climate models

Natural Variability’s Role in Arctic Sea Ice Decline Strengthens Case for Lukewarming

Global Science Report is a feature from the Center for the Study of Science, where we highlight one or two important new items in the scientific literature or the popular media. For broader and more technical perspectives, consult our “Current Wisdom.”

A story this week that has been making the rounds in the climate-media complex finds that natural variability is responsible for perhaps as much as 50% of the summertime decrease in Arctic sea ice that has taken place over the past 30 years or so (anthropogenic climate change is the presumed factor in the remainder).

This isn’t new. The last (2013) science report from the UN’s Intergovernmental panel on climate change said:

Using climate model simulations from the NCAR CCSM4…inferred that approximately half (56%) of the observed rate of decline from 19979 to 2005 was externally (anthropogenically) forced, with the other half associated with natural internal variability.

Ten years ago, a study was conducted by a team led by Julienne Stroeve that looked at the observed rate of Arctic sea ice loss and compared it to climate model expectations. [A side note here: the loss of Arctic sea ice (which is floating ice) does not lead to sea level rise just as the melting of ice in your cocktail doesn’t lead to your glass overflowing]. What Stroeve and colleagues found was the Arctic sea ice was being lost at a far brisker pace than climate models had predicted (Figure 1).

Figure 1. Arctic sea ice extent from observations (red think line) and climate models (colored spaghetti), from Stroeve et al. (2007).

You Ought to Have a Look: Natural Climate Variability

You Ought to Have a Look is a feature from the Center for the Study of Science posted by Patrick J. Michaels and Paul C. (“Chip”) Knappenberger. While this section will feature all of the areas of interest that we are emphasizing, the prominence of the climate issue is driving a tremendous amount of web traffic. Here we post a few of the best in recent days, along with our color commentary.

We’ve got a lot cover this week, so let’s get right to it.

On the science front, we want to highlight two new papers that both suggest that attributing heavy precipitation events in the United States to human-caused climate change is a fool’s errand (not that there aren’t plenty of fools running around out there). This is a timely topic to explore with the big rains in Louisiana over the weekend leading the news coverage.

One paper by a research team from the University of Iowa found that “the stronger storms are not getting stronger” and that there has not been any change in the seasonality of heavy rainfall events by examining trends in the magnitude, frequency, and seasonality of heavy rainfall events in the United States. They did report that the frequency of heavy rain events was increasing across much of the United States, with the exception of the Northwest. As to the reason behind the observed patterns, the authors write “[o]ur findings indicate that the climate variability of both the Atlantic and Pacific Oceans can exert a large control on the precipitation frequency and magnitude over the contiguous USA.”

The other paper, from a research team led by NOAA/GFDL’s Karin van der Wiel, examined climate model projections and observed trends in heavy precipitation events across the United States and concludes:

Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.

Pretty emphatic and straightforward summary.

So, the next time you read that such and such extreme precipitation event was made worse by global warming, you’ll know that there is precious little actual science to back that up.

You Ought to Have a Look: 2015 Temperatures, Climate Sensitivity, and the Warming Hiatus

You Ought to Have a Look is a feature from the Center for the Study of Science posted by Patrick J. Michaels and Paul C. (“Chip”) Knappenberger.  While this section will feature all of the areas of interest that we are emphasizing, the prominence of the climate issue is driving a tremendous amount of web traffic.  Here we post a few of the best in recent days, along with our color commentary.

What’s lost in a lot of the discussion about human-caused climate change is not that the sum of human activities is leading to some warming of the earth’s temperature, but that the observed rate of warming (both at the earth’s surface and throughout the lower atmosphere) is considerably less than has been anticipated by the collection of climate models upon whose projections climate alarm (i.e., justification for strict restrictions on the use of fossil fuels) is built.

We highlight in this issue of You Ought to Have a Look a couple of articles that address this issue that we think are worth checking out.

First is this post from Steve McIntyre over at Climate Audit that we managed to dig out from among all the “record temperatures of 2015” stories. In his analysis, McIntyre places the 2015 global temperature anomaly not in real world context, but in the context of the world of climate models.

Climate model-world is important because it is in that realm where climate change catastrophes play out, and that influences the actions of real-world people to try to keep them contained in model-world.

So how did the observed 2015 temperatures compare to model world expectations? Not so well.

Current Wisdom: A Closer Look at Climate Model Performance

The Current Wisdom is a series of monthly articles in which Patrick J. Michaels and Paul C. “Chip” Knappenberger, from Cato’s Center for the Study of Science, review interesting items on global warming in the scientific literature or of a more technical nature. These items may not have received the media attention that they deserved or have been misinterpreted in the popular press.

Posted Wednesday in the Washington Post’s new online “Energy and Environment” section is a piece titled “No, Climate Models Aren’t Exaggerating Global Warming.” That’s a pretty “out there” headline considering all the evidence to the contrary.

We summed up much of the contrary evidence in a presentation at the annual meeting of the American Geophysical Union last December.  The take-home message—that climate models were on the verge of failure (basically the opposite of the Post headline)—is self-evident in Figure 1, adapted from our presentation.

Figure 1. Comparison of observed trends (colored circles according to legend) with the climate model trends (black circles) for periods from 10 to 64 years in length. All trends end with data from the year 2014 (adapted from Michaels and Knappenberger, 2014).

The figure shows (with colored circles) the value of the trend in observed global average surface temperatures in lengths ranging from 10 to 64 years and in all cases ending in 2014 (the so-called “warmest year on record”). Also included in the figure (black circles) is the average trend in surface temperatures produced by a collection of climate models for the same intervals. For example, for the period 1951–2014 (the leftmost points in the chart, representing a trend length of 64 years) the trend in the observations is 0.11°C per decade and the average model projected trend is 0.15°C per decade. During the most recent 10-year period (2005–2014, rightmost points in the chart), the observed trend is 0.01°C per decade while the model trend is 0.21°C per decade.

AGU 2014: Quantifying the Mismatch between Climate Projections and Observations

Global Science Report is a feature from the Center for the Study of Science, where we highlight one or two important new items in the scientific literature or the popular media. For broader and more technical perspectives, consult our monthly “Current Wisdom.”

Pat Michaels is in San Francisco this week attending the annual meeting of the American Geophysical Union (AGU) and presenting a poster detailing the widening mismatch between observations of the earth’s temperature and climate model projections of its behavior. Since most global warming concern (including that behind regulatory action) stems from the projections of climate models as to how the earth’s temperature will evolve as we emit greenhouse gases into the atmosphere (as a result of burning fossil fuels to produce energy), it is important to keep a tab on how the model projections are faring when compared with reality. That they are faring not very well should be more widely known—Pat will spread the word while there.

We don’t want those of you who are unable to attend the conference to think you are missing out on anything, so we have reformatted our poster presentation to fit this blog format (it is available in its original format here).

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Quantifying the Lack of Consistency between Climate Model Projections and Observations of the Evolution of the Earth’s Average Surface Temperature since the Mid-20th Century

Patrick J. Michaels, Center for the Study of Science, Cato Institute, Washington DC

Paul C. Knappenberger, Center for the Study of Science, Cato Institute, Washington DC

INTRODUCTION

Recent climate change literature has been dominated by studies which show that the equilibrium climate sensitivity is better constrained than the latest estimates from the Intergovernmental Panel on Climate Change (IPCC) and the U.S. National Climate Assessment (NCA) and that the best estimate of the climate sensitivity is considerably lower than the climate model ensemble average. From the recent literature, the central estimate of the equilibrium climate sensitivity is ~2°C, while the climate model average is ~3.2°C, or an equilibrium climate sensitivity that is some 40% lower than the model average.

To the extent that the recent literature produces a more accurate estimate of the equilibrium climate sensitivity than does the climate model average, it means that the projections of future climate change given by both the IPCC and NCA are, by default, some 40% too large (too rapid) and the associated (and described) impacts are gross overestimates.

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