reflected solar radiation. J Clim 20(3):575–591CrossRefGoogle Scholar
  35. Ma CC, Mechoso CR, Robertson AW, Arakawa A (1996) Peruvian stratus clouds and the tropical Pacific circulation: a coupled ocean-atmosphere GCM study. J Clim 9:1635–1645CrossRefGoogle Scholar
  36. Mace GG, Benson-Troth S (2002) Cloud-layer overlap characteristics derived from long-term cloud radar data. J Clim 15:2505–2515CrossRefGoogle Scholar
  37. Mace GG, Zhang Q, Vaughn M, Marchand R, Stephens G, Trepte C, Winker D (2009) A description of hydrometeor layer occurrence statistics derived from the first year of merged CloudSat and CALIPSO data. J Geophys Res. doi: 10.1029/2007JD009755
  38. Mechoso CR et al (1995) The seasonal cycle over the tropical Pacific in coupled ocean-atmosphere general circulation models. Mon Weather Rev 123:2825–2838CrossRefGoogle Scholar
  39. Menzel WP, Baum BA, Strabala KI, Frey RA (2002) Cloud top properties and cloud phase algorithm theoretical basis document. http://modis.gsfc.nasa.gov/data/atbd/atbd_mod04.pdf
  40. Moorthi S, Pan HL, Caplan P (2001) Changes to the 2001 NCEP operational MRF/AVN global analysis/forecast system. NWS Tech Proced Bull 484:14Google Scholar
  41. Morcrette JJ, Fouquart Y (1986) The overlapping of cloud layers in shortwave radiation parameterizations. J Atmos Sci 43:321–328CrossRefGoogle Scholar
  42. Morcrette JJ, Jakob C (2000) The response of the ECMWF model to changes in the cloud overlap assumption. Mon Weather Rev 128:1707–1732CrossRefGoogle Scholar
  43. Morcrette CJ, O’Connor EJ, Petch JC (2012) Evaluation of two cloud parametrization schemes using ARM and Cloudnet observations. Q J R Meteorol Soc. doi: 10.1002/qj.969
  44. Naud CM, Del Genio A, Mace GG, Benson S, Clothiaux EE, Kollias P (2008) Impact of dynamics and atmospheric state on cloud vertical overlap. J Clim. doi: 10.1175/2007JCLI1828.1
  45. Neggers R (2009) A dual mass flux framework for boundary layer convection Part II: clouds. J Atmos Sci 66:1489–1506CrossRefGoogle Scholar
  46. Norris JR (1998) Low cloud type over the ocean from surface observations. Part II: geographical and seasonal variations. J Clim 11:383–403CrossRefGoogle Scholar
  47. Oreopoulos L, Khairoutdinov MF (2003) Overlap properties of clouds generated by a cloud-resolving model. J Geophys Res. doi: 10.1029/2002JD003329
  48. Oreopoulos L, Norris PM (2011) An analysis of cloud overlap at a midlatitude atmospheric observation facility. Atmos Chem Phys. doi: 10.5194/acp-11-5557-2011
  49. Pagano TS, Auman HH, Hagan DE, Overoye K (2003) Prelaunch and in-flight radiometric calibration of the atmospheric infrared sounder (AIRS). IEEE T Geosci Remote 41:265–273CrossRefGoogle Scholar
  50. Pan HL, Wu WS (1995) Implementing a mass flux convective parameterization package for the NMC medium-range forecast model. NMC Office Note 409Google Scholar
  51. Paquin-Ricard D, Jones C, Vaillancourt PA (2010) Using ARM observations to evaluate cloud and clear-sky radiation processes as simulated by the Canadian regional climate model GEM. Mon Weather Rev 138:818–838CrossRefGoogle Scholar
  52. Pincus R, Hannay C, Klein SA, Xu KM, Hemler R (2005) Overlap assumptions for assumed probability distribution function cloud schemes in large-scale models. J Geophys Res 110, D15S09. doi: 10.1029/2004JD005100
  53. Platnick S, King MD, Ackerman SA, Menzel WP, Baum BA, Riedi JC, Frey RA (2003) The MODIS cloud products: algorithms and examples from Terra. IEEE T Geosci Remote 41:459–473CrossRefGoogle Scholar
  54. Platt CM et al (1994) The experimental cloud lidar pilot study (ECLIPS) for cloud–radiation research. Bull Am Meteor Soc 75:1635–1654CrossRefGoogle Scholar
  55. Räisänen P, Barker HW, Khairoutdinov M, Li J, Randall DA (2004) Stochastic generation of subgrid-scale cloudy columns for largescale models. Q J R Meteorol Soc 130:2047–2067CrossRefGoogle Scholar
  56. Randall DA et al (2007) The physical science basis contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University, CambridgeGoogle Scholar
  57. Rosenkranz PW (2003) Rapid radiative transfer model for AMSU/HSB channels. IEEE T Geosci Remote. doi: 10.1109/TGRS.2002.808323
  58. Rossow WB, Schiffer RA (1999) Advances in understanding clouds from ISCCP. Bull Am Meteor Soc 80:2261–2287CrossRefGoogle Scholar
  59. Rossow WB, Zhang YC (1995) Calculation of surface and top of atmosphere radiative fluxes from physical quantities based on ISCCP data sets, 2. Validation and first results. J Geophys Res 100:1167–1197CrossRefGoogle Scholar
  60. Rossow WB, Gardner LC, Lacis AA (1989) Global seasonal cloud variations from satellite radiance measurements. Part Ι: sensitivity of analysis. J Clim 2:419–458CrossRefGoogle Scholar
  61. Sengupta M, Clothiaux EE, Ackerman TP (2004) Climatology of warm boundary layer clouds at the ARM SGP site and their comparison to models. J Clim 17:4760–4782CrossRefGoogle Scholar
  62. Shonk JKP, Hogan RJ, Edwards JM, Mace GG (2010) Effect of improving representation of horizontal and vertical cloud structure on the Earth’s global radiation budget. Part I: review and parametrization. Q J R Meteorol Soc. doi: 10.1002/qj.647
  63. Slingo JM (1987) The development and verification of a cloud prediction scheme for the ECMWF model. Q J R Meteorol Soc. doi: 10.1002/qj.49711347710
  64. Stephens GL (2005) Cloud feedbacks in the climate system: a critical review. J Clim 18:237–273CrossRefGoogle Scholar
  65. Stephens GL et al (2002) The CloudSat mission and the a-train. Bull Am Meteor Soc 83:1771–1790CrossRefGoogle Scholar
  66. Stokes MG, Schwartz SE (1994) The atmospheric radiation measurement (ARM) program: programmatic background and design of the cloud and radiation test bed. Bull Am Meteor Soc 75:1201–1221CrossRefGoogle Scholar
  67. Sun R, Moorthi S, Xiao H, Mechoso CR (2010) Simulation of low clouds in the Southeast Pacific by the NCEP GFS: sensitivity to vertical mixing. Atmos Chem Phys. doi: 10.5194/acp-10-12261-2010
  68. Susskind J, Barnet CD, Blaisdell JM (2003) Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds. IEEE T Geosci Remote 41:390–409CrossRefGoogle Scholar
  69. Susskind J, Barnet C, Blaisdell J, Iredell L, Keita F, Kouvaris L, Molnar G, Chahine M (2006) Accuracy of geophysical parameters derived from atmospheric infrared sounder/advanced microwave sounding unit as a function of fractional cloud cover. J Geophys Res. doi: 10.1029/2005JD006272
  70. Tian L, Curry JA (1989) Cloud overlap statistics. J Geophys Res 94:9925–9935CrossRefGoogle Scholar
  71. Tobin DC et al (2006) Atmospheric radiation measurement site atmospheric state best estimates for atmospheric infrared sounder temperature and water vapor retrieval validation. J Geophys Res. doi: 10.1029/2005JD006103
  72. Tiedtke M (1993) Representation of clouds in large-scale models. Mon Weather Rev 121:3040–3061CrossRefGoogle Scholar
  73. Tompkins A (2002) 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 59:1917–1942CrossRefGoogle Scholar
  74. Walden VP, Roth WL, Stone RS, Halter B (2006) Radiometric validation of the atmospheric infrared sounder over the Antarctic Plateau. J. Geophys. Res. doi: 10.1029/2005JD006357
  75. Wang Z, Sassen K (2004) An improved cloud classification algorithm based on the SGP CART site observations. The Fourteenth ARM Science Team Meeting, Albuquerque, New Mexico. http://www.arm/gov/publications/proceedings.stm
  76. Warren SG, Hahn CJ, London J (1985) Simultaneous occurrence of different cloud types. J Appl Meteorol Clim 24:658–667CrossRefGoogle Scholar
  77. Watanabe M, Emori S, Satoh M, Miura H (2009) A pdf-based hybrid prognostic cloud scheme for general circulation model. Clim Dyn. doi: 10.1007/s00382-008-0489-0
  78. Webb M, Senior C, Bony S, Morcrette JJ (2001) Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Clim Dyn 17:905–922CrossRefGoogle Scholar
  79. Wielicki BA, Cess RD, King MD, Randall DA, Harrison EF (1995) Mission to planet Earth: role of clouds and radiation in climate. Bull Am Meteor Soc 76:2125–2153CrossRefGoogle Scholar
  80. Wilson DR, Bushell AC, Kerr-Munslow AM, Price JD, Morcrette CJ (2008) PC2: a prognostic cloud fraction and condensation scheme. I: scheme description. Q J R Meteorol Soc 134:2093–2107CrossRefGoogle Scholar
  81. Xi B, Dong X, Minnis P, Khaiyer M (2010) A 10-year climatology of cloud fraction and vertical distribution derived from both surface and GOES observations over the DOE ARM SGP Site. J Geophys Res. doi: 10.1029/2009JD012800
  82. Xie SP et al (2007) A regional ocean–atmosphere model for eastern Pacific climate: toward reducing tropical biases. J Clim 20:1504–1522CrossRefGoogle Scholar
  83. Xu KM, Randall DA (1996) A semiempirical cloudiness parameterization for use in climate models. J Atmos Sci 53:3084–3102CrossRefGoogle Scholar
  84. Yang F, Pan HL, Krueger SK, Moorthi S, Lord SJ (2006) Evaluation of the NCEP global forecast system at the ARM SGP site. Mon Weather Rev 134:3668–3690CrossRefGoogle Scholar
  85. Yoo HL, Li Z (2012) Evaluation of cloud properties in the NOAA/NCEP global forecast system using multiple satellite products. Clim Dyn. doi: 10.1007/s00382-012-1430-0
  86. Zhang MH et al (2005) Comparing clouds and their seasonal variations in 10 atmospheric general circulation models with satellite measurements. J Geophys Res. doi: 10.1029/2004JD005021

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hyelim Yoo
    • 1
  • Zhanqing Li
    • 1
    • 2
    Email author
  • Yu-Tai Hou
    • 3
  • Steve Lord
    • 3
  • Fuzhong Weng
    • 4
  • Howard W. Barker
    • 5
  1. 1.Dept of Atmospheric and Oceanic ScienceUniversity of MarylandCollege ParkUSA
  2. 2.State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System SciencesBeijing Normal UniversityBeijingChina
  3. 3.Environmental Modeling CenterNCEP/NWS/NOAACollege ParkUSA
  4. 4.STAR/NESDIS, NOAACollege ParkUSA
  5. 5.Environment CanadaTorontoCanada

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