I find that the long-term value of climate sensitivity is, on average, 26% above that inferred during transient warming within global climate models, with a larger discrepancy when climate sensitivity is high.
Numerical experiments show that for lower degree polynomial models and for models with many interactions, low discrepancy designs approximating the arcsine distribution are superior.
In agreement with the largest RMSD and Rg, AMBER-03 predicts a total SASA that is ∼10% larger than NMR models, with most of this discrepancy resulting from the exposure of non-polar groups to solvent during simulation.
This comparison is partly inspired by the work of England and Immel (2012), who reported that the previous HWM07 model shows discrepancies with drift velocities of equatorial and low-latitude plasma depletions observed by the far ultraviolet imager on the IMAGE spacecraft.
However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge.
A comparison with prediction models showed some discrepancies in the low-frequency range.
Finally, comparisons of the observed thresholds with existing models revealed significant discrepancies between the predicted and measured values.
By contrast, for the effects of duration, age at initiation, and time since last exposure, the strongest estimates were provided by the WC models, but the discrepancies with ULR and CLR were weaker than for intensity.
(This is another book with discrepancies.
These ablation results and model-experiment discrepancies, combined with antidromic activation from the XII nucleus and axonal projection patterns, ascribe rhythm-generating and premotor roles to Dbx1 preBötC neurons.
