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The features of cloud overlapping in Eastern Asia and their effect on cloud radiative forcing

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Abstract

Characteristics of cloud overlap over Eastern Asia are analyzed using a three-year dataset (2007–2009) from the cloud observing satellite CloudSat. Decorrelation depth L* cf is retrieved, which represents cloud overlap characteristics in the simulation of cloud-radiation processes in global climate models. Results show that values of L* cf in six study regions are generally within the range 0–3 km. By categorizing L* cf according to cloud amount in subregions, peak L* cf appears near subregions with cloud amount between 0.6 and 0.8. Average L* cf is 2.5 km. L* cf at higher altitudes is generally larger than at lower latitudes. Seasonal variations of L* cf are also clearly demonstrated. The sensitivity of cloud radiative forcing (CRF) to L* cf in Community Atmosphere Model 3.0 of the National Center for Atmospheric Research (CAM3/NCAR) is analyzed. The result shows that L* cf can have a big impact on simulation of CRF, especially in major monsoon regions and the Mid-Eastern Pacific, where the difference in CRF can reach 40–50 W m−2. Therefore, accurate parameterization of cloud vertical overlap structure is important to CRF simulation and its feedback to climate.

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References

  1. Ramanathan V, Cess R D, Harrison E F, et al. Cloud-radiative forcing and climate: Results from the earth radiation budget experiment. Science, 1989, 243:57–63

    Article  Google Scholar 

  2. Wang H Q, Zhao G X. Cloud and radiation. Sci Atmos Sin, 1994, 18 (Suppl):910–932

    Google Scholar 

  3. Ding S G, Zhao C S, Shi G Y, et al. Analysis of global total cloud amount variation over the past 20 years. J Appl Meteorol, 2005, 16:670–676

    Google Scholar 

  4. Sun B, Groisman P Y. Cloudiness variations over the former Soviet Union. Int J Climatol, 2000, 20:1097–1111

    Article  Google Scholar 

  5. Houghton J T, Ding Y, Griggs D J, et al. Climate Change: The Scientific Basis. New York: Cambridge University Press, 2001. 1–421

    Google Scholar 

  6. Wetherald R T, Manabe S. Cloud feedback processes in a general circulation model. J Atmos Sci, 1988, 45:1397–1415

    Article  Google Scholar 

  7. Houghton J T, Ding Y, Griggs D J, et al. Climate Change: The Scientific Basis. Cambridge: Cambridge University Press, 2001. 148–149

    Google Scholar 

  8. Zhang H, Jing X W. Effect of cloud overlap assumptions in climate models on modeled earth-atmosphere radiative fields (in Chinese). Chin J Atmos Sci, 2010, 34:520–532

    Google Scholar 

  9. Jing X W, Zhang H, Guo P W. A study of the effect of sub-grid cloud structure on global radiation in climate models (in Chinese). Acta Meteorol Sin, 2010, 67:1058–1068

    Google Scholar 

  10. Manabe S, Strickler R F. Thermal equilibrium of the atmosphere with a convective adjustment. J Atmos Sci, 1964, 21:361–385

    Article  Google Scholar 

  11. Geleyn J F, Hollingsworth A. An economical analytical method for the computation of the interaction between scattering and line absorption of radiation. Cont Atmos Phys, 1979, 52:1–16

    Google Scholar 

  12. Morcrette J J, Fouquart Y. The overlapping of cloud layers in shortwave radiation parameterizations. J Atmos Sci, 1986, 43:321–328

    Article  Google Scholar 

  13. Barker H W, Stephens G L, Partain P T, et al. Assessing 1D atmospheric solar radiative transfer models: Interpretation and handling of unresolved clouds. J Clim, 2003, 16:2676–2699

    Article  Google Scholar 

  14. Morcrette J J, Jakob C. The response of the ECMWF model to changes in cloud overlap assumption. Mon Weather Rev, 2000, 128:1707–1732

    Article  Google Scholar 

  15. Tian L, Curry J A. Cloud overlap statistics. J Geophys Res, 1989, 94:9925–9935

    Article  Google Scholar 

  16. Barker H W, Stephens G L, Fu Q. The sensitivity of domain-averaged solar fluxes to assumptions about cloud geometry. Q J R Meteorol Soc, 1999, 125:2127–2152

    Article  Google Scholar 

  17. Li J. Accounting for unresolved clouds in a 1D infrared radiative transfer model. Part I: Solution for radiative transfer, cloud scattering, and overlap. J Atmos Sci, 2002, 59:3302–3320

    Article  Google Scholar 

  18. Liang X Z, Wang W C. Cloud overlap effects on general circulation model climate simulations. J Geophys Res, 1997, 102:11039–11047

    Article  Google Scholar 

  19. Hogan R J, Illingworth A J. Deriving cloud overlap statistics from radar. Quart J Roy Meteor Soc, 2000, 128:2903–2909

    Article  Google Scholar 

  20. Barker H W. Overlap of fractional cloud for radiation calculations in GCMs: A global analysis using CloudSat and CALIPSO data. J Geophys Res, 2008, 113:D00A01

    Article  Google Scholar 

  21. Räisänen P, Barker H W, Khairoutdinov M, et al. Stochastic generation of subgrid-scale cloudy columns for large-scale models. Q J R Meteorol Soc, 2004, 130:2047–2068

    Article  Google Scholar 

  22. Barker H W, Räisänen P. Radiative sensitivities for cloud structural properties that are unresolved by conventional GCMs. Q J R Meteorol Soc, 2005, 131:3103–3122

    Article  Google Scholar 

  23. Räisänen P, Barker H W, Cole J N S. The Monte Carlo Independent Column Approximation’s conditional random noise: Impact on simulated climate. J Clim, 2005, 18:4715–4730

    Article  Google Scholar 

  24. Pincus R H, Klein S A. Using stochastically generated subcolumns to represent cloud structure in a large scale model. Mon Weather Rev, 2006, 134:3644–3656

    Article  Google Scholar 

  25. Räisänen P, Järvenoja S, Järvinen H, et al. Tests of Monte Carlo independent column approximation in the ECHAM5 atmospheric GCM. J Clim, 2007, 20:4995–5011

    Article  Google Scholar 

  26. Morcrette J J, Barker H W, Cole J N S, et al. Impact of a new radiation package, McRad, in the ECMWF Integrated Forecasting System. Mon Weather Rev, 2008, 136:4773–4798

    Article  Google Scholar 

  27. Shi G Y. Atmospheric Radiation (in Chinese). Beijing: Science Press, 2007. 302–318

    Google Scholar 

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Authors and Affiliations

  1. Laboratory for Climate Studies of CMA, National Climate Center, Beijing, 100081, China

    Hua Zhang, Jie Peng & XianWen Jing

  2. Chinese Academy of Meteorological Sciences, Beijing, 100081, China

    XianWen Jing

  3. Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Jie Peng

  4. Canadian Center for Climate Modeling and Analysis, University of Victoria, Victoria, BC, V8W 3V6, Canada

    JiangNan Li

Authors
  1. Hua Zhang
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  2. Jie Peng
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  3. XianWen Jing
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  4. JiangNan Li
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Correspondence to Hua Zhang.

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Zhang, H., Peng, J., Jing, X. et al. The features of cloud overlapping in Eastern Asia and their effect on cloud radiative forcing. Sci. China Earth Sci. 56, 737–747 (2013). https://doi.org/10.1007/s11430-012-4489-x

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  • DOI: https://doi.org/10.1007/s11430-012-4489-x

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