There is a new paper that sheds more light on major problems with the scientific accuracy of the multi-decadal global climate model predictions (h/t to John Christy]. The paper is
Stephens, G. L., T. L’Ecuyer, R. Forbes, A. Gettlemen, J.‐C. Golaz, A. Bodas‐Salcedo, K. Suzuki, P. Gabriel, and J. Haynes (2010), Dreary state of precipitation in global models, J. Geophys. Res., 115, D24211, doi:10.1029/2010JD014532.
The abstract reads [highlight added]
“New, definitive measures of precipitation frequency provided by CloudSat are used to assess the realism of global model precipitation. The character of liquid precipitation (defined as a combination of accumulation, frequency, and intensity) over the global oceans is significantly different from the character of liquid precipitation produced by global weather and climate models. Five different models are used in this comparison representing state‐of‐the‐art weather prediction models, state‐of‐the‐art climate models, and the emerging high‐resolution global cloud “resolving” models. The differences between observed and modeled precipitation are larger than can be explained by observational retrieval errors or by the inherent sampling differences between observations and models. We show that the time integrated accumulations of precipitation produced by models closely match observations when globally composited. However, these models produce precipitation approximately twice as often as that observed and make rainfall far too lightly. This finding reinforces similar findings from other studies based on surface accumulated rainfall measurements. The implications of this dreary state of model depiction of the real world are discussed.”
The conclusion includes
“The differences in the character of model precipitation are systemic and have a number of important implications for modeling the coupled Earth system as discussed above. It is also well known that the ability of a numerical model for resolving wave‐like fields that vary continuously in time and space is several times the grid resolution [e.g., Williamson, 2008]. Our results suggest this is also true of intermittent fields like precipitation. Since the tendency is for increased frequency of precipitation as the averaging scale of observations increases (e.g., Figures 3 and 5), the much higher frequency of occurrences of model grid point precipitation implies that this precipitation is more representative of a scale that is many times the model grid resolution. Roberts and Lean , for example, demonstrated that an acceptable measure of skill in precipitation forecasts from high resolution models of 1 and 12 km resolution occurs at scales of 45–60 and 50–80 km, respectively. This suggests that the real resolution of model precipitation is several times that of the model grid resolution. This implies little skill in precipitation calculated at individual grid points, and thus applications involving downscaling of grid point precipitation to yet even finer‐scale resolution has little foundation and relevance to the real Earth system.”