• A full resolution of this issue will require reducing
the large observational uncertainties that currently exist.
For Antarctica,
large observational uncertainties result in low confidence that anthropogenic forcings have contributed to the observed warming averaged over available stations.
In general, comparing warming from models and obs since the mid-1800s isn't ideal, since there is
large observational uncertainty prior to 1900.
Not exact matches
You have to remember that the 5 year forecast is derived from a
large number of individual runs each with slightly different starting conditions matching the range of the
observational uncertainty in the real starting conditions.
The very high significance levels of model — observation discrepancies in LT and MT trends that were obtained in some studies (e.g., Douglass et al., 2008; McKitrick et al., 2010) thus arose to a substantial degree from using the standard error of the model ensemble mean as a measure of
uncertainty, instead of the ensemble standard deviation or some other appropriate measure for
uncertainty arising from internal climate variability... Nevertheless, almost all model ensemble members show a warming trend in both LT and MT
larger than
observational estimates (McKitrick et al., 2010; Po - Chedley and Fu, 2012; Santer et al., 2013).
They are perhaps the
largest uncertainty in our understanding of climate change, owing to disagreement among climate models and
observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming2, 3.
When the bottom - up approach is used to extrapolate the emissions to
larger scales,
uncertainty results from the inherent
large temporal and spatial variations of fluxes and the limited range of
observational conditions.
[7] Brient & Schneider's method thus down - weights a model whose estimate has a
larger or smaller
uncertainty than the
observational estimate even if the model's and the
observational mean estimates are identical.