In the IPCC's defense, their second report in 1995 greatly reduced projections (SAR page 39), and the first report had said, in bold, «There are
many uncertainties in our predictions particularly with regard to the timing, magnitude and regional patterns of climate change, due to our incomplete understanding» (page xii).
«Why there's a lot of
uncertainty in the predictions is that it depends on what the sun's doing, to a large measure.»
Our new -LCB- \ em Spitzer -RCB- observations were taken two years after the original K2 discovery data and have a significantly higher cadence, allowing us to derive improved estimates for this planet's radius, semi-major axis, and orbital period, which greatly reduce
the uncertainty in the prediction of near future transit times for the -LCB- \ em James Webb Space Telescope -RCB--LRB--LCB- \ em JWST -RCB--RRB- observations.
This underlines the importance of being aware of
the uncertainty in the predictions (see below).
By its very nature, a model is a simplification of reality, so the final step when we consider predictions made by numerical models is to assess
the uncertainty in our predictions.
«
Uncertainty in Predictions of the Climate Response to Rising Levels of Greenhouse Gases.»
Secondly, deterministically formulated climate models are incapable of predicting
the uncertainty in their predictions; and yet this is a crucially important prognostic variable for societal applications.
New understanding of the thinner ice regime in the Arctic will help reduce
the uncertainty in predictions of how the ice conditions evolve.
Clarifying the areas of ignorance and knowledge gaps and
uncertainty in predictions is the absolutely first step before «translating» anything.
Dr Jochem Marotzke: «That obligates us to clearly state
the uncertainties in our predictions as well.»
With nonstationary statistics the standard error of the fit over past years is not a good measure of
the uncertainty in the prediction.
Lindsay comments, «with nonstationary statistics, the standard error of the fit over past years is not a good measure of
the uncertainty in the prediction.»
«That obligates us to clearly state
the uncertainties in our predictions as well,» he says.
The curved blue lines in Figure 9 - 1 present the calibration error, or
the uncertainty in predictions based on the calibration (technically the 95 percent prediction interval, which has probability 0.95 of covering the unknown temperature), which is a standard component of a regression analysis.
Secondly, what is
the uncertainty in that prediction given a particular forcing?
* D. A. Stainforth, et al., (2005) «
Uncertainty in predictions of the climate response to rising levels of greenhouse gases» Nature 433, 403 - 406.