Effects of Climate Model Mean-State Bias on Blocking Underestimation

In discussions of extreme weather trends, the subject of atmospheric blocking remains an open question, in part because of the inability of climate models to accurately reproduce blocking frequency patterns for the current climate. A number of factors have been proposed to explain this failure, including specific problems with model physics and inadequate resolution. In this paper, we show that, in the case of the National Center for Atmospheric Research Community Atmosphere Model (NCAR CAM), its underestimation of blocking frequency is caused by its mean state bias and that correcting that bias increases blocking frequency estimates over Europe and decreases the root-mean-square error versus reanalysis from 0.015 to 0.011.

Duke Scholars

Author Ding Ma DKU Faculty