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.
Similar content being viewed by others
References
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, 158
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
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
Aumann HH et al (2003) AIRS/AMSU/HSB on the aqua mission: design, science objectives, data products, and processing systems. IEEE T Geosci Remote 41:253–264
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
Barker HW, Stephens GL, Fu Q (1999) The sensitivity of domain averaged solar fluxes to assumptions about cloud geometry. Q J R Meteorol Soc 125:2127–2152
Barnes WL, Pagano TS, Salomonson VV (1998) Prelaunch characteristics of the moderate resolution imaging spectroradiometer (MODIS) on EOS-AM1. IEEE T Geosci Remote 36:1088–1100
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
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
Boutle IA, Morcrette CJ (2010) Parametrization of area cloud fraction. Atmos Sci Lett. doi: 10.1002/asl.293
Brent RP (1973) Algorithms for minimization without derivatives. Englewood Cliffs, New Jersey
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
Chang FL, Li Z (2005a) A new method for detection of cirrus overlapping water clouds and determination of their optical properties. J Atmos Sci 62:3993–4009
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 18:4752–4771
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 39:645–665
Collins WD (2001) Parameterization of generalized cloud overlap for radiative calculations in general circulation models. J Atmos Sci 58:3224–3242
Dai A, Trenberth KE (2004) The diurnal cycle and its depiction in the community climate system model. J Clim 17:930–951
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
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
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
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 52:1–16
Golaz JC, Larson VE, Cotton WR (2002) A PDF-based model for boundary layer clouds. Part I: method and model description. J Atmos Sci 59:3540–3551
Gordon CT (1992) Comparison of 30-day integrations with and without cloud-radiation interaction. Mon Weather Rev 120:1244–1277
Han J, Pan HL (2011) Revision of convection and vertical diffusion schemes in the NCEP global forecast system. Weather Forecast 26:520–533
Hannay C et al (2009) Evaluation of forecasted southeast Pacific stratocumulus in the NCAR, GFDL, and ECMWF models. J Clim 22:2871–2889
Hartmann DL et al (1992) The effect of cloud type on Earth’s energy balance: global analysis. J Clim 5:1281–1304
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):19535–19594
Hogan RJ, Illingworth AJ (2000) Deriving cloud overlap statistics from radar. Q J R Meteorol Soc 128:2903–2909
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, Cambridge
King MD et al (2003) Cloud and aerosol properties, precipitable water, and profiles of temperature and humidity from MODIS. IEEE T Geosci Remote 41:442–458
Klein SA, Hartmann DL (1993) The seasonal cycle of low stratiform clouds. J Clim 6:1587–1606
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 582–585
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
Loeb NG et al (2007) Multi-instrument comparison of top-of-atmosphere reflected solar radiation. J Clim 20(3):575–591
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 9:1635–1645
Mace GG, Benson-Troth S (2002) Cloud-layer overlap characteristics derived from long-term cloud radar data. J Clim 15:2505–2515
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
Mechoso CR et al (1995) The seasonal cycle over the tropical Pacific in coupled ocean-atmosphere general circulation models. Mon Weather Rev 123:2825–2838
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
Moorthi S, Pan HL, Caplan P (2001) Changes to the 2001 NCEP operational MRF/AVN global analysis/forecast system. NWS Tech Proced Bull 484:14
Morcrette JJ, Fouquart Y (1986) The overlapping of cloud layers in shortwave radiation parameterizations. J Atmos Sci 43:321–328
Morcrette JJ, Jakob C (2000) The response of the ECMWF model to changes in the cloud overlap assumption. Mon Weather Rev 128:1707–1732
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
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
Neggers R (2009) A dual mass flux framework for boundary layer convection Part II: clouds. J Atmos Sci 66:1489–1506
Norris JR (1998) Low cloud type over the ocean from surface observations. Part II: geographical and seasonal variations. J Clim 11:383–403
Oreopoulos L, Khairoutdinov MF (2003) Overlap properties of clouds generated by a cloud-resolving model. J Geophys Res. doi:10.1029/2002JD003329
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
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 41:265–273
Pan HL, Wu WS (1995) Implementing a mass flux convective parameterization package for the NMC medium-range forecast model. NMC Office Note 409
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 138:818–838
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
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 41:459–473
Platt CM et al (1994) The experimental cloud lidar pilot study (ECLIPS) for cloud–radiation research. Bull Am Meteor Soc 75:1635–1654
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 130:2047–2067
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, Cambridge
Rosenkranz PW (2003) Rapid radiative transfer model for AMSU/HSB channels. IEEE T Geosci Remote. doi:10.1109/TGRS.2002.808323
Rossow WB, Schiffer RA (1999) Advances in understanding clouds from ISCCP. Bull Am Meteor Soc 80:2261–2287
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 100:1167–1197
Rossow WB, Gardner LC, Lacis AA (1989) Global seasonal cloud variations from satellite radiance measurements. Part Ι: sensitivity of analysis. J Clim 2:419–458
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 17:4760–4782
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
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
Stephens GL (2005) Cloud feedbacks in the climate system: a critical review. J Clim 18:237–273
Stephens GL et al (2002) The CloudSat mission and the a-train. Bull Am Meteor Soc 83:1771–1790
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 75:1201–1221
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
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 41:390–409
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
Tian L, Curry JA (1989) Cloud overlap statistics. J Geophys Res 94:9925–9935
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
Tiedtke M (1993) Representation of clouds in large-scale models. Mon Weather Rev 121:3040–3061
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 59:1917–1942
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
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
Warren SG, Hahn CJ, London J (1985) Simultaneous occurrence of different cloud types. J Appl Meteorol Clim 24:658–667
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
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 17:905–922
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 76:2125–2153
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 134:2093–2107
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
Xie SP et al (2007) A regional ocean–atmosphere model for eastern Pacific climate: toward reducing tropical biases. J Clim 20:1504–1522
Xu KM, Randall DA (1996) A semiempirical cloudiness parameterization for use in climate models. J Atmos Sci 53:3084–3102
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 134:3668–3690
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
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
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.
Author information
Authors and Affiliations
Corresponding author
Additional information
This paper is a contribution to the Topical Collection on Climate Forecast System Version 2 (CFSv2). CFSv2 is a coupled global climate model and was implemented by National Centers for Environmental Prediction (NCEP) in seasonal forecasting operations in March 2011. This Topical Collection is coordinated by Jin Huang, Arun Kumar, Jim Kinter and Annarita Mariotti.
Rights and permissions
About this article
Cite this article
Yoo, H., Li, Z., Hou, YT. et al. Diagnosis and testing of low-level cloud parameterizations for the NCEP/GFS model using satellite and ground-based measurements. Clim Dyn 41, 1595–1613 (2013). https://doi.org/10.1007/s00382-013-1884-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00382-013-1884-8