It was 84 degrees near the Arctic Ocean this weekend as carbon dioxide hit its highest level in human history
Oh no! It’s sweltering in (or at least near) the Arctic! To emphasize the dire nature of this horrible news, the article goes on to say:
Over the weekend, the climate system sounded simultaneous alarms. Near the entrance to the Arctic Ocean in northwest Russia, the temperature surged to 84 degrees Fahrenheit (29 Celsius). Meanwhile, the concentration of carbon dioxide in the atmosphere eclipsed 415 parts per million for the first time in human history.
To the average American, who was given a very poor education in both geography and critical thinking, that sounds so bad. It shouldn’t be that warm near the Arctic Ocean, should it? Of course it should! All you have to do is look at a compilation of the weather statistics for the city being discussed (Arkhangelsk, Russia). As you can see, since 1940, the highest temperature recorded at Arkhangelsk was 93.9 F (34.4 C). During that same time period, the highest May temperature was 86.4 F (30.2 C). Both of those are higher than the “alarming” temperature being discussed in the article.
Now these results are for all years since 1940. The recent, “abnormally warm” temperatures caused by global warming are setting those records, right? Wrong. You can click on various years, and you will find that the highest temperature on record (34.4 C) occurred sometime between 1960 and 1980. As you can see, then, there is nothing unusual about it being 84 F near the Arctic Ocean at this time of year. Most people don’t know that, and most people (especially those who blindly accept what the High Priests of Science proclaim) aren’t willing to do any investigation on their own to find out.
Of course, that’s what the author of this article is counting on.
The majority of climate scientists think that global temperatures have risen over the past century mostly because of human activity. However, there are some climate scientists who think that the small changes we have seen in global temperature are mostly the result of natural variations that exist independently of people. Others simply say we don’t have enough information to know how much human activity has played a role in the process. Add to that the unreliability of much of the early data regarding global temperatures, and you end up with a picture that is far more murky than what most media outlets and politicians want you to see.
A recently-published study might help to eventually shed some light on how much human activity affects global temperatures. It comes from four climate scientists in China who are affiliated with The Climate Center of the Zhejiang Meteorologic Bureau, the Earth Science School of Zhejiang University, and the Shanghai Climate Center. They are convinced that the vast majority of the changes we have seen in global temperatures are due to natural variations, and those variations are buffered by the oceans. As a result, they have tried to analyze global temperatures from that perspective.
Since global temperature data sets don’t really agree with one another, they first had to choose which global temperatures they would actually use. They chose the Global Land Surface Temperature Anomaly Index (GLST) as compiled by the NOAA. They then tried to find correlations between those data and the Sea Surface Temperatures (SST) as compiled by the Hadley Climate Center. The correlations they found led them to develop a mathematical equation that would reproduce the GLST data. While the idea of finding a single equation that would fit all the GLST data might seem like an impossible task, it is not. One phrase I often hear from my nuclear chemistry colleagues is, “It only takes four parameters to fit an elephant.” In other words, if you have enough parameters in your equation, you can fit just about anything.
Of course, for something as complex as global temperatures, it takes more than four parameters. In fact, their paper indicates that it took 20. However, with their 20-parameter equation, they were able to reasonably reproduce the global temperature data that they were analyzing. The results can be seen in the image at the top of the post. The jagged, grey line indicates the data, and the smoother, black line indicates the results of their equation. As you can see, it does a pretty good job of fitting the known data.
Does that mean their equation is a good explanation of global temperatures? Not at all. It is simply an equation that has been forced to fit the data. What I find interesting, however, are the temperatures it predicts for the future. According to the equation, the earth has hit its maximum temperature for a while, and over the next 100+ years, the average temperature of the planet will cool. Do I think that prediction is correct? There is no way I can adequately judge that. There are simply too many unknowns in climate science for anyone to make a reliable prediction about what is going to happen in the future. Perhaps we will eventually learn enough about climate science to change that, but right now, the uncertainties simply preclude reasonable predictions.
However, here’s what I will say about this very interesting study: The authors assume that that the vast majority of the temperature variations we have seen are the result of natural processes. If, over the next 30 years, the data continue to fall in line with the predictions of their equation, that will lend more credence to their assumption. If not, that will indicate that either their assumption is wrong, or that some of the natural variations which cause global temperature changes are too long-term to show up in a century’s worth of unreliable temperature data.
Regardless of the outcome, I do think that this paper, while simple in its approach, is a valuable addition to climate science.
If you have been reading this blog for a while, you probably know that I am very skeptical of climate models that predict the consequences of rising carbon dioxide levels in the atmosphere. Initially, this was due to my own experience with large-scale computer models. In my early scientific research, I both wrote and used them, so I know how much their results are affected by the assumptions programmed into them. As time has gone on, my skepticism has increased, since it has been demonstrated over and over again that the climate models do not line up with the most relevant data.
There is a lot of dead, decaying matter on the floors of the tropical forests of the world. As that dead matter decomposes, it releases carbon dioxide into the atmosphere. Well, decomposition is driven by chemical reactions, and chemical reactions speed up with increasing temperature. So, as the world warms, what should happen to the rate of carbon dioxide produced by decomposition? It should increase, right? That will release more carbon dioxide into the air, which will accelerate warming. This is an example of a positive feedback mechanism. In such a mechanism, a change promotes a process that amplifies the change. This particular positive feedback mechanism is programmed into the climate models that are being used to predict the consequences of increased carbon dioxide in the atmosphere.
While that assumption makes perfect sense, the real world often works differently from our simple assumptions. That’s one reason Stephanie Roe decided to test it. She went to Puerto Rico’s El Yunque National Forest, where the US Forest Service set up infrared heaters in different parts of the forest. Those heaters were programmed to keep their surroundings 4 degrees Celsius warmer than the rest of the forest. Those parts of the forest, then, should behave like the tropical forests will behave if the earth warms by an average of 4 degrees. In addition, there were parts of the forest where identical, non-working heaters were placed. They served as control areas – they stayed at the normal temperature of the forest, but they had the physical structures of the heaters present. Roe introduced various kinds of dead matter (both native and non-native) to the forest in both the warmed sections and the control sections. She then collected samples later to test the rate of decomposition in each.
What did she find? She found that the result was precisely opposite of what is programmed into the climate models. The warmed areas of the forests had slower rates of decomposition than the control areas. Why? According to her research, it is because the warmer parts of the forest were drier. The process of decomposition is accelerated strongly by moisture, so the loss of moisture slowed down the decomposition more than the higher temperature sped it up. Thus, according to her research, increased temperatures should reduce the amount of carbon dioxide produced by decomposition. This, of course, is an example of a negative feedback mechanism: a change promotes a process that decreases the rate of change. Once again, such mechanisms are the hallmark of designed systems, so it is not surprising that it exists here on earth.
The more we learn about climate, the less confidence I have in the predictions of the climate change doomsayers.
While China and the U.S. lead the world in the amount of power generated by wind farms, India is not too far behind. As a result, a group of researchers from the Indian Institute of Science decided to study the ecological impacts of wind turbines. They analyzed turbines that have been installed in an Indian Mountain Range called the Western Ghats. Some of those wind turbines are pictured above. Specifically, they wanted to see if the predatory nature of wind turbines had other effects on the local ecosystem. Not surprisingly, it did.
First, they found that predator birds were four times less likely to be in the areas where wind turbines are installed compared to areas where they are not installed. That’s not surprising. Animals tend to avoid areas where they are preyed upon. Of course, the opposite is true as well. Animals tend to flock to places where they will not be preyed upon. As a result, the population of fan-throated lizards (a favorite meal of predator birds in the area) is significantly higher around wind turbines.
Interestingly enough, the effect of wind turbines was not limited to populations. The lizards’ behavior changed as well. Apparently, life is so carefree for the lizards living near the wind turbines that they have lost some of their fear of predators in general. The researchers tried to simulate predator attacks and found that they could get significantly closer to lizards that live near the wind turbines than they could get to lizards living where there are no wind turbines. Based on subsequent blood tests, the researchers concluded that lizards living near wind turbines have significantly less corticosterone (a stress hormone) in their blood.
So in the end, the ecological effect of wind farms goes beyond the slaughter of birds (and bats). It “trickles down” the food chain as well. The authors say:
By adding an effective trophic level to the top of food webs [by being an apex predator], we find that wind farms have emerging impacts that are greatly underestimated. There is thus a strong need for an ecosystem-wide view when aligning green-energy goals with environment protection. (bracketed statement mine)
I predict that as more research is done, we will see many more unexpected ecological effects from wind farms.
This is an important issue, because climate models (which make projections about future temperatures based on different emission scenarios) are “calibrated” against the known temperature data in an effort to make them more realistic. Since the satellite data have only been collected since 1979, they are rarely used. Instead, the longer temperature record (based on thermometers) is generally preferred. The two commonly-used thermometer records are GISS TEMP (maintained by NASA) and HadCrut4 (maintained by the University of East Anglia and the UK Met Office). Those two data sets are in good agreement with one another, but once again they do not agree with the satellite data.
Are these thermometer data reliable? Based on the PhD thesis of John D. McLean at James Cook University, the answer is “no.” He did what he claims is the first audit of the reliability of the Hadcrut4 data, and he has found 25 areas of concern. I will discuss only three. First, he finds many instances of anomalous data. One station in Colombia, for example, reports that the 1978 average monthly temperatures in April, June, and July were 81.5 oC, 83.4 oC, and 83.4 oC. In case you aren’t familiar with the Celsius temperature scale, that’s about 180 oF. Given that the highest temperature ever recorded on earth was 134 oF, it’s safe to say that the report from Colombia is simply wrong. He lists many other examples of anomalous data that cannot possibly be correct.
This isn’t a new suggestion. In fact, this recent study is partly a follow-up of a study that was published 14 years ago. In that study, the authors used a fairly simple physical model to indicate that by changing the way air is mixed near the surface of the earth, wind farms increase the temperature in their local area and, in turn, the entire planet. This new study uses a more sophisticated mathematical model, but it also compares the model’s results to warming that has actually been observed and measured near wind farms.
The authors show that their model reproduces the observed warming fairly well, so they use that model to make some estimates. They estimate that if all of the United States’ electrical needs are met with wind power, the wind farms would warm the continental U.S. by 0.24 degrees Celsius. The authors are quick to point out that this is much less than the warming that is supposed to occur as a result of the carbon dioxide produced by coal and gas power. However, it is clearly more than was expected and is at least ten times larger than any warming expected to be produced by meeting the needs of the country with solar power.
Of course, all of these models are far from realistic, because we are ignorant about so much when it comes to the earth’s climate and how various factors affect it. As a result, I take all of these numbers with a grain of salt. The actual fact is that we don’t know the warming that will occur as a result of any energy production source, including coal and gas. However, just as the science behind carbon dioxide trapping heat in the atmosphere is solid, the science behind this paper is solid. The authors demonstrate quite clearly that based on well-known physics, wind farms do warm their local area, and the observational studies they reference and use in their analysis confirm that this warming does, indeed, happen.
So what’s the bottom line? The most important one is the one I brought up in my five-year-old post about wind farms. The environmental effects of energy production aren’t as simple as people make them out to be. Every means of energy production will affect our planet in some way, and unfortunately, in the effort to produce “green” energy, this fact has been overlooked. If we are really interested in caring for our planet, we should not buy into a certain means of energy production (or a certain means of transportation) just because someone has decided it is “green.” Otherwise, we might be replacing a bad system with a worse one!
Corals are amazing animals that form reefs which are teeming with life. They eat things that are floating in the water around them, but they also have a mutualistic relationship with algae called “zooxanthellae.” The corals provide the algae with housing, and in exchange, the algae give the corals chemicals they need. It’s a wonderful system that allows both species to flourish.
However, there are times when this system breaks down. When corals become “stressed” (usually by a sudden change in temperature, the intensity of sunlight, pollution levels, etc.), the algae are expelled from the corals. The details of this process are still a mystery, but it usually causes the corals to turn white, as shown in the picture above. Because of that, this process is often called bleaching.
Large-scale coral bleaching events, in which reefs become extremely fragile, were virtually unheard-of before the 1980s.
That’s the typical “party line” when it comes to those who don’t want to study the issue of global warming seriously. Something bad is happening now, it hardly ever happened in the past, and if we don’t do something about it soon, we are all going to die. Not surprisingly, it just isn’t true.
When you read about global warming, aka “climate change,” you often hear about climate models that tell us the world will reach dangerously high temperatures if people don’t sharply reduce their use of carbon-dioxide-emitting energy sources. However, these models are built using our current understanding of climatology, which is incomplete at best. As a result, there is a lot of uncertainty in their forecasts. Specifically, they seem to overstate any warming that has actually occurred so far.
Why is that? The simple answer is that we don’t understand climate science very well, and as a result, it is hard to predict what effects human activity will have on future climate. Scientists, however, need a more detailed answer. What exactly is wrong with our understanding of climate science? Christopher Monckton, Third Viscount Monckton of Brenchley thinks he has found one reason. Whether or not he is correct, his assertion illustrates how little we know about forecasting climate.
Now, of course, Viscount Monckton is not a climate scientist. He has a masters in classics and a diploma in journalism studies. He served as a Special Advisor to Prime Minister Margaret Thatcher and is and a well-known skeptic of the narrative that global warming is a serious problem that has been caused by human activity. Nevertheless, he has studied climate science extensively and thinks he has found a “startling” mathematical error that is common to all climate models. He is currently trying to get a paper that makes his case published in the peer-reviewed literature, but as the article to which I linked shows, the reviewers have serious objections to its main thesis.
A few days ago, I ran across an interesting study that I think is worth discussing. Like most studies that try to understand human behavior, its results are incredibly tentative. Nevertheless, they are interesting, and they also are consistent with a trend that I have noticed among my colleagues and friends.
The researchers wanted to probe how a person’s belief in human-induced “climate change” affects his or her personal behaviors. They recruited 600 people from Amazon Mechanical Turk (I had never heard of it until reading the study), and assessed both their beliefs about human-induced climate change as well as their behavior when it came to four types of “pro-environmental” activities: recycling, using public transportation, purchasing environmentally-friendly consumer products, and utilizing reusable shopping bags.
One very important aspect of this study is that the researchers didn’t just do this once. They did it seven times throughout one year. That way, they could track beliefs and behaviors as they ebbed and flowed. Unfortunately, it is hard to keep people interested in a study like this, so while they started with 600 participants, only 291 actually completed all seven evaluations. However, some participants missed just a few evaluations, so an average of 413 participants were evaluated in each of the second through seventh analyses.
Probably because yesterday was Earth Day, I ran across an article written by Ronald Bailey for Earth Day 2000. It reviews some of the predictions made by “environmentalists”* in the 1970s, when the first Earth day was celebrated. As Bailey noted back in the year 2000:
The prophets of doom were not simply wrong, but spectacularly wrong. (emphasis his)
There are a lot of failed predictions in the article, but I want to start with the one I highlighted in the meme above. Here is the full quote, which is found in the Spring 1970 issue of The Living Wilderness:
Demographers agree almost unanimously on the following grim timetable: by 1975 widespread famines will begin in India; these will spread by 1990 to include all of India, Pakistan, China and the Near East, Africa. By the year 2000, or conceivably sooner, South and Central America will exist under famine conditions….By the year 2000, thirty years from now, the entire world, with the exception of Western Europe, North America, and Australia, will be in famine. (emphasis his)
Notice how Dr. Gunter starts. He uses the consensus argument. He says that demographers (those who study human populations) “agree almost unanimously” with his grim forecast. I have no idea whether or not that statement was correct back in the 1970s, but it is eerily similar to what we hear now in reference to global warming, AKA climate change. Climate alarmists insist that we must listen to them, because climate scientists agree almost unanimously that doom is right around the corner. In light of this fact, it is useful to note that the supposed “consensus” has been spectacularly wrong before.