Blowing in the wind: there isn’t the faintest chance that any of the Government’s renewable energy targets will be met

Is there any subject on which more nonsense is talked and written than the mindblowing proposals being bandied about by the Government for meeting our EU target of generating, within 10 years, 30 per cent of our electricity from renewable sources? (That is roughly six times the current total, meaning that we have by far the most challenging target of any country in Europe.)

For instance, the industry regulator, Ofgem, recently announced that by 2020 we will need to have spent 40 billion pounds on connecting up our new renewable energy sources to the national grid - 4 billion pounds a year. Alistair Buchanan, the head of Ofgem, blithely claimed, on the BBC Today programme and elsewhere, that this would only add 6 pounds a year to the average electricity bill of Britain’s 25 million households. Yet ten seconds with a calculator shows that the cost per household of that 4 billion pounds a year works out to 160 pounds.

On top of this, the Government wants us to have, by 2020, offshore wind farms with a capacity of 33 gigawatts (1 gigawatt = 1,000 megawatts). At the current capital cost of 3 million per megawatt of capacity, this would cost another 100 billion (10 billion a year, or 400 a year for each household), to be paid for through our electricity bills. However, even if they could all be built, they would produce on average only around a quarter of that amount of electricity.

Add in 8 billion a year (or 320 per household) which, the Government forecasts, we will be paying by then through its ludicrously generous feed-in tariff for solar power and, for these measures alone, our total annual bill for the dream of meeting our EU renewables target would be at least 22 billion. That’s considerably more than the entire wholesale cost of Britain’s electricity generated from all sources last year, at 18.6 billion.

In other words, these measures alone would much more than double our electricity bills, for producing on average - and very unreliably - barely as much energy as we get from a handful of conventional power stations.

In reality, there isn’t the faintest chance that any of the Government’s targets will be met. But the massive diversion of resources that it is doing its best to encourage will not help when it comes to filling the looming 40 per cent gap in our electricity supplies, as 17 of the older nuclear and coal-fired power stations are forced to close. There is virtually nothing, then, in these plans to ensure that we can keep Britain’s lights on.

Read more here.

CAUAYAN, Philippines (Oct. 18)—The strongest cyclone in years to buffet the Philippines knocked out communications and power as residents took shelter Monday, while flooding in Vietnam swept away a bus and 20 of its passengers, including a girl pulled from her mother’s grasp by the raging waters.

Enlarged here.

Super Typhoon Megi, crossing the northern Philippines, was expected to add to the already heavy rains that have fallen on much of Asia. In China, authorities evacuated 140,000 people from a coastal province ahead of the typhoon.

Surface map 00GMT Monday, October 18, 2010, ECMWF

Megi could later hit Vietnam, where flooding has caused 30 deaths in recent days, in addition to those missing and feared dead after a bus was snatched off a road by surging currents Monday.

Megi packed sustained winds of 140 miles (225 kilometers) per hour and gusts of 162 mph (260 kph) as it made landfall midday Monday at Palanan Bay in Isabela province, felling trees and utility poles and cutting off power, phone and Internet services in many areas. It appeared to be weakening while crossing the mountains of the Philippines’ main northern island of Luzon.

With more than 3,600 Filipinos riding out the typhoon in sturdy school buildings, town halls, churches and relatives’ homes, roads in and out of coastal Isabela province, about 320 kilometers (200 miles) northeast of Manila, were deserted and blocked by collapsed trees and power lines.

One man who had just rescued his water buffalo slipped and fell into a river and probably drowned, said Bonifacio Cuarteros, an official with the Cagayan provincial disaster agency.

As it crashed ashore, the typhoon whipped up huge waves. There was zero visibility and radio reports said the wind was so powerful that people could not take more than a step at a time. Ships and fishing vessels were told to stay in ports, and several domestic and international flights were canceled.

Thousands of military reserve officers and volunteers were on standby, along with helicopters, including six Chinooks that were committed by U.S. troops holding war exercises with Filipino soldiers near Manila, said Benito Ramos, a top disaster-response official.

“This is like preparing for war,” Ramos, a retired army general, told The Associated Press. “We know the past lessons, and we’re aiming for zero casualties.”

In July, an angry President Benigno Aquino III fired the head of the weather bureau for failing to predict that a typhoon would hit Manila. That storm killed more than 100 people in Manila and outlying provinces.

This time, authorities sounded the alarm early and ordered evacuations and the positioning of emergency relief and food supplies days before the typhoon hit. The capital was expected to avoid any direct hit, though schools were closed.

Megi was the most powerful typhoon to hit the Philippines in four years, government forecasters say. A 2006 howler with 155-mph (250-kph) winds set off mudslides that buried entire villages, killing about 1,000 people.

In central Vietnam, officials said 20 people on a bus were swept away Monday by strong currents from a river flooded by recent rains unrelated to Megi, while another 17 survived by swimming or clinging to trees or power poles.

One survivor treaded water for 3 and one half hours as the current pushed her downstream and she was forced to let go of her daughter due to exhaustion. The girl is among the missing.

Officials said 30 other people died in central Vietnam from flooding over the weekend, and five remain missing.

Megi could add to the misery.

“People are exhausted,” Vietnamese disaster official Nguyen Ngoc Giai said by telephone from Quang Binh province. “Many people have not even returned to their flooded homes from previous flooding, while many others who returned home several days ago were forced to be evacuated again.”

China’s National Meteorological Center said Megi was expected to enter the South China Sea on Tuesday, threatening southeasterern coastal provinces. The center issued its second-highest alert for potential “wild winds and huge waves,” warning vessels to take shelter and urging authorities to brace for emergencies.

Floods triggered by heavy rains forced nearly 140,000 people to evacuate from homes in the southern island province of Hainan, where heavy rains left thousands homeless over the weekend, the official Xinhua News Agency reported Monday.

Thailand also reported flooding that submerged thousands of homes and vehilce and halting train service. No casualties were reported, but nearly 100 elephants were evacuated from a popular tourist attraction north of the capital. Read more here.

Reference:
Christy, J.R., Herman, B., Pielke Sr., R., Klotzbach, P., McNider, R.T., Hnilo, J.J., Spencer, R.W., Chase, T., and Douglass, D. 2010. What do observational datasets say about modeled troposphere temperature trends since 1979? Remote Sensing 2: 2148-2169. Testing of climate model results is an important but difficult problem. One of the key model results is the presence of a tropical troposphere “hotspot” in which the troposphere warms faster than the surface under conditions of enhanced greenhouse gas forcing. Previous studies have produced disagreement over whether data were consistent with models on this question. In this study, the authors made several advances by doing the following: 1) enhancing the data for surface trends, 2) extending the data to a 31-year length, 3) evaluating the wind-based temperature estimates, and 4) clarifying the meaning of “best estimate” multi-data warming trends from data and models.

Two prior studies had derived tropospheric temperature trends from the Thermal Wind Equation (TWE)—which uses radiosonde measurements of wind speed to calculate temperature—on the theoretical basis that warmer air should move faster than cooler air. They found that there were biases in the data for this type of calculation. For example, particularly for older radiosonde observations, on days when the upper wind was stronger, the balloons would tend to blow out of receiver range. This created a bias by causing missing data for high winds for older observations, leading to a spurious warm trend over time. Overall, the TWE-based trends were three times greater than trends derived from all other types of data. In addition, they did not agree with other wind data, and were also based on much sparser data. This type of data was therefore not used in the authors’ analysis, which also identified a small warm bias in the RSS satellite data that was explained by Christy and his colleagues.

The next innovation was to use the Scaling Ratio (SR), which is the ratio of atmospheric temperature trend to surface temperature trend. The SR attempts to factor out the effect of the lack of actual (historic) El Niño’s or other oscillations in climate model runs, and different such simulated events in different computer runs.

The nine researchers found that the SR for real-world data was 0.8 plus or minus 0.3, whereas the model simulations had a SR of 1.38 plus or minus 0.08 (a significant difference). That is, the data show a lower rate of warming for the lower troposphere than for the surface (though not statisically different), whereas the models show amplification, as theorized. In fact, the SR value for the middle troposphere data was 0.4, which is even more different from the model predictions. Only the SR for RSS data, which has the documented warming bias noted above, overlaps with any model SR results.

This study thus suggests that current state-of-the-art climate models have something fundamentally wrong with how they represent earth’s atmosphere.

See post here.

Man is not the primary cause of change in the Arctic says book by Russian scientists.

Forget the orthodox view of Arctic climate change - this book has a very different message. (h/t to WUWT commenter Enneagram)

Published last year, this is a synthesis of work by the Russian Arctic and Antarctic Research Institute (AARI). It sets out the data and experience of scientists over 85 years, drawing together much already published in the area. For a book that is billed under a climate change heading, this is actually more an antidote to the hype usually associated with warming in the Arctic. A few pages of each chapter are available on-line and even that is well worth reading; no doubt even better in its entirety.

The Preface sets the tone of the book very clearly - “...scientists have predicted a significant decrease in sea-ice extent in the Arctic and even its complete disappearance in the summertime by the end of the 21st century. This monograph presents results of studies of climatic system changes in the Arctic, focused on ice cover, that do not justify such extreme conclusions.” “Many studies and international projects, such as the Arctic Climate Impact Assessment (ACIA), attribute the air temperature increase during the last quarter of the 20th century exclusively to accumulation of greenhouse gases in the atmosphere. However these studies typically do not account for natural hydrometeorological fluctuations whose effects on multiyear variability, as this monograph shows, can far exceed the anthropogenic impact on climate.”

The book begins by examining the major effects of the Polar Ice caps and their overall stability on Earth’s climate - affecting albedo, and regulating the heat flux from the sea to atmosphere. Climate variations are discussed and the WMO’s “30 year average” definition of climate is not considered applicable in the Arctic because fluctuations in the polar climate are so large.

Chapter 2 looks at what is known about changes in sea ice in the 20th century. The Russian data sets probably hold the most extensive information available for the first half of the century due to interest in the Northern Sea Route in the 1930s. In addition, measurements of ice thickness also go back to the middle of the 1930s when they were taken regularly for coast-bound ice at many of the Polar stations.

It is particularly interesting what they say about Arctic air temperatures (Chapter 4). “Periodic cooling and warming events are evident in air temperature fluctuations in the Arctic during the 20th century, similar to changes in ice cover.” A cool period at the beginning of the 20th century was followed by what is commonly referred to as the “Arctic Warming Period” in the 1920s-1940s. Relative cooling was widespread between the late 1950s to late 1970s, followed by the current warming period peaking in recent years. Gridded average temperature anomalies for 70-85N produce a curve that fits a polynomial trend to the sixth power and the cycle periodicity is 50-60 years (Figure 4.1). Other indicators in Arctic and Antarctic support this cycle and show its global nature. On the subject of polar amplification, whereby weather and climate variability increase with latitude, a number of models and explanations are discussed. None of these involve CO2.

Cyclic temperature for Arctic stations in the GHCNv2 dataset enlarged here (originally posted here). 

The authors point out there is an abundance of hypotheses as to the possible causes of climate and ice variation and climate change (a ‘long-term’ phenomenon) but these lack detailed long-term data. They state “where data do exist, we should prefer data to computer models”; they believe model projections of future ice area fluctuations are unreliable. Actually, they have some deliciously scathing remarks about climate models.

“The models neglect natural fluctuations because they have no means of incorporating them, and put the entire blame for climate changes since the 19th century on human activity.”

On possible future changes they predict that “..in the 21st century, oscillatory (rather than unidirectional) ice extent changes will continue to dominate Arctic seas.” A new ice maximum in 2030-2035 is predicted (Figure 6.1) and this will have major implications for shipping in the region.

From the results of spectral analyses, they conclude that there are 50-60 year cycles and less prevalent ones at 20 years, 8-12 years and 2-3 years. These are closely related to variations in general atmospheric circulation. In the longer term the decreasing trend of ice extent may be a segment of a 200 year cyclic variation responsible for the Medieval Warm Period and Little Ice Age. Much of the discussion about solar effects is behind the paywall for the book, however there are some strong conclusions about solar effects on Arctic climate. Despite the small variation in Total Solar irradiance (TSI) through solar cycles, solar activity may have a greater effect on high latitudes because of interaction with the Earth’s magnetic field. Solar system “dissymmetry” (barycentre) influences are also mentioned as closely corresponding to the 60 year cycles.

The authors conclude that the simulation by the general circulation models does not appear to reflect the cyclic features in Arctic ice extent and climate, and, if their cyclic interpretations of climate variation are correct, ice cover will continue to fluctuate as there is little connection with the anthropogenic burning of fossil fuels.

Climate Change in Eurasian Arctic Shelf Seas: Centennial Ice Cover Observations. Authors: Ivan E. Frolov, Zalmann M. Gudkovich, Valery P. Karklin, Evgeny G. Kovalev, and Vasily M. Smolyanitsky. Published by Springer/Praxis (2009) ISBN 9783540858744

See post here. See Verity’s Digging in the Clay site here.

There was a very clever paper published in Science this past week by Lacis, Schmidt, Rind, and Ruedy that uses the GISS climate model (ModelE) in an attempt to prove that carbon dioxide is the main driver of the climate system.

This paper admits that its goal is to counter the oft-quoted claim that water vapor is the main greenhouse gas in our atmosphere. (They provide a 1991 Lindzen reference as an example of that claim).

Through a series of computations and arguments, the authors claim that is actually the CO2, not water vapor, that sustains the warmth of our climate system.

I suspect this paper will result in as many opinions in the skeptic community as there are skeptics giving opinions. But unless one is very careful in reading this paper and knows exactly what the authors are talking about, it is easy to get distracted by superfluous details and miss the main point. For instance, their table comparing the atmospheres of the Earth, Venus, and Mars does nothing to refute the importance of water vapor to the Earth’s average temperature. Appearances can be deceiving.

I do not have a problem with the authors’ calculations or their climate model experiment per se. There is not much new here, and their model run produces about what I would expect. It is an interesting exercise that has value by itself.

It is instead their line of reasoning I object to - what they claim their model results mean in terms of causation - in their obvious attempt to relegate the role of water vapor in the atmosphere to that of a passive component that merely responds to the warming effect of CO2.

OUR ASSUMPTIONS DETERMINE OUR CONCLUSIONS

From what I can tell reading the paper, their claim is that, since our primary greenhouse gas water vapor (and clouds, which constitute a portion of the greenhouse effect) respond quickly to temperature change, vapor and clouds should only be considered “feedbacks” upon temperature change - not “forcings” that cause the average surface temperature of the atmosphere to be what it is in the first place.

Though not obvious, this claim is a central tenet of the paper, and is an example of the cause-versus-effect issue I repeatedly refer to in the past when discussing some of the most fundamental errors made in the scientific ‘consensus’ on climate change.

It is a subtle attempt to remove water vapor from the discussion of “control” over the climate system by definition. Only those of us who know enough of the details of forcing-feedback theory within the context of climate change theory will likely realize this, through.

But just because water vapor responds quickly to temperature change does not mean that there are no long-term water vapor (or cloud changes) - not due to temperature - that cause climate change. Asserting so is a non sequitur, and just leads to circular reasoning.

I am not claiming the authors are being deceptive. I think I understand why so many scientists go down this path of reasoning. They view the climate system as a self-contained, self-controlled complex of physically intertwined processes that would forever remain unchanged until some “external” influence (forcing) enters the picture and alters the rules by which the climate system operates.

Of course, increasing CO2 is the currently fashionable forcing in this climatological worldview.

But I cannot overemphasize the central important of this paradigm (or construct) of climate change theory to the eventual conclusions the climate researcher will inevitably make.

If one assumes from the outset that the climate system can only vary through changes imposed external to the normal operation of the climate system, then one removes natural, internal climate cycles from the list of potential causes of global warming. And natural changes in water vapor (or more likely, clouds) are one potential source of internally-driven change. There are influences on cloud and water vapor other than temperature which in turn help to determine the average temperature state of the climate system.

After assuming clouds and water vapor are no more than feedbacks upon temperature, the Lacis et al. paper then uses a climate model experiment to ‘prove’ their paradigm that CO2 drives climate - by forcing the model with a CO2 change!

Well, DUH. If they had forced the model with a water vapor change, it would have done the same thing. But they had already assumed water vapor and clouds cannot be climate drivers.

They ran a climate model experiment in which they instantaneously removed all of the atmospheric greenhouse gases except water vapor, and they got rapid cooling “plunging the climate into an icebound Earth state”. The result after 7 years of model integration time is shown in the next image.

Such a result is not unexpected for the GISS model. But while this is indeed an interesting theoretical exercise, we must be very careful about what we deduce from it about the central question we are ultimately interested in: “How much will the climate system warm from humanity adding carbon dioxide to it?” We can’t lose sight of why we are discussing all of this in the first place.

As I have already pointed out, the authors have predetermined what they would find. They assert water vapor (as well as cloud cover) is a passive follower of a climate system driven by CO2. They run a model experiment that then “proves” what they already assumed at the outset.

But we also need to recognize that their experiment is misleading in other ways, too.

First, the instantaneous removal of 100% of the greenhouse gases in the atmosphere except for water vapor causes about 8 times the radiative forcing (over 30 Watts per sq. meter) as a 100% increase in CO2 (2XCO2, less than 4 Watts per sq. meter), something that will not occur until late this century - if ever. Currently, we are about 40% of the way to that doubling.

This is the so-called ‘logarithmic effect’ adding more and more CO2 has a progressively weaker radiative forcing response.

So are we to assume that this dramatic theoretical example should influence our views of the causes of global warming, when their no-CO2 experiment involves ~20 times the radiative forcing of what has occurred to date from adding more CO2 to the atmosphere?

Furthermore, the cloud feedbacks in their climate model are positive, which further amplifies the model’s temperature response to forcing. As readers here are aware, our research suggests that cloud feedbacks in the real climate system might be so strongly negative that they could more than negate any positive water vapor feedback.

In fact, this is where the authors have made a logical stumble. Everyone agrees that the net effect of clouds is to cool the climate system on average. But the climate models suggest that the cloud feedback response to the addition of CO2 to our currentclimate system will be just the opposite, with cloud changes acting to amplify the warming.

What the authors didn’t realize is that when they decided to relegate the role of clouds in the average state of the climate system to one of “feedback”, they did not realize their model’s positive cloud feedback actually contradicts the known negative “feedback” effect of clouds on the climate’s normal state.

Oops.

CONCLUSION
Taken together, the series of computations and claims made by Lacis et al. might lead the casual reader to think, “Wow, carbon dioxide really does have a strong effect on the Earth’s climate system!” And, in my view, it does. But the paper really tells us nothing new about (1) how much warming we can expect from adding more CO2 to the atmosphere, or (2) how much of recent warming was caused by CO2.

The paper implies that it presents new understanding, but all it does is get more explicit about the conceptual hoops one must jump through in order to claim that CO2 is the main driver of the climate system. From that standpoint alone, I find the paper quite revealing.

Unfortunately, what I present here is just a blog posting. It would take another peer-reviewed paper that follows an alternative path, to effectively counter the Lacis paper, and show that it merely concludes what it assumes at the outset. I am only outlining here what I see as the main issues.

Of course, the chance of editors at Science allowing such a response paper to get published are virtually zero. The editors at Science choose which scientists will be asked to provide peer review, and they already know who they can count on to reject a skeptic’s paper.

Many of us have already been there, done that. See post here.