A new paper posted today on ScienceXpress (from Science magazine), by Thomas Karl, Director of NOAA’s Climate Data Center, and several co-authors[1], that seeks to disprove the “hiatus” in global warming prompts many serious scientific questions.

The main claim[2] by the authors that they have uncovered a significant recent warming trend is dubious. The significance level they report on their findings (.10) is hardly normative, and the use of it should prompt members of the scientific community to question the reasoning behind the use of such a lax standard.

In addition, the authors’ treatment of buoy sea-surface temperature (SST) data was guaranteed to create a warming trend. The data were adjusted upward by 0.12°C to make them “homogeneous” with the longer-running temperature records taken from engine intake channels in marine vessels. 

As has been acknowledged by numerous scientists, the engine intake data are clearly contaminated by heat conduction from the engine itself, and as such, never intended for scientific use. On the other hand, environmental monitoring is the specific purpose of the buoys. Adjusting good data upward to match bad data seems questionable, and the fact that the buoy network becomes increasingly dense in the last two decades means that this adjustment must put a warming trend in the data.

The extension of high-latitude arctic land data over the Arctic Ocean is also questionable. Much of the Arctic Ocean is ice-covered even in high summer, meaning the surface temperature must remain near freezing. Extending land data out into the ocean will obviously induce substantially exaggerated temperatures.

Additionally, there exist multiple measures of bulk lower atmosphere temperature independent from surface measurements which indicate the existence of a “hiatus”[3]. If the Karl et al., result were in fact robust, it could only mean that the disparity between surface and mid-tropospheric temperatures is even larger that previously noted. 

Getting the vertical distribution of temperature wrong invalidates virtually every forecast of sensible weather made by a climate model, as much of that weather (including rainfall) is determined in large part by the vertical structure of the atmosphere.

Instead, it would seem more logical to seriously question the Karl et al. result in light of the fact that, compared to those bulk temperatures, it is an outlier, showing a recent warming trend that is not in line with these other global records.

And finally, even presuming all the adjustments applied by the authors ultimately prove to be accurate, the temperature trend reported during the “hiatus” period (1998–2014), remains significantly below (using Karl et al.’s measure of significance) the mean trend projected by the collection of climate models used in the most recent report from the United Nation’s Intergovernmental Panel on Climate Change (IPCC). 

It is important to recognize that the central issue of human-caused climate change is not a question of whether it is warming or not, but rather a question of how much. And to this relevant question, the answer has been, and remains, that the warming is taking place at a much slower rate than is being projected.

The distribution of trends of the projected global average surface temperature for the period 1998–2014 from 108 climate model runs used in the latest report of the U.N.’s Intergovernmental Panel on Climate Change (IPCC)(blue bars). The models were run with historical climate forcings through 2005 and extended to 2014 with the RCP4.5 emissions scenario. The surface temperature trend over the same period, as reported by Karl et al. (2015, is included in red. It falls at the 2.4^th percentile of the model distribution and indicates a value that is (statistically) significantly below the model mean projection.

div[2] “It is also noteworthy that the new global trends are statistically significant and positive at the 0.10 significance level for 1998–2012…”
div[3] Both the UAH and RSS satellite records are now in their 21^st year without a significant trend, for example