Explaining climate change science & rebutting global warming misinformation
Scientific skepticism is healthy. Scientists should always challenge themselves to improve their understanding. Yet this isn't what happens with climate change denial. Skeptics vigorously criticise any evidence that supports man-made global warming and yet embrace any argument, op-ed, blog or study that refutes global warming. This website gets skeptical about global warming skepticism. Do their arguments have any scientific basis? What does the peer reviewed scientific literature say?
In their reply to our criticisms, Prof Fritz Vahrenholt and Dr Sebastian Lüning exhibit a misunderstanding of various key aspects of climate science. Their claim, that mainstream science is radically wrong, is unfounded and not backed up by sufficiently strong evidence. In our response, also published at EER, we only focused on a few selected issues of contention. Here we reply to all of Vahrenholt’s and Lüning’s arguments and allegations.
A long reference list in their book is by itself not persuasive for their argument. In their reply they already show a tendency to misinterpret published research (e.g. Solanki 2004; Mann 2008; Berger 2011).
They present their view as some kind of superior alternative to the IPCC. That is a very strong claim. The least they should do is to submit such a claim to scientific scrutiny, rather than hiding behind a long -partly misunderstood and partly cherrypicked- reference list.
Vahrenholt and Lüning are correct in pointing out that the climate has a delayed response to changes in its radiation budget (whether from the sun, from CO2 or from other causes) due to the ocean’s heat capacity. This may cause the planet to continue to warm after the radiative forcing has stabilized, but the rate of warming will decrease and level off as the climate equilibrates to the new situation.
However, the observations show that both surface temperatures as well as ocean heat content started to increase (during the 1970s and 80s) long after solar activity had reached its plateau (during the 1950s). This is inconsistent with a lagged response to the sun, as suggested by Vahrenholt and Lüning. The relatively steady rate of warming of both ocean and atmosphere over the past four decades indicates that this must be caused by another process. The sun cannot be responsible for the warming of the past four decades, irrespective of how strongly one wishes to amplify its effect.
So begins Simply Wrong: Jan-Erik Solheim on Hansen 1988, by SkS's most prolific myth-buster, Dana. As to be expected, this article has generated the most comments of the articles posted this past week.
Before and after: Current and projected temperature extremes in the L.A. area.
A groundbreaking new study led by UCLA climate expert Alex Hall shows that climate change will cause temperatures in the Los Angeles region to rise by an average of 4 to 5 degrees Fahrenheit by the middle of this century, tripling the number of extremely hot days in the downtown area and quadrupling the number in the valleys and at high elevations.
James Powell's iBook Going to Extremes is an informative read about the recent weather extremes around the globe, with an emphasis on the U.S. which experienced 14 billion-dollar weather disasters in 2011, the most in history. My short review will mostly be about the advantages of this - relatively - new type of book and not so much about the content which will be very familiar to regular readers of Skeptical Science.
The iBook-format is ideal for a topic like weather extremes and their relationship with climate change as it makes it easy to include not just pictures but also videos and interactive graphics. You'll come across videos from floodings as well as footage captured by satellite of events like the inundation of Cairo Beach:
These multi-media additions make reading this as an iBook a lot more interesting than reading it the "traditional way" as a printed book. I was especially impressed by several "before-and-after" satellite images depicting towns like Joplin before and after the tornado hit on May 22, 2011.
Scientists do not blindly trust their own models of global warming. In fact, nobody is more aware of a model’s specific weaknesses than the developers themselves. Most of our time is spent comparing model output to observations, searching for discrepancies, and hunting down bugs.
If 1.5 C global warming above preindustrial temperatures really does represent the threshold for “dangerous climate change” (rather than 2 C, as some have argued), then we’re in trouble. Stabilizing global temperatures at this level isn’t just climatically difficult, it’s also mathematically difficult. Given current global temperatures, and their current rate of change, it’s nearly impossible to smoothly extend the curve to stabilize at 1.5 C without overshooting.
Sometimes computers do weird things. Some bugs appear for the most illogical reasons (last week, the act of declaring a variable altered every single metric of the model output). Other bugs show up once, then disappear before you can track down the source, and you’re never able to reproduce them. It’s not uncommon to fix a problem without ever understanding why the problem occurred in the first place.
John Christy, climate scientist at the University of Alabama at Huntsviile (UAH) was recently interviewed for an article in al.com (Alabama local news). The premise of the article was reasonable, focusing on the fact that the hot month of May 2012 is by itself not evidence of global warming. However, hot weather will of course become more commonplace as the planet warms and global warming "loads the dice"; a fact which Christy and the article neglected to mention.
As has become an unfortunate habit of his, Christy also made a number of misleading claims in the interview. The primary assertion which became the main focus of the article was similar to some other recent claims from climate contrarians - an exaggeration of the discrepancy between global climate models and observational measurements.
Models vs. Data
Specifically regarding the model-data discrepancy, Christy claimed:
Over the past decade, engineers and scientists have studied questions about the effectiveness of wind farms. They found that turbines produce much more energy than they take to build and that even though wind needs backup power stations for when it's calm, they still make big carbon savings.
When calculating these carbon savings the researchers found they had to include some surprising factors like the accuracy of weather forecasts and how efficiently gas power stations turn on and off. Wind isn't zero carbon, but it's very low carbon.
Turbines produce about 20 times the energy used to build them, and are low CO2
A wind farm 'life cycle assessor' adds up the energy needed to mine, refine, process and transport the materials in a turbine and adds the energy used to maintain and decommission a wind farm at the end of its life. Then they compare this with the energy produced.
A 2010 University of Vermont study brought together data for 119 wind farms and found that, on average, they produce almost 20 times the energy used to build them; twice as good as coal (Kubiszewski et al, 2010).
For the 69 that also reported carbon emissions, the average was 25 grams of CO2 for each unit of electricity generated; 98% savings versus an average coal power station. This fits with figures reported by others like Weisser, 2007 and Tremeac and Meunier, 2009.
If you want to mislead people into thinking that there is nothing weird going on in the Arctic, you have to do it during winter. In winter things almost look normal on some graphs, with gaps between trend lines and long-term averages not as ridiculously big as during spring and summer. If you're lucky anomalous weather patterns can make those trend lines come real close to the long-term average, and you'll have a couple of weeks of shouting 'recovery', ridiculing scientists and suggesting graphs are being cooked. It's an annual ritual on pseudo-skeptic blogs, which is only logical. The Arctic is becoming ever more problematic for their life work, ie denying AGW could ever be a problem and thus delaying any meaningful action on mitigating the consequences of AGW. Thank God water still freezes in winter.
Sea ice extent maximum on the left and how it looks now on the right (source: NSIDC)
This week we have temperature studies from Saudi-Arabia, European Alps, and the whole globe. Clouds disturb satellite measurements. Tree rings measure wind too. Some future related issues are methane under glaciers, snow albedo feedback, and AMOC slowdown. Lightning flashes take weekends off. What are the causes for El Niño intensification and for UV radiation increase?
Solheim claims that "Hansen’s model overestimates the temperature by 1.9°C, which is a whopping 150% wrong." Yet Scenario A - the emissions scenario with the largest projected temperature change - only projects 0.7°C surface warming between 1988 and 2012. Even if emissions were higher than in Scenario A (which they weren't, but Solheim wrongly claims they were), they would have to be several times higher for Hansen's model to project the ~2.3°C warming over just 23 years (1°C per decade!) that Solheim claims. Solheim's claim here is simply very wrong.
CO2 is Not the Only Greenhouse Gas
Quite similar to Patrick Michaels' misrepresentation of Hansen's study back in 1998, Solheim claims that Hansen's Scenario A has been closest to reality by focusing exclusively on CO2 emissions. However, the main difference between the various Hansen emissions scenarios is not due to CO2, it's due to other greenhouse gases (GHGs) like chlorofluorocarbons (CFCs) and methane (CH4), whose emissions have actually been below Scenario C (Figure 1). In fact, more than half of the Scenario A radiative forcing comes from non-CO2 GHGs.
Figure 1: Radiative forcing contributions from 1988 to 2010 from CO2 (dark blue), N2O (red), CH4 (green), CFC-11 (purple), and CFC-12 (light blue) in each of the scenarios modeled in Hansen et al. 1988, vs. observations (NOAA). Solheim claims the actual changes were larger than Scenario A (indicated by the blue arrow). In reality they were smaller than Scenario B.
This is a reprint of a news release posted by the National Science Foundation (NSF) on May 21, 2012.
Researchers find that the global carbon pool in seagrass beds is as much as 19.9 billion metric tons
Dense seagrass meadows are a hallmark of the Florida Coastal Everglades LTER site.
Credit: Florida Coastal Everglades LTER Site
Seagrasses are a vital part of the solution to climate change and, per unit area, seagrass meadows can store up to twice as much carbon as the world's temperate and tropical forests.
So report researchers publishing a paper this week in the journal Nature Geoscience.
A brilliant and beautifully put together video from Science Year 2012, an initiative of the German Federal Ministry of Education and Research. Check it out:
Note: Jan-Erik Solheim has just recently made some very incorrect claims about Hansen 1988, which we will debunk later this week. Consider this post a brief primer.
Earlier this year in a post Patrick Michaels Continues to Distort Hansen 1988, Part 1, we compared Patrick Michaels' claims about Hansen et al. (1988) in his 1998 testimony before US Congress to reality. As Figure 1 shows, we found that Michaels had distorted reality, telling Congress that Hansen's Scenario A was closest to reality, when in fact the actual 1988 to 1998 radiative forcing changes weren't even quite as large as in Scenario C.
Figure 1: Radiative forcing contributions from 1988 to 1998 from CO2 (dark blue), N2O (red), CH4 (green), CFC-11 (purple), and CFC-12 (light blue) in each of the scenarios modeled in Hansen et al. 1988, vs. observations (NOAA).
Michaels had claimed Scenario A was accurate because at one point Hansen described it as "business as usual" (BAU). However, between 1988 and 1998 some major events occurred, such as passage of the Montreal Protocol international agreement to reduce chlorofluorocarbon (CFC) emissions, and the collapse of the Soviet Union. Thus, while it is debatable whether Scenario A truly represents a BAU scenario (we argued that it would be more accurate to describe Scenario B as BAU - see Figure 2 below), we did not follow a BAU path over this timeframe anyway. But more importantly, in terms of the greenhouse gas (GHG) radiative forcing (which is what Hansen's model responded to), Scenario C was the closest to reality as of 1998.
A conservative specialist in environmental law—Professor Jonathan Adler of Case Western Reserve University—lays out a thoughtful conservative approach to tackling climate change in a recent post at The Atlantic magazine.
Climate hawk David Roberts (Grist) accurately describes Adler’s piece as “an eloquent, principled case for the simple notion that ‘embrace of limited government principles need not entail the denial of environmental claims.’”
Adler suggests four policy changes to “make it cheaper and easier to adopt low-carbon technologies:” 1) prizes to spark innovation, 2) lower legal barriers to deployment, 3) a revenue-neutral carbon tax, and 4) adaptation.
It is not news that people are polarized over their assessment of the risks posed by climate change. But is it true that the most polarized people are those who are more scientifically literate? Counter-intuitive though it may seem, the answer is: Yes, it is. This is the result of a recent article by Dan Kahan and six colleagues in Nature Climate Change (henceforth, the Kahan Study). This study has received a lot of attention, with blog articles, for example in The Economist, Mother Jones and by David Roberts at Grist.
At Skeptical Science, our goal is to debunk false arguments and explain the science behind climate change. In the light of this peer-reviewed research, we have to ask ourselves: if we are striving to increase scientific literacy, won’t we just be making the polarization that exists around climate change worse? We will come back to that question at the end of this piece, but first, we’ll look in some detail at the Kahan Study itself.
Testing two hypotheses
Kahan et al identified two contrasting hypotheses that seek to explain the polarization in the public’s appreciation of the risks posed by climate change. (Note that the Kahan Study did not look at the public’s perception of the truth or reliability of climate science but, rather, the public’s assessment of the risks that climate change poses.) These hypotheses are:
Scientists working on climate on a daily basis must have been rather astonished by the interview with Professor Fritz Vahrenholt (European Energy Review, May 2, free registration required). Vahrenholt, chief of RWE Innogy, self-proclaimed climate expert and author of the book Die Kalte Sonne (The Cold Sun), claims that “the contribution of CO2 to global warming is being exaggerated”. These claims, however, do not stand up to scientific scrutiny. We assess his ideas in the light of the scientific literature on the role of the sun versus other climate forcing factors. The dominant influence of greenhouse gases follows not only from their basic physical properties, but also from their “fingerprint” in the observed warming. The sun, in contrast, has not exhibited any warming trend over the past 50 years. The sun is thus not responsible for the warming seen during this period. Greenhouse gases in all likelihood are.
First of all, we welcome the active participation of the business community in the discussion on climate change. Global warming and its effects may have consequences which business, e.g. the energy sector, should anticipate and adapt to. Furthermore, mitigation policies may affect the competitive advantages and business prospects of a variety of energy options. Investment portfolios should take that into account. That is not an easy task. The business consultant or director developing a climate change response strategy may be overwhelmed by the vast amount of –sometimes conflicting- scientific information available. Luckily, every couple of years an integrated assessment is made by the IPCC, the Intergovernmental Panel on Climate Change, primarily aimed at governments, but also quite valuable for the business community.
In my previous three articles on HadSST3, CRUTEM4 and HadCRUT4, I have given an overview of the literature and data concerning the new datasets which comprise the Hadley/CRU version of the instrumental temperature record. The analysis I have presented so far has been addressed at communicating the work done by Hadley and CRU as clearly as possible.
However in the course of examining the data for these articles I have come across a number of features which are of interest in understanding the data and do not seem to have been widely reported. Some of these features are (at least to me) rather unexpected. Note however that this material is the result of a few months of spare-time effort, and has not been subject to the scrutiny of peer-review, and so should be treated as tentative. It is likely that at least some of it is wrong. Constructive criticism and pointers to any previous similar work I have missed are welcome.
The material is quite dense. Much of it concerns the problem of coverage bias, so reviewing my previous articles ‘HadCRUT3, Cool or Uncool?’ and ‘GISTEMP, Cool or Uncool?’ on this subject may be helpful. I will start by presenting an outline of my conclusions and then explain in detail how I reached them.
One important thing in science is method development. Science works at the edge between known and unknown, and in order to reveal little bit more of unknown, it is quite often needed to improve our research methods and even come up with some new ones. That is because the studied issues, or at least some aspects of them, have not been known for long, and research methods developed originally to study something else might not be suitable for studying the new issue.
We have some studies this week, that are at least partially method development papers. There is a paper about a meeting of statisticians, mathematicians, and climate scientists, where they discussed how uncertainties should be quantified in climate observations. One paper makes an effort to determine surface air temperatures using satellite measurements. Ice core syncronisation is the subject of one paper. Speaking of ice cores, there's another paper on ice cores which is borderline method development. Ice cores are used to study past climates but they have limited reach back in time. Currently longest ice core reaches back 800,000 years. Now researchers have studied ice flows in Allan Hills icefield and found out that there old ice has moved upwards, so old ice is there at the surface presenting possibility to extend ice core records beyond 800,000 years.
Other studies this week are touching the unknowns of carbon cycle, temperatures in European Alps, atmospheric carbon dioxide effects, Greenland glaciers, Southern Ocean wind, climate change scepticism, tropical and African rainfall, and atmospheric methane.
A little over a year ago we reported on the success of the the Regional Greenhouse Gas Initiative (RGGI), which is a carbon cap and trade system implemented by ten northeastern states in the USA (Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Rhode Island, and Vermont; New Jersey has since dropped out) which set the goal of reducing their carbon dioxide (CO2) emissions from the power sector by 10% by 2018.
Through the first two years of the system, the ten states had generated $789 million through the auctioning and direct sale of CO2 emissions allowances. Each state developed its own plan for investing those funds, but overall, 52% was used for energy efficiency programs, 14% for energy bill payment assistance, including assistance to low-income ratepayers, and 11% to accelerate deployment of renewable energy technologies. New York, New Hampshire, and New Jersey also diverted some of the funds to reduce their state budget deficits.
Arguments
A conservative specialist in environmental law—Professor Jonathan Adler of Case Western Reserve University—lays out a thoughtful conservative approach to tackling climate change in a recent post at The Atlantic magazine.
Adler suggests four policy changes to “make it cheaper and easier to adopt low-carbon technologies:” 1) prizes to spark innovation, 2) lower legal barriers to deployment, 3) a revenue-neutral carbon tax, and 4) adaptation.
