Hall and Qu (2006) show that biases of a number of MMD models in reproducing the observed seasonal cycle of land snow cover (especially the spring melt) are tightly related to the large variations in snow
albedo feedback strength simulated by the same models in climate change scenarios.
Not exact matches
«By comparing the response of clouds and water vapor to ENSO forcing in nature with that in AMIP simulations by some leading climate models, an earlier evaluation of tropical cloud and water vapor
feedbacks has revealed two common biases in the models: (1) an underestimate of the
strength of the negative cloud
albedo feedback and (2) an overestimate of the positive
feedback from the greenhouse effect of water vapor.
Figure 9.43 (a)
Strengths of individual
feedbacks for CMIP3 and CMIP5 models (left and right columns of symbols) for Planck (P), water vapour (WV), clouds (C),
albedo (A), lapse rate (LR), combination of water vapour and lapse rate (WV+LR) and sum of all
feedbacks except Planck (ALL), from Soden and Held (2006) and Vial et al. (2013), following Soden et al. (2008).
The fundamental issue is the ratio of the various radiative
feedbacks (
albedo + water vapor + clouds, etc) to the
strength of the Planck radiative restoring response.
This shows the
strength of the ice -
albedo and carbon cycle
feedbacks over tens of thousands of years...»