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This is an update to our 2015 Scientific Reports paper: Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise. The paper used a novel statistical estimate of unforced variability that was derived from reconstructed and instrumental surface temperature records. We used our statistical estimate of unforced variability to aid in our interpretation of recently observed temperature variability (more info here).
Our paper used global temperature data through 2013 since that was the most recent year in the major global temperature datasets at the time that the paper was submitted. Below I update Figures 2 and 3 from the paper, incorporating the data from 2014-2016.
Figure 2 updated through 2016.
Figure 3 updated through 2016.
My thoughts on claims made by Dr. Patrick Frank (SLAC) on the validity of climate model projections of global warming:
It is always useful to check past predictions against eventual observations. Below is the NASA GISTEMP observed global temperature (updated through 2016) overlain on top of various projections of CO2-induced warming from calculations published in 1981 (Hansen et al. 1981). 2015 and 2016 are literally off of the chart. This does not imply higher equilibrium climate sensitivity than that represented by the dashed line (5.6C) because these calculations did not include the effects of anthropogenic increases in non-CO2 greenhouse gasses. There are a number of other important caveats to this juxtaposition like Hansen’s model not allowing for unforced/internal variability as well as differences between the assumed and actual growth rate of atmospheric CO2 ect. Nevertheless, it is an interesting comparison.
NASA released their 2016 global mean surface temperature data today. With this datapoint in, observations are now above the average climate model value for this point in time (using 1986-2005 as the baseline):
This graphic uses the RCP 4.5 emissions scenario for the models but the divergence between RCP 4.5 and steeper emissions scenarios is not appreciable until the mid-21st century (see e.g. Figure 1 here).
We have published a new paper titled “Spread in the magnitude of climate model interdecadal global temperature variability traced to disagreements over high-latitude oceans“. Here is a brief summary:
Natural unforced variability in global mean surface air temperature (GMST) is of the same order of magnitude as current externally forced changes in GMST on decadal timescales. Thus, understanding the precise magnitude of unforced GMST variability is relevant for both the attribution of past climate changes to human causes as well to the prediction of climate change on policy-relevant timescales.
Climate models could be useful for estimating the true magnitude of unforced GMST variability provided that they more-or-less converge on the same answer. Unfortunately, current models show substantial disagreement on the magnitude of natural GMST variability, highlighting a key uncertainty in contemporary climate science. This large model spread must be narrowed in the future if we are to have confidence that models can be trusted to give useful insights on natural variability.
Since it is known that unforced GMST variability is heavily influenced by tropical Pacific surface temperatures, it might be tempting to suppose that the large inter-model spread in the simulated magnitude of GMST variability is due to model disagreement in the amount of simulated tropical Pacific variability. Perhaps surprisingly, our study shows that this is not the case and that the spread in the magnitude of model-simulated GMST variability is linked much more strongly to model disagreements over high-latitude oceans. Our findings suggesting that improving the simulation of air-sea interaction in these high-latitude ocean regions could narrow the range of simulated GMST variability, advance our fundamental understanding of natural variability, and appreciably improve our ability to forecast global warming on policy-relevant timescales.
We have recently published a study in Geophysical Research Letters titled “The necessity of cloud feedback for a basin-scale Atlantic Multidecadal Oscillation“.
The Atlantic Multidecadal Oscillation (AMO) – a basin-scale coherent oscillation of sea surface temperatures over the North Atlantic – is thought be one of the climate system’s most important modes of natural variability, affecting everything from drought to hurricane activity to natural fluctuations in global temperature. Traditionally, the basin-scale AMO has been explained as a direct consequence of variability in the Atlantic Ocean’s meridional overturning circulation (AMOC). In contrast, our study identifies atmospheric processes; specifically cloud feedback, as a necessary component for the existence of a basin-scale AMO, thus amending the canonical view of the AMO as a signature directly and solely attributable to oceanic processes.
We have new published research that shows in detail why the earth’s temperature remains stable when it is not pushed by outside forcings. Below is a summary in plain english. For a more technical discussion see here.