Month: July 2020

Reports Of The Demise Of Polar Bears Are Greatly Exaggerated

Wouldn’t it be nice if we could debate climate change for five minutes without hearing about polar bears or being subjected to footage of them perched precariously on a melting ice floe?

But that is a little too much to expect. Polar bears have become the pin-ups of climate change, the poor creatures who are supposed to jolt us out of thinking about abstract concepts and make us weep that our own selfishness is condemning these magnificent animals to a painful and hungry end.

Needless to say, the Guardian and BBC jumped on the opportunity for more polar bear coverage when a paper appeared in the journal Nature Climate Change, predicting that a high carbon emissions scenario ‘will jeopardise the persistence of all but a few high-Arctic subpopulations by 2100.’ The paper uses a new predictive model by Peter Molnar of the University of Toronto.

A BBC report, as usual, upgraded the claims made in the paper in order to state: ‘Polar bears will be wiped out by the end of the century unless more is done to tackle climate change, a study predicts.’ Except that the paper doesn’t quite say that. The high emissions scenario used in the study isn’t what would happen if the world continued on its current trajectory of fossil fuel use. Instead it uses a worst-case scenario called ‘RCP8.5’ dreamed up in 2014, which envisages that coal-burning will globally increase fivefold between now and 2100. This could be a challenge, because it would mean burning through more coal than, according to some estimates, exists on Earth. In fact, global coal-burning likely peaked in 2013. Even Nature Climate Changes’ mother journal Nature published a think piece in January calling for scientists and campaigners to stop using RCP8.5 as a ‘business as usual’ scenario, on the grounds that it is highly improbable.

But even if we were to jack up carbon emissions to the level envisaged by RCP8.5, and Arctic sea ice was to melt in accordance with the models, would it really mean the end of most polar bear populations? Given that polar bears feed on seals they catch by punching through sea ice, this may seem a reasonable claim. Yet the relationship between sea ice and polar bear population isn’t quite so simple.

A lot of the assumptions about polar bears and sea ice have been made on the back of the animals’ decline in the Western Hudson Bay area of Canada. Compared with the 1980s, sea ice there now breaks up on average two weeks earlier and refreezes a week later. As a result, polar bears are spending five months on land – where they struggle to find food – rather than four as before. Their estimated numbers fell by 22 per cent between 1987 and 2004, although this has levelled off since then. Polar bear numbers have also been falling in Canada’s Southern Beaufort Sea.

Yet it is a very different story in the Barents Sea, which lies to the north of Scandinavia and European Russia. There, the retreat of seasonal sea ice has been far more dramatic – it now hangs around, on average, 21 weeks less than it did 40 years ago. Yet polar bear numbers are stable. On Svalbard their numbers have increased by 40 percent – and the females seem to be in better physical condition now than they were 15 years ago. It is a different story, too, in the Chukchi Sea, which lies to the north of Alaska and Russia’s far east. There, sea ice forms for 41 days fewer than it did 40 years ago – yet the polar bear population seems to be stable, with no decline in the bears’ physical condition. The Kane Basin, off north western Greenland, has lost 53 days’ of sea ice in recent decades, yet the estimated number of polar bears more than doubled between 1997 and 2013.

All of which seems to indicate that polar bears, like many other creatures, have proved rather adaptable to changes in their environment. The assumption that they can only catch seals through sea ice, and will inevitably decline if their opportunities to do this disappear, seems simply to be wrong. Somehow or other, most populations of polar bears are finding enough to eat.

The end of polar bears has been predicted many times before. Indeed, one of the authors of the Nature Climate Change paper, Steven Armstrup, claimed in 2007 that the decline of sea ice would lead to a two thirds reduction in polar bear numbers by the middle of this century. The failure of overall polar bear populations to follow this downward trend, in spite of a decline is sea ice, was documented in a book The Polar Bear Catastrophe that Never Happened by [evolutionary biologist] Susan Crockford.

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July 25, 2020 at 02:56AM

Why Subsidised Wind & Solar Are Sending South Africa’s Power Prices Into Orbit

Rocketing power prices and grid instability are two inescapable consequences of subsidised wind and solar. While sunshine and breezes might be free, attempting to run your power system using nature’s gifts, brings with it a raft of other costs which RE zealots tend to gloss over.

The electricity generation and distribution system – which wind and solar power are meant to completely replace – is one that was designed to work all on its lonesome; no mythical mega-batteries; no load shedding when the wind drops or the sun sets; no prayers to the wind gods; no fuss; and no failures that can’t be fixed in an engineering jiffy.

The same can’t be said of the unreliables, which always and everywhere depend upon the system as it was – one built on ever-reliable coal, gas, nuclear and hydro (where its available). But STT is referring to a system that works, always has and always will. On the other hand, those seeking to profit from the wind and solar scam claim keep talking about a new ‘system’; when, in reality, all they’ve got to offer is chaos. And chaos costs.

Rob Jeffrey takes a look at how South Africa’s obsession with subsidised wind and solar is laying that cost squarely at the feet of South African power consumers and taxpayers.

Weaknesses of solar and wind, Myths and Questions that require an answer
Watts Up With That?
Rob Jeffrey
3 July 2020

It is claimed that wind and solar are the cheapest sources of electricity and these sources should dominate future electricity supply. This paper focuses on known additional costs and subsidies which are not taken into account in the costs of wind and solar put forward by their advocates.

Advocates of wind and solar claim a cost of 0.62 rand (about 3.6 US cents) /kWh. This is, however, the price at the gate of the supplier. It does not include all the costs of supply necessary to convert this electricity from non-dispatchable electricity supply at the gate to dispatchable electricity supply at the point of supply to the customer. These are in effect direct subsidies to solar and wind suppliers, whereas they should be added as a cost to the renewable energy suppliers.

Renewables, such as hydro, biomass and thermal have different qualities and are not considered in this paper. In any event, Hydro and thermal are not options as they are not available in quantity domestically in South Africa. Gas is another fossil fuel, which at this stage, is not found in significant economic amounts in South Africa. The critical issues are that solar and wind have very low load factors and are variable, intermittent and unpredictable. In other words, they are not dispatchable. In the case of wind, the load factor is an average of 35% or less and solar 26% or less. Their supply is weather dependent, and therefore backup must be available 100% of the time 24/7.

Coal has a load factor on average of approximately 80% and nuclear an average of 90%. Their load factors are affected by predictable maintenance requirements and generally to a lesser extent by unpredictable repair requirements. A reserve margin (or backup) of 20% has traditionally been considered sufficient to cover for both these events. Methodologies and more realistic estimates of the real costs of solar and wind, including back up, can be calculated using the load factor alone. This gives the cost of wind at R1.77/kWh and the cost of solar at R2.38/kWh. These costs must be compared to a coal cost of R1.31/kWh and nuclear at R1.44/kWh. More complex methodologies taking risk and uncertainty of outages into account and using variance or standard deviation as the estimate of risk put the costs of wind at R2.52/kWh, solar at R3.83, coal R1.10/kWh and nuclear R1.33/kWh.

Added to the claimed costs of 62cents/kWh for solar and wind should be the following items:

Additional grid costs: Transmission lines will have to be built, yet used for less than 35% of the time. This low usage suggests that at the minimum grid costs of wind must be at least approximately 3x the grid costs of dispatchable power units if not more. The capital cost per kWh and the running cost per kWh must be approximately 3x that of reliable dispatchable power supply.

Efficiency loss of backup and alternative electricity supply: Due to low utilisation, backup facilities would typically be running approximately 40% below their optimal efficiency. Their efficiency loss is in effect a direct subsidy of the solar and wind.

Excess supply of electricity: Because electricity supply from solar and wind is variable, there will be periods where a surplus of electricity will be generated. In terms of the power purchase agreements (PPA), Eskom must pay the renewable producers for the excess power being produced. All these are additional costs that at present are passed on to the utility (Eskom) or other electricity producers or consumers.

Insufficient electricity supply as a result of technology being unable to close the gap between supply and demand immediately: Because electricity supply from solar and wind is variable, unreliable, unpredictable and intermittent there will be periods where a shortage of electricity supply will exist. The economy will suffer as a result of the Cost Of Unserved Energy (COUE).

High Economic Cost Of Unserved Energy: The IRP estimates the COUE at R87.85/kWh. This is as per the National Energy Regulator of South Africa (NERSA) study. A senior energy expert estimated that load shedding cost South Africa more than R1-trillion over the previous decade or about 1.5% GDP growth per annum.

Insufficient electricity supply as a result of extended periods of weather-related conditions:

The Higher the penetration of low load, high variable intermittent technologies, the higher the Cost Of Unserved Energy: Models invariably are only as good as the assumptions used. Most models assume the certainty of output and do not take into account risk and uncertainty. The fact is that the real world is subject to risk and uncertainty.

Reduction in sales by Eskom as a result of artificially low prices offered by renewable suppliers: Installation of renewable power direct at customers’ or potential customers’ premises of Eskom reflect finally as a lost demand or sales at Eskom

Cost of backup for installation directly supplied by solar and wind: If there is a reduction in such customers’ electricity supply, Eskom is expected to provide immediate backup supply. Eskom must have the necessary substantial backup readily available. This is extremely costly.

Cost of purchasing electricity from customers who have their own renewable installations: The trend is that customers can sell their surplus electricity supply to Eskom. Invariably, there is a commitment to purchase, which in return reduces the perceived backup required. However, this is not true as backup is still necessary for regular backup requirements but also the full installation of the renewable supply at the customer’s premises. Either way, customers are paying for the additional costs involved.

Destruction of industries and political, social-economic impacts: The move to solar and wind as set out in the IRP would result in South Africa’s coal industry shrinking by 46%. Coal mining accounted for 26.7% of the total value of mining production in 2015, making it the most valuable in terms of sales of the 14 primary mining commodities. Several previously prosperous communities in Gauteng and South Africa would become ghost towns with rising unemployment and increasing poverty levels. Social benefits would increase dramatically.

Lack of permanent job creation: Renewable energy sources do not give rise to permanent jobs being created. Most jobs created by solar and wind relate only to the construction phase. Most jobs, mainly skilled jobs, are generated overseas in countries supplying equipment. These countries would primarily be Germany in the case of wind-related equipment and China in the case of solar equipment.

Export of jobs and Loss of energy sovereignty: The move towards solar and wind will mean that South Africa loses it energy sovereignty, primarily to Germany for imports of technology and equipment related to wind and China for equipment related to solar. South Africa will effectively export its skilled jobs overseas and suffer a loss of skills. Instead of South Africa being an energy exporter, it will become an energy importer as a result of losing coal exports and becoming dependent on gas imports. Any current account deficit caused should be factored into the cost of solar and wind.

Creation of a current account deficit and not utilising valuable natural assets: Coal is one of South Africa’s most significant commodity products and the country’s largest export. The importation of gas and loss of coal exports will result in an increasing and substantial current account deficit. Coal mining accounted for approximately 26% of the total value of mining production in 2015, making it the most valuable in terms of sales. Potential uranium reserves are also substantial. The drive for wind would deprive South African citizens of these benefits.

Levelised Cost of Electricity (LCOE) is not a sound methodology to compare highly variable and interruptible electricity technologies with electricity supplied by reliable dispatchable electricity-generating technologies: A report entitled ‘Critical Review of The Levelised Cost of Energy (LCOE) Metric’, by M.D. Sklar-Chik et al., South African Journal of Industrial Engineering December 2016 concludes that “LCOE neglects certain key terms such as inflation, integration costs, and system costs.” The work of Paul Joskow et al. of the Massachusetts Institute of Technology published in February 2011 wrote a paper entitled Comparing The Costs of Intermittent and Dispatchable Electricity Generating Technologies. They note “Many international reports prove that such electricity supply is costly due to its variability, interruptibility, inefficiency and its requirement of 100% backup”.

The test of global reality: There is nothing like the test of global reality. In 2016, the prices paid by industry in Germany were approximately 52% higher than France (nuclear) and 86% higher than Poland (coal). The average estimates discussed above result in costs that are close to this global reality.

The above costs are absorbed by Eskom or other suppliers or directly by customers. They can be measured in R billions /annum and should be added to the costs of solar and wind.

Emerging economies need to focus on those technologies which are efficient and effective. In South Africa, mining, manufacturing and industry need security of supply of electricity at competitive prices. The only two electricity generation sources of Energy available in South Africa that can achieve these objectives in this country are High-Efficiency Low-Emissions (HELE) coal, otherwise called ‘clean’ coal and nuclear.

The country must focus on raising its economic growth rate by ensuring it has a sustainable, secure supply of electricity at the lowest economic and financial cost. Any decision must be accompanied by the necessary supporting condition fostering domestic and foreign investment into its economy. The arguments above show clearly that renewables in the form of solar and wind in particular, almost certainly have substantial additional costs which are not fully accounted for in the current costs being utilised by their advocates. This also means that the so-called least cost optimum mix recommended by them is wrong. As a result, this methodology as currently defined and used is severely flawed. The technique and methodology recommended uses statistical calculations based on variable estimates utilising the variance and mean of each technology to calculate the COUE. Current models do not utilise any such statistical and analytical technique.

The above arguments and estimates lend force to the evidence that solar and wind, in particular, are unaffordable in the current economic situation in the country. The estimates strongly suggest that the least cost methodology is severely flawed and that going forward the renewable technologies of solar and wind should play a marginal role in any future technology mix for the country.

The final nail in the coffin for South Africa is that increased penetration of wind will lead to a rapidly rising import bill for gas imports and the demise of its coal mining industry, if not the entire mining industry. These are catastrophes which could ensure that the future of South Africa will move towards rising unemployment, increasing poverty and increasing social and political instability. South Africa needs to focus its energy plans on HELE or ‘clean’ coal, nuclear, domestic solar and limited gas.
Watts Up With That?

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July 25, 2020 at 02:31AM

Settled Science? New Climate Study Shifts the Goalposts to 2.6-3.9C

Guest essay by Eric Worrall

A new climate study has dismissed utterly implausible high end climate models. But the new study also seeks to raise the low end of the range of estimated climate sensitivity into the discomfort zone.

The climate won’t warm as much as we feared – but it will warm more than we hoped

July 23, 2020 5.52am AEST

Steven SherwoodARC Laureate Fellow, Climate Change Research Centre, UNSW

Eelco RohlingProfessor of Ocean and Climate Change, Australian National University

Katherine MarvelAssociate Research Scientist, NASA

We know the climate changes as greenhouse gas concentrations rise, but the exact amount of expected warming remains uncertain. 

major new assessment has now calculated a range of 2.6–3.9℃. This implies that alarmingly high estimates from some recent climate models are unlikely, but also that comfortingly low estimates from other studies are even less likely.

In 1979, a farsighted report estimated for the first time that equilibrium climate sensitivity falls somewhere between 1.5℃ and 4.5℃. So if carbon dioxide concentrations doubled, global temperatures would eventually increase by somewhere in that range. 

The width of this range is a problem. If equilibrium climate sensitivity lies at the low end of the range, climate change might be manageable with relatively relaxed national policies.

Read more: https://theconversation.com/the-climate-wont-warm-as-much-as-we-feared-but-it-will-warm-more-than-we-hoped-143175

The abstract of the study;

An assessment of Earth’s climate sensitivity using multiple lines of evidence

Authors: S. Sherwood, M.J. Webb, J.D. Annan, K.C. Armour, P.M. Forster, J.C., Hargreaves, G. Hegerl, S. A. Klein, K.D. Marvel, E.J. Rohling, M. Watanabe, T. Andrews, P. Braconnot, C.S. Bretherton, G.L. Foster, Z. Hausfather, A.S. von der Heydt, R. Knutti, T. Mauritsen, J.R. Norris, C. Proistosescu, M. Rugenstein, G.A. Schmidt, K.B. Tokarska, M.D. Zelinka.

We assess evidence relevant to Earth’s equilibrium climate sensitivity per doubling of atmospheric CO2, characterized by an effective sensitivity S. This evidence includes feedback process understanding, the historical climate record, and the paleoclimate record. An S value lower than 2 K is difficult to reconcile with any of the three lines of evidence. The amount of cooling during the Last Glacial Maximum provides strong evidence against values of S greater than 4.5 K. Other lines of evidence in combination also show that this is relatively unlikely. We use a Bayesian approach to produce a probability density (PDF) for S given all the evidence, including tests of robustness to difficult-to-quantify uncertainties and different priors. The 66% range is 2.6-3.9 K for our Baseline calculation, and remains within 2.3-4.5 K under the robustness tests; corresponding 5-95% ranges are 2.3-4.7 K, bounded by 2.0-5.7 K (although such high – confidence ranges should be regarded more cautiously). This indicates a stronger constraint on S than reported in past assessments, by lifting the low end of the range. This narrowing occurs because the three lines of evidence agree and are judged to be largely independent, and because of greater confidence in understanding feedback processes and in combining evidence. We identify promising avenues for further narrowing the range in S, in particular using comprehensive models and process understanding to address limitations in the traditional forcing-feedback paradigm for interpreting past changes.

Read more: https://climateextremes.org.au/wp-content/uploads/2020/07/WCRP_ECS_Final_manuscript_2019RG000678R_FINAL_200720.pdf

The study uses an unusual definition of equilibrium climate sensitivity, though they provide a detailed explanation for their choice. From the main body of the study;

In choosing the reference scenario to define sensitivity for this assessment, for practical reasons we depart from the traditional Charney ECS definition (equilibrium response with ice sheets and vegetation assumed fixed) in favor of a comparable and widely used, so-called “effective climate sensitivity” S derived from system behavior during the first 150 years following a (hypothetical) sudden quadrupling of CO2. During this time the system is not in equilibrium, but regression of global-mean top-of-atmosphere energy imbalance onto global-mean near-surface air temperature, extrapolated to zero imbalance, yields an estimate of the long-term warming valid if the average feedbacks active during the first 150 years persisted to equilibrium (Gregory et al., 2004). This quantity therefore approximates the long-term Charney ECS (e.g., Danabasoglu and Gent, 2009), though how well it does so is a matter of active investigation addressed below. Our reference scenario does not formally exclude any feedback process, but the 150-year time frame minimizes slow feedbacks (especially ice sheet changes).

Read more: Same link as above

The treatment of cloud feedback is interesting. The study acknowledges large cloud feedback uncertainties, mentions the Lindzen et al. (2001) “iris effect”, and admit GCMs cannot be trusted to reproduce observed cloud response, yet still appears to attempt to derive a cloud feedback factor based on satellite observations, and mix this observational cloud factor with model predictions.

The treatment of clouds may turn out to be one of the most controversial assumptions in the study – as Pat Frank has pointed out on a number of occasions, the magnitude of model cloud response error is significantly greater than the CO2 driven warming which models attempt to project, which calls into question whether climate models have any predictive skill whatsoever.

To the author’s credit they have described their method in great detail, so I’m looking forward to detailed responses to this study.

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July 25, 2020 at 12:47AM

New Video : COVID Cancel Culture

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July 24, 2020 at 11:01PM