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Introduction Limitations of cloud data for evaluating climate models

Using Reanalyses in combination with Earth Radiation Budget data to evaluate climate model simulated cloud radiative properties Richard P. Allan, Tony Slingo, Mark A. Ringer Hadley Centre for Climate Prediction and Research. Introduction Limitations of cloud data for evaluating climate models

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Introduction Limitations of cloud data for evaluating climate models

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  1. Using Reanalyses in combination with Earth Radiation Budget data to evaluate climate model simulated cloud radiative propertiesRichard P. Allan, Tony Slingo, Mark A. RingerHadley Centre for Climate Prediction and Research • Introduction • Limitations of cloud data for evaluating climate models • Use well-calibrated, stable monthly mean radiation budget data • Use method of Cess et al. (2001) • N=-SWCF/LWCF • Evaluation of climate model cloud properties

  2. From Cess et al. (2001), J. Clim, 14, p.2129

  3. Limitations • Convergence of points at Net CF=0, -SWCF/LWCF=1.0 • Plot N verses -SWCF? • Cloud altitude, and therefore N, strongly dependent on dynamical regime • sample by dynamic regime? • use reanalyses • CF dependent on cloud amount although N is not (to 1st order) • scale by total cloud fraction?

  4. N verses -SWCF (Allan et al., 2002)

  5. MODEL EVALUATION • Changes in N-SWCF distribution dependent on change in dynamic regime • Large scale anomalous N in 1998 (and 1994) relate to large-scale changes in tropical radiation budget (Wielicki et al. 2001) • Cess cloud ratio technique useful. But need to • sample by dynamic regime • Account for Cloud Forcing dependence on changes in cloud amount Currently using technique to assess simulation of tropical radiation budget in latest climate model version, HadGEM and ERA-40. Apply scaling factor to Cloud Forcing: assuming to first order linear in cloud amount...

  6. Evaluation vesions of climate model and ERA40. N verses -SWCF: (a) ERBS/ERA40, (b) HadAM3, (c) HadAM4, (d) New Dynamics, (e) ERBS/NCEP, (f) ERA40. Unscaled by cloud amount.

  7. ...SCALED by cloud amount.

  8. Conclusions • Anomalous cloud forcing ratio in tropical west Pacific during 1998 • (1) change in dynamic regime • (2) large-scale tropical changes (Wielicki et al. 2001) • Model can simulate (1) but not (2) • Cloud forcing ratio useful if • sample by dynamic regime • scale by cloud amount

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