• Brunk, H. D., 1965: An Introduction to Mathematical Statistics. Blaisdell, 429 pp.

  • Cess, R. D., G. L. Potter, W. L. Gates, J.-J. Morcrette, and L. Corsetti, 1992: Comparison of general circulation models to Earth Radiation Budget Experiment data: Computation of clear-sky fluxes. J. Geophys. Res.,97, 20421–20426.

  • Diekmann, F. J., and G. L. Smith. 1989: Investigation of scene identification algorithms for radiation budget measurements. J. Geophys. Res.,94, 3395–3412.

  • Ferraro, R. R., F. Weng, N. C. Grody, and A. Basist. 1996: An eight-year (1987–1994) time series of rainfall, clouds, water vapor, snow cover, and sea ice derived from SSM/I measurements. Bull. Amer. Meteor. Soc.,77, 891–905.

  • Fu, R., A. Del Genio, and W. B. Rossow, 1990: Behavior of deep convective clouds in the tropical Pacific deduced from ISCCP radiances. J. Climate,3, 1129–1152.

  • Gates, W. L., 1992: AMIP: The Atmospheric Model Intercomparison Project. Bull. Amer. Meteor. Soc.,73, 1962–1970.

  • Greenwald, T. J., G. L. Stephens, T. H. Vonder Haar, and D. L. Jackson, 1993: A physical retrieval of cloud liquid water over the global oceans using Special Sensor Microwave/Imager (SSM/I) observations. J. Geophys. Res.,98, 18471–18488.

  • Harrison, E. F., P. Minnis, B. R. Barkstrom, V. Ramanathan, R. D. Cess, and G. G. Gibson, 1990: Seasonal variation of cloud radiative forcing derived from the Earth Radiation Budget Experiment. J. Geophys. Res.,95, 18687–18703.

  • Hartmann, D. L., and D. Doelling, 1991: On the net radiative effectiveness of clouds. J. Geophys. Res.,96, 869–891.

  • Houghton, J. T., L. G. Meira Filho, B. A. Callander, N. Harris, A. Kattenberg, and K. Maskel, Eds., 1996: Climate Change 1995. The Science of Climate Change. Cambridge University Press, 572 pp.

  • Kalnay E., and Coauthors, 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc.,77, 437–471.

  • Li, Z., and H. G. Leighton, 1993: Global climatologies of solar radiation budgets at the surface and in the atmosphere from 5 years of ERBE data. J. Geophys. Res.,98, 4919–4930.

  • Liao, X., W. B. Rossow, and D. Rind, 1995: Comparisons between SAGE II and ISCCP high-level clouds. 1. Global and zonal mean cloud amounts. J. Geophys. Res.,100, 1121–1135.

  • Minnis, P., P. W. Heck, and D. F. Young, 1993: Inference of cirrus cloud properties using satellite-observed visible and infrared radiances. Part II: Verification of theoretical cirrus radiative properties. J. Atmos. Sci.,50, 1305–1322.

  • North, G. R., T. L. Bell, F. F. Cahalan, and F. J. Moeng, 1982: Sampling errors in estimation of empirical orthogonal functions. Mon. Wea. Rev.,110, 699–706.

  • Phillips, T. J., 1994: A summary documentation of the AMIP model. PCMDI Rep. 18, 343 pp. [Available from Program for Climate Model Diagnosis and Intercomparison, L-264, Lawrence Livermore National Laboratory, Livermore, CA 94550.].

  • ——, 1996: Documentation of the AMIP models on the World Wide Web. Bull. Amer. Meteor, Soc.,77, 1191–1196.

  • Potter, G. L., J. M. Slingo, J.-J. Morcrete, and L. Corsetti, 1992: A modeling perspective on cloud radiative forcing. J. Geophys. Res.,97, 20507–20518.

  • Ramanathan, V., R. D. Cess, E. F. Harrison, P. Minnis, B. R. Barkstrom, E. Ahmad, and D. Hartmann, 1989: Cloud-radiative forcing and climate: Results from the Earth Radiation Budget Experiment. Science,243, 57–63.

  • Rossow, W. L., and R. A. Schiffer, 1991: ISCCP cloud data products. Bull. Amer. Meteor. Soc.,72, 2–21.

  • Susskind, J., P. Piraino, L. Rokke, L. Iredell, and A. Mehta, 1997: Characteristics of the TOVS Pathfinder Path A dataset. Bull. Amer. Meteor. Soc.,78, 1449–1472.

  • Weare, B. C., 1993: Multi-year statistics of selected variables from the ISCCP C2 data set. Quart. J. Roy. Meteor. Soc.,119, 795–808.

  • ——, 1994: Interrelationships between cloud properties and sea surface temperatures on seasonal and interannual time scales. J. Climate,7, 248–260.

  • ——, 1995a: Factors controlling ERBE longwave clear-sky and cloud forcing fluxes. J. Climate,8, 1889–1899.

  • ——, 1995b: Evaluation of total cloudiness in AMIP during ENSO. Proc. Int. Conf. on the Tropical Ocean Global Atmosphere (TOGA) Program, Melbourne, Australia, World Meteor. Org., 628–634.

  • ——, 1997: Climatic variability of cloud radiative forcing. Quart. J. Roy. Meteor. Soc.,123, 1055–1073.

  • ——, and AMIP Modeling Groups, 1996: Evaluation of the zonal mean vertical structure of clouds and its variability in the Atmospheric Model Intercomparison Project. J. Climate,9, 3419–3431.

  • ——, I. I. Mokhov, and AMIP Modeling Groups, 1995: Evaluation of total cloudiness and its variability in the atmospheric model intercomparison project. J. Climate,8, 2224–2238.

  • Wielicki, B. A., and J. A. Coakley Jr., 1981: Cloud retieval using infrared sounder data: Error analysis. J. Appl. Meteor.,20, 157–169.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 13 13 4
PDF Downloads 8 8 3

Comparison of NCEP–NCAR Cloud Radiative Forcing Reanalyses with Observations

View More View Less
  • 1 Atmospheric Science Program, Department of Land, Air and Water Resources, University of California, Davis, Davis, California
© Get Permissions
Restricted access

Abstract

Longwave and shortwave cloud radiative forcing from the recently released National Center for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses are compared to Earth Radiation Budget Experiment (ERBE) observations. The observed differences are analyzed utilizing concurrent International Satellite Cloud Climatology Project (ISCCP) estimates of cloudiness and other satellite observations.

The results show that the NCEP–NCAR longwave cloud forcing agrees well with that of ERBE not only for the annual means but also for seasonal and climatic variations. Areas of disagreement are generally related to disagreements between NCEP–NCAR high cloudiness and observations. Overall, the NCEP–NCAR shortwave cloud forcing is in poorer agreement with ERBE observations. NCEP–NCAR annual means in the Tropics are often 20–30 W m−2 too negative. On the other hand the NCEP–NCAR total cloud cover in this region is 10%–20% less than the ISCCP observations, which should lead to less, rather than more, negative shortwave cloud forcing. Thus the primary error in the mean shortwave cloud forcing is likely due to specification of clouds that are too reflective in the NCEP analysis model. Moderate errors in the variability of NCEP–NCAR SWCF are apparently related to errors in the analyzed seasonal variability of total cloudiness, which are exacerbated by NCEP model specification of clouds that are too bright and underestimates of the seasonal variability of the clear-sky fluxes.

Corresponding author address: Prof. Bryan C. Weare, Atmospheric Science Program, Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616.

Email: bcweare@ucdavis.edu

Abstract

Longwave and shortwave cloud radiative forcing from the recently released National Center for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses are compared to Earth Radiation Budget Experiment (ERBE) observations. The observed differences are analyzed utilizing concurrent International Satellite Cloud Climatology Project (ISCCP) estimates of cloudiness and other satellite observations.

The results show that the NCEP–NCAR longwave cloud forcing agrees well with that of ERBE not only for the annual means but also for seasonal and climatic variations. Areas of disagreement are generally related to disagreements between NCEP–NCAR high cloudiness and observations. Overall, the NCEP–NCAR shortwave cloud forcing is in poorer agreement with ERBE observations. NCEP–NCAR annual means in the Tropics are often 20–30 W m−2 too negative. On the other hand the NCEP–NCAR total cloud cover in this region is 10%–20% less than the ISCCP observations, which should lead to less, rather than more, negative shortwave cloud forcing. Thus the primary error in the mean shortwave cloud forcing is likely due to specification of clouds that are too reflective in the NCEP analysis model. Moderate errors in the variability of NCEP–NCAR SWCF are apparently related to errors in the analyzed seasonal variability of total cloudiness, which are exacerbated by NCEP model specification of clouds that are too bright and underestimates of the seasonal variability of the clear-sky fluxes.

Corresponding author address: Prof. Bryan C. Weare, Atmospheric Science Program, Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616.

Email: bcweare@ucdavis.edu

Save