UNEP Emissions Gap Report 2018 Part 3 – UNEP tacitly admits climate mitigation is a failure

To those following the superficial political spin of climate policy, a UN organisation admitting that climate mitigation has failed may come as a surprise. Yet one does not have to go too deeply into the new UNEP Emissions Gap Report 2018 to see that this tacit admission is clearly the case. It is contained within the 3 major points in the Executive Summary.

By policy failure, I mean to achieve a global substantial reduction in GHG emissions in the near future, even if that reduction is not in line with either the 1.5°C or 2.0°C warming objective. On this measure, the UNEP is tacitly admitting failure it the summary.
The Executive Summary of the UNEP Emissions Gap Report 2018 starts on the pdf page 14 of 112, numbered page xiv.

Point 1 – Current commitments are inadequate

1. Current commitments expressed in the NDCs are inadequate to bridge the emissions gap in 2030. Technically, it is still possible to bridge the gap to ensure global warming stays well below 2°C and 1.5°C, but if NDC ambitions are not increased before 2030, exceeding the 1.5°C goal can no longer be avoided. Now more than ever, unprecedented and urgent action is required by all nations. The assessment of actions by the G20 countries indicates that this is yet to happen; in fact, global CO2 emissions increased in 2017 after three years of stagnation.

This is not a statement about a final push to get policy over the line, but a call for a complete change of direction. The tacit admission is that this is politically impossible. In the amplification it is admitted that in the G20 major economies – most of them developing countries – even the “NDC ambitions” for 2030 are not likely to be achieved. As I showed in the Part 2 post, 9 of the G20 will actually increase their emissions from 2015 to 2030 if the commitments are fully met, and the sum of the emissions increases will be greater than the emissions decreases. The exhortation for “unprecedented and urgent action” is not like Shakespeare’s Henry V rallying his men with a “once more unto the breach chaps and we will crack it” but more about like “Hey good fellows, if we are really going to breach the defenses we need to upgrade from the colorful fireworks to a few kegs of proper gunpowder, then make a few genuine sacrifices. I will be cheering you all the way from the rear“. This sentiment is contained in the following statement.

As the emissions gap assessment shows, this original level of ambition needs to be roughly tripled for the 2°C scenario and increased around fivefold for the 1.5°C scenario.

Point 2 – Emissions are increasing, not decreasing rapidly

2. Global greenhouse gas emissions show no signs of peaking. Global CO2 emissions from energy and industry increased in 2017, following a three-year period of stabilization. Total annual greenhouse gases emissions, including from land-use change, reached a record high of 53.5 GtCO2e in 2017, an increase of 0.7 GtCO2e compared with 2016. In contrast, global GHG emissions in 2030 need to be approximately 25 percent and 55 percent lower than in 2017 to put the world on a least-cost pathway to limiting global warming to 2°C and 1.5°C respectively.

In just 13 years from now global emissions need to be down by a quarter or more than a half to achieve the respective 2°C and 1.5°C targets. Emissions are still going up. Again, an admission that the progress in over two decades is small in relation to the steps needed to achieve anything like a desired outcome.

Point 3 – Scale of the gap in numbers

3. The gap in 2030 between emission levels under full implementation of conditional NDCs and those consistent with least-cost pathways to the 2°C target is 13 GtCO2e. If only the unconditional NDCs are implemented, the gap increases to 15 GtCO2e. The gap in the case of the 1.5°C target is 29 GtCO2e and 32 GtCO2e respectively. This gap has increased compared with 2017 as a result of the expanded and more diverse literature on 1.5°C and 2°C pathways prepared for the IPCC Special Report.

Some developing countries said they would change course conditional on massive amounts of funding. It is clear this will not be forthcoming. Fleshing out the 1.5°C target in the SR1.5 Report showed that it requires more onerous policies than previously thought. Each year UNEP produces a chart that nicely shows the scale of the problem. The 2018 version on page xviii is reproduced as figure 1.

Figure 1 : The emissions GAP in 2030 under the 1.5°C and 2°C scenarios, from the UNEP Emissions Gap Report 2018.

The widening gap between the 1.5°C and 2°C pathways and current projected commitments over the last five reports is shown in figure 2.

This widening gap is primarily a result of recalculations. Increased emissions in 2017 are secondary.

Conclusion

That nearly 200 nations would fail to agree to collectively and substantially reduce global emissions was obvious from the Rio Declaration in 1992. This exempted developing countries from any obligation to reduce their emissions. These developing countries now have at least four fifths of the global population and around two-thirds emissions. It was even more obvious from reading the Paris Agreement, where vague aspirations are evident. It is left to the reader to work out the implications of paragraphs like 4.1 and 4.4, which renders the UNFCCC impotent in reducing emissions. The latest UNEP Emissions Gap Report presents the magnitude of the mitigation policy failure and very clear statements about that failure.

Kevin Marshall

Leave EU Facebook Overspending and the Brexit Result

Last week an Independent article claimed

Brexit: Leave ‘very likely’ won EU referendum due to illegal overspending, says Oxford professor’s evidence to High Court

The article began

It is “very likely” that the UK voted for Brexit because of illegal overspending by the Vote Leave campaign, according to an Oxford professor’s evidence to the High Court.

Professor Philip Howard, director of the Oxford Internet Institute, at the university, said: “My professional opinion is that it is very likely that the excessive spending by Vote Leave altered the result of the referendum.
“A swing of just 634,751 people would have been enough to secure victory for Remain.
“Given the scale of the online advertising achieved with the excess spending, combined with conservative estimates on voter modelling, I estimate that Vote Leave converted the voting intentions of over 800,000 voters in the final days of the campaign as a result of the overspend.”

Is the estimate conservative? Anthony Masters, a Statistical Ambassador for the Royal Statistical Society, questions the statistics in the Spectator. The 800,000 was based upon 80 million Facebook users, 10% of whom clicked in on the advert. Of those clicking, 10% changed their minds.

Masters gave some amplification on in a follow-up blog post Did Vote Leave’s overspending cause their victory?
The reasons for doubting the “conservative” figures are multiple, including
– There were not 80 million voters on Facebook. Of the 46 million voters, at most only 25.6 million had Facebook accounts.
– Click through rate for ads is far less than 10%. In UK in 2016 it was estimated at 0.5%.
– Advertising is not the source of campaigning. It is not even viewed as the primary source, merely bolstering other parts of a campaign through awareness and presence.
– 10% of those reading the advert changing their minds is unlikely. Evidence is far less.
Anthony Masters concludes the Spectator piece by using Professor Howard’s own published criteria.

Prof Howard’s 2005 book, New Media Campaigns and the Managed Citizen, also argues that we should apply a different calculation to that submitted to the High Court. His book says to apply a one per cent click-through rate, where 10 per cent “believe” what they read; and of that 10 per cent act. This ‘belief’ stage appears to have been omitted in the High Court submission’s final calculation. Using these rates, this calculation turns 25.6 million people into 2,560 changed votes – hardly enough to have swung the referendum for Leave, given that their margin of victory was over a million votes. If we share a belief in accuracy, this erroneous claim should have limited reach.

There is further evidence that runs contrary to Prof Howard’s claims.

1. The Polls
To evaluate the statistical evidence for a conjecture – particularly for a contentious and opinionated issue like Brexit – I believe one needs to look at the wider context. If a Facebook campaign swung the Referendum campaign in the final few days from Remain to Leave, then there should be evidence of a swing in the polls. In the blog article Masters raised three graphs based on the polls that contradict this swing. It would appear that through the four weeks of the official campaign the Remain / Leave split was fairly consistent on a poll of polls basis. From analysis by pollster YouGov, the Leave share peaked on 13th June – ten days before the referendum. The third graphic, from a statistical analysis from the LSE, provides the clearest evidence.

The peak was just three days before the murder of MP Jo Cox by Tommy Mair. Jo Cox was a Remain campaigner, whilst it was reported that the attacker shouted slogans like “Britain First”. The shift in the polls could have been influenced by the glowing tributes to the murdered MP, alongside the speculation of the vile motives a clear Vote Leave supporter. That Jo Cox’s murder should have had no influence, especially when campaigning was suspended as a result of the murder, does not seem credible.

On Twitter, Anthony Masters also pointed to a question in Lord Ashcroft’s poll carried out on the day of the referendum – How the United Kingdom voted on Thursday… and why to a graphic that looked at when people had decided which way to vote. At most 16% of leave voters made up their minds in the last few days, slightly less than the 18% who voted remain.

The same poll looked at the demographics.


This clearly shows the split by age group. The younger a voter the more likely they were to vote Remain. It is not a minor relationship. 73% of 18-24s voted for Remain, whilst 40% of the 65% voted. Similarly, the younger a person the greater the time spent on social media such as Facebook.

2. Voting by area
Another, aspect is to look at the geographical analysis. Using Chris Hanretty’s estimates of the EU referendum results by constituency, I concluded that the most pro-Remain areas were the centre of major cities and in the University Cities of Oxford, Cambridge and Bristol. This is where the most vocal people reside.

The most pro-Leave areas were in the minor towns such are Stoke and Boston. Greater Manchester provided a good snapshot of the National picture. Of the 22 constituencies is estimated that just 3 has a majority remain vote. The central to the City of Manchester. The constituencies on the periphery voted to Leave, the strongest being on the east of Manchester and a few miles from the city centre. Manchester Central contains many of the modern flats and converted warehouses of Manchester. Manchester Withington has a preponderance of media types working at Media City for the BBC and ITV, along with education sector professionals.

These are the people who are not just geographically marginalised, but often feel politically marginalised as well.

Concluding comments

Overall, Professor Howard’s claims of late Facebook posts swinging the Referendum result are not credible at all. They are about as crackpot (and contradict) as the claims of Russian influence on the Brexit result.
To really understand the issues one needs to look at the data from different perspectives and the wider context. But the more dogmatic Remainers appear to be using their power and influence – backed by scanty assertions -to thrust their dogmas onto everyone else. This is undermining academic credibility, and the democratic process. By using the courts to pursue their dogmas, it also threatens to pull the legal system into the fray, potentially undermining the respect for the rule of law for those on the periphery.

Kevin Marshall

Natural Variability in Alaskan Glacier Advances and Retreats

One issue with global warming is discerning how much of that warming is human caused. Global temperature data is only available since 1850. That might contain biases within the data, some recognized (like the urban heat island effect) and others maybe less so. Going further back is notoriously difficult, with proxies for temperature having to be used. Given that (a) recent warming  in the Arctic has been significantly greater than warming at other latitudes (see here) and (b) the prominence given a few years ago to the impact of melting ice sheets, the retreat of Arctic glaciers ought to be a useful proxy. I was reminded of this with yesterday’s Microsoft screensaver of Johns Hopkins Glacier and inlet in Glacier Bay National Park, Alaska.

The caption caught my eye

By 1879, when John Muir arrived here, he noticed that the huge glacier had retreated and the bay was now clogged with multiple smaller glaciers.
I did a quick search on how for more information on this retreat. At the National Park Service website, there are four images of the estimated glacier extent.
The glacier advanced from 1680 to 1750, retreated dramatically in the next 130 years to 1880, and then retreated less dramatically in the last 130+ years. This does not fit the picture of unprecedented global warming since 1950.

The National Park Service has more detail on the glacial history of the area, with four maps of the estimated glacial extent.

The glacial advance after 1680 enveloped a village of some early peoples. This is so something new to me. Previous estimates of glacier movement in Glacier Bay have only been of the retreat. For instance this map from a 2012 WUWT article shows the approximate retreat extents, not the earlier advance. Is this recently discovered information.

I have marked up the John Hopkins Glacier where the current front is about 50 miles from the glacier extent in 1750.
The National Park Service has a more detailed map of Glacier Bay, with more detailed estimated positions of the glacier terminus at various dates. From this map the greatest measured retreat of John Hopkins Glacier was in 1929. By 1966 it had expanded over a mile and the current terminus in slightly in front of the 1966 terminus. This is an exception to the other glaciers in Glacier Bay which are still retreating, but at a slower rate than in the nineteenth century.

As the human-caused warming is supposed to have predominately after 1950 the glacial advance and retreat patterns of the extensive Glacier Bay area do not appear to conform to those signals.

A cross check is from the Berkeley Earth temperature anomaly for Anchorage.

Whilst it might explain minor glacial advances from the 1929 to 1966, it does not explain the more significant glacial retreat in the nineteenth century, nor the lack of significant glacial retreat from the 1970s.

Kevin Marshall

UNEP Emissions Gap Report 2018 Part 2 – Emissions Projections by Country

On previous UNEP Emission Gap Reports I found that although they showed the aggregate global projected emissions, there has been no breakdown by country. As mitigation policies are mostly enacted by nation states, and the aim is to reduce global emissions, it would be useful to actually see how each of the near 200 nation states have pledged contribute to that objective.  Table 2.1 on page 9 of the UNEP Emissions Gap Report 2018 (published last week) goes part way to remedy this glaring omission. The caption states

Table 2.1: Overview of the status and progress of G20 members, including on Cancun pledges and NDC targets.


The G20 economies accounted for 78% of global emissions (excluding LULUCF) in 2017. The table does not clearly show the estimate emissions in 2015 and 2030, only the emissions per capita in 2015 (including LULUCF) and the percentage change in emissions per capita from 2015 to 2030. So I have done my own calculations based on this data using the same future population estimates as UNEP. That is from the medium fertility variant of the United Nations World Population Prospects 2017 edition. There are two additional assumptions I have made in arriving at these figures. First, the share of global emissions in 2015 for each country was exactly the same as in 2017. Second, the global shares including LULUCF (Land use, land-use change and forestry) are the same as those excluding LULUCF. This second assumption will likely understate the total emissions shares of countries like Brazil and Indonesia, where land use has high, and variable, emissions impacts. It may impact the country rankings by a small amount. However, the overall picture shown in Figure 1 will not be materially changed as the report states on page XV that the land use element was just 4.2 GtCO2e of the 53.5 GtCO2e estimated emissions in 2017.

In Figure 1 it is only G20 countries with 33% of current global emissions where emissions are projected to be lower 2030 than in 2015. The other G20, with 45% of global emissions, are projected to be higher. There are wide variations. I calculate, Argentina is projected to increase its emissions by 7% or 32 MtCO2e, Turkey by 128% or 521 MtCO2e and India by 93% or 2546 MtCO2e.
To get a clearer picture I have looked at the estimates changes between 2015 and 2030  in Figure 2. Please note the assumptions made above, particularly concerning LULUCF. I also make the additional assumption that in rest of the world emissions will increase in line with projected population growth, so emissions per capita will be unchanged.

The calculated figures show a net increase of 7.4 GtCO2e, compared to EGR2018 estimates of 6 GtCO2e including LULUCF. It might be a reasonable assumption that there are net reductions in removing the rainforests by burning, and increase in trees due to more planting, and the impact of increased growth due to higher CO2 levels will be net positive.
Note that whilst the USA has given notice of exiting the Paris Agreement, and thus its pledges, the pledge was a very soft target. It is more than likely the United States will have the greatest emissions reductions of any country between 2015 and 2030, and have one of the largest percentage reductions as well. These reductions are mostly achieved without economically damaging mitigation policies.
The figures used for the G20 countries in Table 2.1 are only vague estimates as section 2.4.2 (Emissions trends and targets of individual G20 members) implies. However, the assumption of a net increase of 29% for the rest of the world might not be valid if one uses country INDC submissions as a basis for calculation. There are a few countries that have pledged to reduce emissions. Andorra and Liechtenstein are two examples. But among the more populous emerging economies, it is clear from the INDC submissions that there is no intention to reduce emissions.

Figure 3 estimates the implied increase in emissions in the more populous countries outside of the G20 for the unconditional scenarios.

I would also have liked to include DR Republic of Congo, Egypt and Iran, with a combined population of 260 million. However, lack of data in the INDCs prevented this.
Although the 8 countries in Figure 3 contain one eighth of the global population, they currently have just 4% of global emissions. But their aggregate projected emissions increase without outside assistance is 3.0 GtCO2e, on top of 2.1 GtCO2e in 2015. Combined with the 7.4 GtCO2e estimated increase for the G20 countries and it is difficult to see how the UNEP estimates an increase just 3 GtCO2e. (see Figure ES.3 on page XVIII).

There appear to be no countries with a population of more than 40 million outside of the G20 who are promising to decrease their emissions. Tanzania, Colombia, Kenya and Algeria (combined population 190 million people) are all projecting significant emissions increases, whilst Myanmar and Sudan have inadequate data to form an estimate. A quick check of 8 non G20 countries with populations of 30-40 million has the same result. Either an increase in emissions or no data. 

Implications for mitigation policy

In summary, of the 45 nations with a population above 30 million, just 10 have pledged to have emissions lower in 2030 than 2015. The United States will likely achieve this objective are well. The other 34 nations will likely have higher emissions in 2030, with most significantly higher. The 11 emissions-reducing nations have a population of 1.1 billion against 5.3 billion in the 34 other nations and 1.15 billion in nations or territories with a population of less than 30 million. In terms of emissions, barring economic disaster, I estimate it is likely that countries with in excess of 60% of global emissions in 2017 will have emissions in 2030 that exceed those of 2015.  

To put this in context, the Emissions Gap report states on page xv

According to the current policy and NDC scenarios, global emissions are not estimated to peak by 2030.

My analysis confirms this. The Report further states

Total annual greenhouse gases emissions, including from land-use change, reached a record high of 53.5 GtCO2e in 2017, an increase of 0.7 GtCO2e compared with 2016. 
In contrast, global GHG emissions in 2030 need to be approximately 25 percent and 55 percent lower than in 2017 to put the world on a least-cost pathway to limiting global warming to 2°C and 1.5°C respectively.

After over 20 years of annual meeting to achieve global reductions in emissions, there is still no chance of that happening. In the light of this failure UNEP appear to have fudged the figures. Part of this is justified, as many developing countries appear to have put through unjustifiable BAU scenarios then claimed “climate actions” that will bring the projection more into line with what would be a non-policy forecast. COP 24 at Katowice will just be another platform for radical environmentalists to denigrate capitalist nations for being successful, and for a collective finger-wagging at the United States. 

The next part will look at the coded language of the Emissions Gap Report 2018 that effectively admits the 2°C and 1.5°C ambitions are impossible.

Kevin Marshall

 

UNEP Emissions Gap Report 2018 Part 1 – The BBC Response

Over the past year I have mentioned a number of times to UNEP Emissions Gap Report 2017. The successor 2018 EGR (ninth in the series) has now been published. This is the first in a series of short posts looking at the issues with the report. First up is an issue with the reporting by the BBC.
On the 27th Matt Macgarth posted an article Climate change: CO2 emissions rising for first time in four years.
The sub-heading gave the real thrust of the article.

Global efforts to tackle climate change are way off track says the UN, as it details the first rise in CO2 emissions in four years.

Much of the rest of the article gives a fair view of EGR18.  But there is a misleading figure. Under “No peaking?” the article has a figure titled

Number of countries that have pledged to cap emissions by decade and percentage of emissions covered”.

In the report Figure 2.1 states

Number of countries that have peaked or are committed to peaking their emissions, by decade (aggregate) and percentage of global emissions covered (aggregate).

The shortened BBC caption fails to recognize that countries in the past peaked their emissions unintentionally.  In looking at Climate Interactive‘s bogus emissions projections at the end of 2015 I found that, collectively, the current EU28 countries peaked their emissions in 1980. In the USA emissions per capita peaked in 1973. Any increases since then have been less than the rise in population. Yet Climate Interactive’s RCP8.5, non-policy, projection apportionment by country assumed that 

(a) Emissions per capita would start to increase again in the EU and USA after falling for decades

(b) In China and Russia emissions per capita would increase for decades to levels many times that of any country.

(c) In India and African countries emissions per capita would hardly change through to 2100, on the back of stalled economic growth. For India, the projected drop in economic growth was so severe that on Dec 30th 2015 to achieve the projection the Indian economy would have needed to have shrunk by over 20% before Jan 1st 2016. 

Revising the CO2 emissions projections (about 75% of the GHG emissions EGR18 refers to) would have largely explained the difference between the resultant 4.5°C of warming in 2100 from the BAU scenario of all GHG emissions and the 3.5°C consequential on the INDC submissions. I produced a short summary of more reasonable projections in December 2015.

Note that EGR18 now states the fully implemented INDC submissions will achieve 3.2°C of warming in 2100 instead of 3.5°C that CI was claiming three years ago.

The distinction between outcomes consequential on economic activity and those resultant from the deliberate design of policy is important if one wants to distinguish between commitments that inflict economic pain on their citizens (e.g. the UK) and commitments that are almost entirely diplomatic hot air (the vast majority). The BBC fails to make the distinction historically and in the future, whilst EGR18 merely fails with reference to the future.  

The conclusion is that the BBC should correct its misreporting, and the UN should start distinguishing between hot air and substantive policy to could cut emissions. But that would mean recognizing climate mitigation is not just useless, but net harmful to every nation that enacts policy that will make deep cuts in actual emissions,

Kevin Marshall

Two Contrasting Protests on Climate Change

Yesterday marked two protests related to climate change. One in central London by a group of climate extremists baying for more stringent climate policies. The other right across France demanding the removal of a small additional tax on fuel.

The Climate Extremists

Yesterday a group calling themselves !EXTINCTION REBELLION! had a series of protests around London, including blocking off five major bridges. They have a long history, having been founded almost three weeks ago on Halloween. Their aims are quite clear from a mercifully short video.

It is based on “science“.

The Crux

Even without the other ecological drivers of mass species extinction, natural resource exhaustion and growing human population pressure, human-caused (anthropogenic) climate breakdown alone is enough to wipe out the human species by the end of this century, if governments do not immediately begin to reverse their extractivismand ‘growth’ -based economic policies.

This is why the Extinction Rebellion campaign has at its core a group of activists who are prepared to go to prison for peaceful civil disobedience, to get the necessary media coverage for long enough to leverage the government and the public into war-level mobilisation mode.

When you repeatedly come across the figure of 2 degrees i.e. limiting global warming to 2 degrees, think of what happens to a human body when it experiences a temperature increase of more than 2 degrees.

The recent IPCC SR1.5 was the product of two and a half years trying to come up with scary stories to frighten governments into action. Two examples of the scary headlines from the SPM.

Temperature extremes on land are projected to warm more than GMST (high confidence): extreme hot days in mid-latitudes warm by up to about 3°C at global warming of 1.5°C and about 4°C at 2°C, and extreme cold nights in high latitudes warm by up to about 4.5°C at 1.5°C and about 6°C at 2°C (high confidence). The number of hot days is projected to increase in
most land regions, with highest increases in the tropics (high confidence).

By 2100, global mean sea level rise is projected to be around 0.1 metre lower with global warming of 1.5°C compared to 2°C (medium confidence).

In Britain we will be wiped out by a few 20°C+ hot nights and extra sea level rise of four inches. Maybe we could listen to the 40% of the global population that lives in the tropics.

The “science” section includes this quote from Bill McKibben.

What those numbers mean is quite simple. This industry has announced…in promises to shareholders, that they are determined to burn five times more fossil fuel than the planet’s atmosphere can begin to absorb.

This is not science, but blinkered ideology. Why blinkered? Try going to the CDP Carbon Majors Report 2017 Appendix 1 – Cumulative emissions 1988-2015 %. Below are the top 10.

If the !XR! really believe in the climate apocalypse, shouldn’t they be protesting outside the Chinese, Russian, Iranian and Indian Embassies, and inciting rebellion in those countries? Or are they just climate totalitarians trying to wreck the well-being of the British people?

The Carbon Tax Revolt

On the same day in France there were massive nationwide protests after the Macron government raised its hydrocarbon tax this year by 7.6 cents per litre on diesel and 3.9 cents on petrol. This lead to the formation of the gilets jaunes (yellow vests) movement that have organised at least 630 protests nationwide. From the website blocage17novembre.com. I grabbed the a screenshot map of the protest locations.

These protests became far from peaceful, as frustrated drivers tried to push their way through the protesters. The BBC reports one person killed and 227 killed. The BBC also reports that the 200,000+ protesters are backed by about 75% of the French public.

Yet !EXTINCTION REBELLION! should be supporting the Macron

Lessons for the Climate Extremists

Protests in a single country will not work. Protests in many countries will not work either, as people have other priorities. Further, it is too late to convince countries to sign up to massive cuts in emissions. That opportunity was missed in 1992, when “developing” countries were exempted from any obligation to constrain there emissions. Those countries, with at least 80% of the global population and up to two-thirds of global emissions have shown no inclination to change course. The protests in France show how even very small changes can lead to massive protests. In the UK fuel prices are not raised due to political unpopularity.

If such extremists still believe they are correct in their prophesies, and I am in denial, there are a number of strategies that they can legitimately use to evangelize.

  • Let contrary ideas to their own be evaluated on same unemotive level playing field as their own. In the past on hearing reports of court cases of heinous crimes, I have been convinced more by the daft excuses of the defendant than the prosecution’s evidence.  Alternatively, the overturned terrorist convictions in the 1970s of the Guildford Four and the Birmingham Six undermined belief in the Rule of Law.  So too with the false climate alarmism undermines my belief in scientific evidence.
  • Rather than accept whatever “science” that the supports alarmism is put out, seek to clarify the likelihood, type, extent, location and timing of coming catastrophes. That way, people can better adapt to changing conditions. The problem here is that predictions of doom are most likely false prophesies.
  • Supporting and encouraging Governments where they are encountering popular opposition. Why were !XR! not in France supporting President Macron? He not only supports the ban on fracking (with maybe 80% of Europe’s frackable gas reserves), but also have banned any fossil fuel extraction on French soil. After all !XR! believe this is a WW2 type emergency. Winston Churchill swallowed his loathing of the Bolsheviks to extinguish the Nazi Empire. Is climate not important enough to seek allies and give them some encouragement in time of need?

Climate alarmists will not accept what I say, as this would threaten their world views. They have plenty of others to fall back on for reassurance, but in reality they are just supporting policies that are net harmful.

Kevin Marshall

Australian Beer Prices set to Double Due to Global Warming?

Earlier this week Nature Plants published a new paper Decreases in global beer supply due to extreme drought and heat

The Scientific American has an article “Trouble Brewing? Climate Change Closes In on Beer Drinkers” with the sub-title “Increasing droughts and heat waves could have a devastating effect on barley stocks—and beer prices”. The Daily Mail headlines with “Worst news ever! Australian beer prices are set to DOUBLE because of global warming“. All those climate deniers in Australia have denied future generations the ability to down a few cold beers with their barbecued steaks tofu salads.

This research should be taken seriously, as it is by a crack team of experts across a number of disciplines and Universities. Said, Steven J Davis of University of California at Irvine,

The world is facing many life-threatening impacts of climate change, so people having to spend a bit more to drink beer may seem trivial by comparison. But … not having a cool pint at the end of an increasingly common hot day just adds insult to injury.

Liking the odd beer or three I am really concerned about this prospect, so I rented the paper for 48 hours to check it out. What a sensation it is. Here a few impressions.

Layers of Models

From the Introduction, there were a series of models used.

  1. Created an extreme events severity index for barley based on extremes in historical data for 1981-2010.
  2. Plugged this into five different Earth Systems models for the period 2010-2099. Use this against different RCP scenarios, the most extreme of which shows over 5 times the warming of the 1981-2010 period. What is more severe climate events are a non-linear function of temperature rise.
  3. Then model the impact of these severe weather events on crop yields in 34 World Regions using a “process-based crop model”.
  4. (W)e examine the effects of the resulting barley supply shocks on the supply and price of beer in each region using a global general equilibrium model (Global Trade Analysis Project model, GTAP).
  5. Finally, we compare the impacts of extreme events with the impact of changes in mean climate and test the sensitivity of our results to key sources of uncertainty, including extreme events of different severities, technology and parameter settings in the economic model.

What I found odd was they made no allowance for increasing demand for beer over a 90 year period, despite mentioning in the second sentence that

(G)lobal demand for resource-intensive animal products (meat and dairy) processed foods and alcoholic beverages will continue to grow with rising incomes.

Extreme events – severity and frequency

As stated in point 2, the paper uses different RCP scenarios. These featured prominently in the IPCC AR5 of 2013 and 2014. They go from RCP2.6, which is the most aggressive mitigation scenario, through to RCP 8.5 the non-policy scenario which projected around 4.5C of warming from 1850-1870 through to 2100, or about 3.8C of warming from 2010 to 2090.

Figure 1 has two charts. On the left it shows that extreme events will increase intensity with temperature. RCP2.6 will do very little, but RCP8.5 would result by the end of the century with events 6 times as intense today. Problem is that for up to 1.5C there appears to be no noticeable change what so ever.  That is about the same amount of warming the world has experienced from 1850-2010 per HADCRUT4 there will be no change. Beyond that things take off. How the models empirically project well beyond known experience for a completely different scenario defeats me. It could be largely based on their modelling assumptions, which is in turn strongly tainted by their beliefs in CAGW. There is no reality check that it is the models that their models are not falling apart, or reliant on arbitrary non-linear parameters.

The right hand chart shows that extreme events are porjected to increase in frequency as well. Under RCP 2.6 ~ 4% chance of an extreme event, rising to ~ 31% under RCP 8.5. Again, there is an issue of projecting well beyond any known range.

Fig 2 average barley yield shocks during extreme events

The paper assumes that the current geographical distribution and area of barley cultivation is maintained. They have modelled in 2099, from the 1981-2010 a gridded average yield change with 0.5O x 0.5O resolution to create four colorful world maps representing each of the four RCP emissions scenarios. At the equator, each grid is about 56 x 56 km for an area of 3100 km2, or 1200 square miles. Of course, nearer the poles the area diminishes significantly. This is quite a fine level of detail for projections based on 30 years of data to radically different circumstances 90 years in the future. The results show. Map a) is for RCP 8.5. On average yields are projected to be 17% down. As Paul Homewood showed in a post on the 17th, this projected yield fall should be put in the context of a doubling of yields per hectare since the 1960s.

This increase in productivity has often solely ascribed to the improvements in seed varieties (see Norman Borlaug), mechanization and use of fertilizers. These have undoubtably have had a large parts to play in this productivity improvement. But also important is that agriculture has become more intensive. Forty years ago it was clear that there was a distinction between the intensive farming of Western Europe and the extensive farming of the North American prairies and the Russian steppes. It was not due to better soils or climate in Western Europe. This difference can be staggering. In the Soviet Union about 30% of agricultural output came from around 1% of the available land. These were the plots that workers on the state and collective farms could produce their own food and sell surplus in the local markets.

Looking at chart a in Figure 2, there are wide variations about this average global decrease of 17%.

In North America Montana and North Dakota have areas where barley shocks during extreme years will lead to mean yield changes over 90% higher normal, and the areas around have >50% higher than normal. But go less than 1000 km North into Canada to the Calgary/Saskatoon area and there are small decreases in yields.

In Eastern Bolivia – the part due North of Paraguay – there is the biggest patch of > 50% reductions in the world. Yet 500-1000 km away there is a North-South strip (probably just 56km wide) with less than a 5% change.

There is a similar picture in Russia. On the Kazakhstani border, there are areas of > 50% increases, but in a thinly populated band further North and West, going from around Kirov to Southern Finland is where there are massive decreases in yields.

Why, over the course of decades, would those with increasing yields not increase output, and those with decreasing yields not switch to something else defeats me. After all, if overall yields are decreasing due to frequent extreme weather events, the farmers would be losing money, and those farmers do well when overall yields are down will be making extraordinary profits.

A Weird Economic Assumption

Building up to looking at costs, their is a strange assumption.

(A)nalysing the relative changes in shares of barley use, we find that in most case barley-to-beer shares shrink more than barley-to-livestock shares, showing that food commodities (in this case, animals fed on barley) will be prioritized over luxuries such as beer during extreme events years.

My knowledge of farming and beer is limited, but I believe that cattle can be fed on other things than barley. For instance grass, silage, and sugar beet. Yet, beers require precise quantities of barley and hops of certain grades.

Further, cattle feed is a large part of the cost of a kilo of beef or a litre of milk. But it takes around 250-400g of malted barley to produce a litre of beer. The current wholesale price of malted barley is about £215 a tonne or 5.4 to 8.6p a litre. About cheapest 4% alcohol lager I can find in a local supermarket is £3.29 for 10 x 250ml bottles, or £1.32 a litre. Take off 20% VAT and excise duty leaves 30p a litre for raw materials, manufacturing costs, packaging, manufacturer’s margin, transportation, supermarket’s overhead and supermarket’s margin. For comparison four pints (2.276 litres) of fresh milk costs £1.09 in the same supermarket, working out at 48p a litre. This carries no excise duty or VAT. It might have greater costs due to refrigeration, but I would suggest it costs more to produce, and that feed is far more than 5p a litre.

I know that for a reasonable 0.5 litre bottle of ale it is £1.29 to £1.80 a bottle in the supermarkets I shop in, but it is the cheapest that will likely suffer the biggest percentage rise from increase in raw material prices. Due to taxation and other costs, large changes in raw material prices will have very little impact on final retail costs. Even less so in pubs where a British pint (568ml) varies from the £4 to £7 a litre equivalent.

That is, the assumption is the opposite of what would happen in a free market. In the face of a shortage, farmers will substitute barley for other forms of cattle feed, whilst beer manufacturers will absorb the extra cost.

Disparity in Costs between Countries

The most bizarre claim in the article in contained in the central column of Figure 4, which looks at the projected increases in the cost of a 500 ml bottle of beer in US dollars. Chart h shows this for the most extreme RCP 8.5 model.

I was very surprised that a global general equilibrium model would come up with such huge disparities in costs after 90 years. After all, my understanding of these models used utility-maximizing consumers, profit-maximizing producers, perfect information and instantaneous adjustment. Clearly there is something very wrong with this model. So I decided to compare where I live in the UK with neighbouring Ireland.

In the UK and Ireland there are similar high taxes on beer, with Ireland being slightly more. Both countries have lots of branches of the massive discount chain. They also have some products on their website aldi.co.uk and aldi.ie.  In Ireland a 500 ml can of Sainte Etienne Lager is €1.09 or €2.18 a litre or £1.92 a litre. In the UK it is £2.59 for 4 x 440ml cans or £1.59 a litre. The lager is about 21% more in Ireland. But the tax difference should only be about 15% on a 5% beer (Saint Etienne is 4.8%). Aldi are not making bigger profits in Ireland, they just may have higher costs in Ireland, or lesser margins on other items. It is also comparing a single can against a multipack. So pro-rata the £1.80 ($2.35) bottle of beer in the UK would be about $2.70 in Ireland. Under the RCP 8.5 scenario, the models predict the bottle of beer to rise by $1.90 in the UK and $4.84 in Ireland. Strip out the excise duty and VAT and the price differential goes from zero to $2.20.

Now suppose you were a small beer manufacturer in England, Wales or Scotland. If beer was selling for $2.20 more in Ireland than in the UK, would you not want to stick 20,000 bottles in a container and ship it to Dublin?

If the researchers really understood the global brewing industry, they would realize that there are major brands sold across the world. Many are brewed across in a number of countries to the same recipe. It is the barley that is shipped to the brewery, where equipment and techniques are identical with those in other parts of the world. This researchers seem to have failed to get away from their computer models to conduct field work in a few local bars.

What can be learnt from this?

When making projections well outside of any known range, the results must be sense-checked. Clearly, although the researchers have used an economic model they have not understood the basics of economics. People are not dumb  automatons waiting for some official to tell them to change their patterns of behavior in response to changing circumstances. They notice changes in the world around them and respond to it. A few seize the opportunities presented and can become quite wealthy as a result. Farmers have been astute enough to note mounting losses and change how and what they produce. There is also competition from regions. For example, in the 1960s Brazil produced over half the world’s coffee. The major region for production in Brazil was centered around Londrina in the North-East of Parana state. Despite straddling the Tropic of Capricorn, every few years their would be a spring-time frost which would destroy most of the crop. By the 1990s most of the production had moved north to Minas Gerais, well out of the frost belt. The rich fertile soils around Londrina are now used for other crops, such as soya, cassava and mangoes. It was not out of human design that the movement occurred, but simply that the farmers in Minas Gerais could make bumper profits in the frost years.

The publication of this article shows a problem of peer review. Nature Plants is basically a biology journal. Reviewers are not likely to have specialist skills in climate models or economic theory, though those selected should have experience in agricultural models. If peer review is literally that, it will fail anyway in an inter-disciplinary subject, where the participants do not have a general grounding in all the disciplines. In this paper it is not just economics, but knowledge of product costing as well. It is academic superiors from the specialisms that are required for review, not inter-disciplinary peers.

Kevin Marshall

 

IPCC SR1.5 – Notes on Calculations and Assumptions

Given that my previous post was about failing to reconcile the emissions estimates for 1.5°C and 2.0°C of warming in the IPCC fifth assessment report (AR5), I was intrigued to see how the new IPCC “special report on the impacts of global warming of 1.5 °C above pre-industrial levels” would fare. However, that will have to wait for another post, as first there are some “refinements” from AR5 in how results are obtained. From my analysis they would appear that key figures on temperatures and climate sensitivities are highly contrived.

Isn’t 1.5°C of warming already built in? 

Chapter 1 Page 24

Expert judgement based on the available evidence (including model simulations, radiative forcing and climate sensitivity) suggests that if all anthropogenic emissions were reduced to zero immediately, any further warming beyond the 1°C already experienced would likely be less than 0.5°C over the next two to three decades, and also likely less than 0.5°C on a century timescale.

This basically states that if all emissions were stopped now there is more than a 50% chance that warming would not exceed 1.5°C. But using previous assumptions 1.5°C should be already be built in. 

If ECS = 3.0 (as in AR5) then that implies the net effect of all GHGs and all aerosols is less than 396 ppm, despite CO2 on its own in September 2018 being 405.5 ppm (1.6°C of eventual warming). Further, in 2011 the impact of all GHGs combined was equivalent to 430 ppm, or an extra 40 ppm more than CO2 on its own. On that basis we are at the around 445 ppm or fractionally about the 2.0°C warming level. However, in AR5 it was assumed (based on vague estimates) that the negative human impacts of aerosols exactly offset the addition of other GHGs (e.g. methane) so that only CO2 is considered. Even then based on ECS = 3.0 without further emissions 1.5°C will be eventually reached.

But ECS has been lowered.

From Chapter 1 Annex Page 11

…Equilibrium Climate Sensitivity (ECS) of 2.7°C and Transient Climate Response (TCR) of 1.6°C and other parameters as given in Millar et al. (2017).

This raises the CO2-eq level to achieve 1.5°C of warming by 15-16 ppm from 396ppm and the CO2-eq level to achieve 2.0°C by 23-24 ppm from 444 ppm. Mauna Loa CO2 levels in September averaged 405.5 ppm. With ECS = 2.7 this is equivalent to just 1.44°C of eventual warming compared to 1.60°C  when ECS = 3.0. What is more significant is that if ECS were 2.8 eventual warming of 1.50°C would be in the pipeline sometime before the end of the year. ECS = 2.7 is the highest ECS that us currently compatible with the statement made above if CO2 alone is taken into account. Consider this in the light of 2013 AR5 WG1 SPM, which stated on page 16

Equilibrium climate sensitivity is likely in the range 1.5°C to 4.5°C

And in a footnote on the same page.

No best estimate for equilibrium climate sensitivity can now be given because of a lack of agreement on values across assessed lines of evidence and studies.

 In AR5 they chose ECS = 3.0 as it was in the middle of the range. A range unchanged since the Charney Report of 1979. I am not aware of any that establishes ECS is a range that would justify ECS = 2.7 that is not contradicted by other research. For instance Lewis and Curry 2018 gives a median estimate for ECS of 1.66.

Transient Climate Response (TCR)

But how does the Transient Climate Response (TCR) of 1.6°C fit into this? Some context can be had from the very start of the Summary for Policy-Makers SPM-4

A1.1. Reflecting the long-term warming trend since pre-industrial times, observed global mean surface temperature (GMST) for the decade 2006–2015 was 0.87°C (likely between 0.75°C and 0.99°C)

With TCR = 1.6°C for a doubling of CO2 levels what is the warming generated from a rise in CO2 levels from 280 to 400.83 ppm? That is a rise in CO2 levels from pre-industrial times to the average level in 2015. I calculate it to be 0.83°C. Make TCR = 1.7°C and that increases to 0.88°C. It is effectively assuming that both 100% of the rise in average temperatures in over 150 years is due to CO2 alone (consistent with AR5), and there has been no movement whatsoever from the short-term Transient Climate Response to the long-term Equilibrium Climate Sensitivity. However, if TCR is a variable figure derived from a calculation from revealed warming and CO2 rise, it becomes meaningless nonsense unless you can clearly demonstrate the other assumptions are robust. That is (1) 100% of past warming was due to human emissions (2) the impact of GHGs other than CO2 are effectively cancelled out by aerosols etc. (3) natural factors are net zero (4) the average temperature data anomaly is without any systematic biases. For instance, when measured CO2 levels were about 390ppm, the AR5 WG3 SPM stated in the last sentence on page 8

For comparison, the CO2-eq concentration in 2011 is estimated to be 430 ppm (uncertainty range 340 to 520 ppm)

It seems a pretty shaky foundation to the assumption that negative impact of aerosols (with uncertainties) will offset the combined impact of other GHG increases.

Summary and Concluding Comments

On the estimates of climate sensitivity, it appears to be set so that the IPCC can still claim that if emissions stopped tomorrow then there would be a greater than 50% chance of 1.5°C warming never been exceeded. The ECS value of 2.7°C is set at the maximum value, given the assumptions. But ceteris paribus, this will not hold if

  • One waits 3 years and CO2 levels continue increasing at a rate of the last few years.
  • ECS is slightly higher but still well within the accepted range of estimates. Indeed if ECS = 3.0, as in AR5 and AR4 in 2007, then 1.5C of warming was exceeded 5 years ago.
  • The impact of all GHGs together is slightly more than the offsetting impacts of other aerosols.
  • 0.06°C, or more, of the observed rise on temperature since 1850 is not due to GHG emissions.

Then there is the Transient Climate Response (TCR) which appears to be little more than taking the historical temperature change, assuming all of is down to human GHG emissions, and calculating a figure. Including rises in CO2 a century or more ago is hardly transient.

Based on my calculations, the results are highly contrived. They appear as a very fine balance between getting the maximum values for human-caused warming possible and not admitting that 1.5°C or even 2°C is already passed. There is a huge combination of empirical assumptions that are as equally valid as the ones used in the SR1.5 that go one way or the other. Rather than being a robust case, empirically it is highly improbable one.

Finally there is a conundrum here. I have calculated that if ECS = 2.7 and the starting level of CO2 is 280 ppm, then in round numbers, 1.5°C of warming results from CO2 levels of 412 ppm and 2.0°C of warming results from CO2 levels of 468 ppm. With CO2 levels in September 2018 at 406 ppm for 2.0°C of warming requires a rise in CO2 ten times greater than for 1.5°C of warming. So how can the IPCC claim that it is only about twice the amount of emissions? In my previous post I could not find an explanation, even though the emissions numbers reconciled with both past data and future emissions to generate 2.0°C of warming given certain assumptions. In the next I hope to provide an answer, which fits the figures quite closely, but looks pretty embarrassing.

Kevin Marshall

Why can’t I reconcile the emissions to achieve 1.5C or 2C of Warming?

Introduction

At heart I am beancounter. That is when presented with figures I like to understand how they are derived. When it comes to the claims about the quantity of GHG emissions that are required to exceed 2°C of warming I cannot get even close, unless by making some a series of  assumptions, some of which are far from being robust. Applying the same set of assumptions I cannot derive emissions consistent with restraining warming to 1.5°C

Further the combined impact of all the assumptions is to create a storyline that appears to me only as empirically as valid as an infinite number of other storylines. This includes a large number of plausible scenarios where much greater emissions can be emitted before 2°C of warming is reached, or where (based on alternative assumptions) plausible scenarios even 2°C of irreversible warming is already in the pipeline.  

Maybe an expert climate scientist will clearly show the errors of this climate sceptic, and use it as a means to convince the doubters of climate science.

What I will attempt here is something extremely unconventional in the world of climate. That is I will try to state all the assumptions made by highlighting them clearly. Further, I will show my calculations and give clear references, so that anyone can easily follow the arguments.

Note – this is a long post. The key points are contained in the Conclusions.

The aim of constraining warming to 1.5 or 2°C

The Paris Climate Agreement was brought about by the UNFCCC. On their website they state.

The Paris Agreement central aim is to strengthen the global response to the threat of climate change by keeping a global temperature rise this century well below 2 degrees Celsius above pre-industrial levels and to pursue efforts to limit the temperature increase even further to 1.5 degrees Celsius. 

The Paris Agreement states in Article 2

1. This Agreement, in enhancing the implementation of the Convention, including its objective, aims to strengthen the global response to the threat of climate change, in the context of sustainable development and efforts to eradicate
poverty, including by:

(a) Holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels, recognizing that this would significantly reduce the risks and impacts of climate change;

Translating this aim into mitigation policy requires quantification of global emissions targets. The UNEP Emissions Gap Report 2017 has a graphic showing estimates of emissions before 1.5°C or 2°C warming levels is breached.

Figure 1 : Figure 3.1 from the UNEP Emissions Gap Report 2017

The emissions are of all greenhouse gas emissions, expressed in billions of tonnes of CO2 equivalents. From 2010, the quantity of emissions before the either 1.5°C or 2°C is breached are respectively about 600 GtCO2e and 1000 GtCO2e. It is these two figures that I cannot reconcile when using the same  assumptions to calculate both figures. My failure to reconcile is not just a minor difference. Rather, on the same assumptions that 1000 GtCO2e can be emitted before 2°C is breached, 1.5°C is already in the pipeline. In establishing the problems I encounter I will clearly endeavor to clearly state the assumptions made and look at a number of examples.

 Initial assumptions

1 A doubling of CO2 will eventually lead to 3°C of rise in global average temperatures.

This despite the 2013 AR5 WG1 SPM stating on page 16

Equilibrium climate sensitivity is likely in the range 1.5°C to 4.5°C

And stating in a footnote on the same page.

No best estimate for equilibrium climate sensitivity can now be given because of a lack of agreement on values across assessed lines of evidence and studies.

2 Achieving full equilibrium climate sensitivity (ECS) takes many decades.

This implies that at any point in the last few years, or any year in the future there will be warming in progress (WIP).

3 Including other greenhouse gases adds to warming impact of CO2.

Empirically, the IPCC’s Fifth Assessment Report based its calculations on 2010 when CO2 levels were 390 ppm. The AR5 WG3 SPM states in the last sentence on page 8

For comparison, the CO2-eq concentration in 2011 is estimated to be 430 ppm (uncertainty range 340 to 520 ppm)

As with climate sensitivity, the assumption is the middle of an estimated range. In this case over one fifth of the range has the full impact of GHGs being less than the impact of CO2 on its own.

4 All the rise in global average temperature since the 1800s is due to rise in GHGs. 

5 An increase in GHG levels will eventually lead to warming unless action is taken to remove those GHGs from the atmosphere, generating negative emissions. 

These are restrictive assumptions made for ease of calculations.

Some calculations

First a calculation to derive the CO2 levels commensurate with 2°C of warming. I urge readers to replicate these for themselves.
From a Skeptical Science post by Dana1981 (Dana Nuccitelli) “Pre-1940 Warming Causes and Logic” I obtained a simple equation for a change in average temperature T for a given change in CO2 levels.

ΔTCO2 = λ x 5.35 x ln(B/A)
Where A = CO2 level in year A (expressed in parts per million), and B = CO2 level in year B.
I use λ = .809, so that if B = 2A, ΔTCO2 = 3.00

Pre-industrial CO2 levels were 280ppm. 3°C of warming is generated by CO2 levels of 560 ppm, and 2°C of warming is when CO2 levels reach 444 ppm.

From the Mauna Loa CO2 data, average CO2 levels averaged 407 ppm in 2017. Given the assumption (3) and further assuming the impact of other GHGs is unchanged, 2°C of warming would have been surpassed in around 2016 when CO2 levels averaged 404 ppm. The actual rise in global average temperatures is from HADCRUT4 is about half that amount, hence the assumption that the impact of a rise in CO2 takes an inordinately long time for the actual warming to reveal itself. Even with the assumption that 100% of the warming since around 1800 is due to the increase in GHG levels warming in progress (WIP) is about the same as revealed warming. Yet the Sks article argues that some of the early twentieth century warming was due to other than the rise in GHG levels.

This is the crux of the reconciliation problem. From this initial calculation and based on the assumptions, the 2°C warming threshold has recently been breached, and by the same assumptions 1.5°C was likely breached in the 1990s. There are a lot of assumptions here, so I could have missed something or made an error. Below I go into some key examples that verify this initial conclusion. Then I look at how, by introducing a new assumption it is claimed that 2°C warming is not yet reached.

100 Months and Counting Campaign 2008

Trust, yet verify has a post We are Doomed!

This tracks through the Wayback Machine to look at the now defunct 100monthsandcounting.org campaign, sponsored by the left-wing New Economics Foundation. The archived “Technical Note” states that the 100 months was from August 2008, making the end date November 2016. The choice of 100 months turns out to be spot-on with the actual data for CO2 levels; the central estimate of the CO2 equivalent of all GHG emissions by the IPCC in 2014 based on 2010 GHG levels (and assuming other GHGs are not impacted); and the central estimate for Equilibrium Climate Sensitivity (ECS) used by the IPCC. That is, take 430 ppm CO2e, and at 14 ppm for 2°C of warming.
Maybe that was just a fluke or they were they giving a completely misleading forecast? The 100 Months and Counting Campaign was definitely not agreeing with the UNEP Emissions GAP Report 2017 in making the claim. But were they correctly interpreting what the climate consensus was saying at the time?

The 2006 Stern Review

The “Stern Review: The Economics of Climate Change” (archived access here) that was commissioned to provide benefit-cost justification for what became the Climate Change Act 2008. From the Summary of Conclusions

The costs of stabilising the climate are significant but manageable; delay would be dangerous and much more costly.

The risks of the worst impacts of climate change can be substantially reduced if greenhouse gas levels in the atmosphere can be stabilised between 450 and 550ppm CO2 equivalent (CO2e). The current level is 430ppm CO2e today, and it is rising at more than 2ppm each year. Stabilisation in this range would require emissions to be at least 25% below current levels by 2050, and perhaps much more.

Ultimately, stabilisation – at whatever level – requires that annual emissions be brought down to more than 80% below current levels. This is a major challenge, but sustained long-term action can achieve it at costs that are low in comparison to the risks of inaction. Central estimates of the annual costs of achieving stabilisation between 500 and 550ppm CO2e are around 1% of global GDP, if we start to take strong action now.

If we take assumption 1 that a doubling of CO2 levels will eventually lead to 3.0°C of warming and from a base CO2 level of 280ppm, then the Stern Review is saying that the worst impacts can be avoided if temperature rise is constrained to 2.1 – 2.9°C, but only in the range of 2.5 to 2.9°C does the mitigation cost estimate of 1% of GDP apply in 2006. It is not difficult to see why constraining warming to 2°C or lower would not be net beneficial. With GHG levels already at 430ppm CO2e, and CO2 levels rising at over 2ppm per annum, the 2°C of warming level of 444ppm (or the rounded 450ppm) would have been exceeded well before any global reductions could be achieved.

There is a curiosity in the figures. When the Stern Review was published in 2006 estimated GHG levels were 430ppm CO2e, as against CO2 levels for 2006 of 382ppm. The IPCC AR5 states

For comparison, the CO2-eq concentration in 2011 is estimated to be 430 ppm (uncertainty range 340 to 520 ppm)

In 2011, when CO2 levels averaged 10ppm higher than in 2006 at 392ppm, estimated GHG levels were the same. This is a good example of why one should take note of uncertainty ranges.

IPCC AR4 Report Synthesis Report Table 5.1

A year before the 100 Months and Counting campaign The IPCC produced its Fourth Climate Synthesis Report. The 2007 Synthesis Report on Page 67 (pdf) there is table 5.1 of emissions scenarios.

Figure 2 : Table 5.1. IPCC AR4 Synthesis Report Page 67 – Without Footnotes

I inputted the various CO2-eq concentrations into my amended version of Dana Nuccitelli’s magic equation and compared to the calculation warming in Table 5.1

Figure 3 : Magic Equation calculations of warming compared to Table 5.1. IPCC AR4 Synthesis Report

My calculations of warming are the same as that of the IPCC to one decimal place except for the last two calculations. Why are there these rounding differences? From a little fiddling in Excel, it would appear to me that the IPCC got the warming results from a doubling of 3 when calculating to two decimal places, whilst my version of the formula is to four decimal places.

Note the following

  • That other GHGs are translatable into CO2 equivalents. Once translated other GHGs they can be treated as if they were CO2.
  • There is no time period in this table. The 100 Months and Counting Campaign merely punched in existing numbers and made a forecast ahead of the GHG levels that would reach the 2°C of warming.
  • No mention of a 1.5°C warming scenario. If constraining warming to 1.5°C did not seem credible in 2007, which should it be credible in 2014 or 2017, when CO2 levels are higher?

IPCC AR5 Report Highest Level Summary

I believe that the underlying estimates of emissions to achieve the 1.5°C or 2°C  of warming used by the UNFCCC and UNEP come from the UNIPCC Fifth Climate Assessment Report (AR5), published in 2013/4. At this stage I introduce an couple of empirical assumptions from IPCC AR5.

6 Cut-off year for historical data is 2010 when CO2 levels were 390 ppm (compared to 280 ppm in pre-industrial times) and global average temperatures were about 0.8°C above pre-industrial times.

Using the magic equation above, and the 390 ppm CO2 levels, there is around 1.4°C of warming due from CO2. Given 0.8°C of revealed warming to 2010, the residual “warming-in-progress” was 0.6°C.

The highest level of summary in AR5 is a Presentation to summarize the central findings of the Summary for Policymakers of the Synthesis Report, which in turn brings together the three Working Group Assessment Reports. This Presentation can be found at the bottom right of the IPCC AR5 Synthesis Report webpage. Slide 33 of 35 (reproduced below as Figure 4) gives the key policy point. 1000 GtCO2 of emissions from 2011 onwards will lead to 2°C. This is very approximate but concurs with the UNEP emissions gap report.

Figure 4 : Slide 33 of 35 of the AR5 Synthesis Report Presentation.

Now for some calculations.

1900 GtCO2 raised CO2 levels by 110 ppm (390-110). 1 ppm = 17.3 GtCO2

1000 GtCO2 will raise CO2 levels by 60 ppm (450-390).  1 ppm = 16.7 GtCO2

Given the obvious roundings of the emissions figures, the numbers fall out quite nicely.

Last year I divided CDIAC CO2 emissions (from the Global Carbon Project) by Mauna Loa CO2 annual mean growth rates (data) to produce the following.

Figure 5 : CDIAC CO2 emissions estimates (multiplied by 3.664 to convert from carbon units to CO2 units) divided by Mauna Loa CO2 annual mean growth rates in ppm.

17GtCO2 for a 1ppm rise is about right for the last 50 years.

To raise CO2 levels from 390 to 450 ppm needs about 17 x (450-390) = 1020 GtCO2. Slide 33 is a good approximation of the CO2 emissions to raise CO2 levels by 60 ppm.

But there are issues

  • If ECS = 3.00, and 17 GtCO2 of emissions to raise CO2 levels by 1 ppm, then it is only 918 (17*54) GtCO2 to achieve 2°C of warming. Alternatively, in future if there are assume 1000 GtCO2 to achieve 2°C  of warming it will take 18.5 GtCO2 to raise CO2 levels by 1 ppm, as against 17 GtCO2 in the past. It is only by using 450 ppm as commensurate with 2°C of warming that past and future stacks up.
  • If ECS = 3,  from CO2 alone 1.5°C would be achieved at 396 ppm or a further 100 GtCO2 of emissions. This CO2 level was passed in 2013 or 2014.
  • The calculation falls apart if other GHGs are included.  Emissions are assumed equivalent to 430 ppm at 2011. Therefore with all GHGs considered the 2°C warming would be achieved with 238 GtCO2e of emissions ((444-430)*17) and the 1.5°C of warming was likely passed in the 1990s.
  • If actual warming since pre-industrial times to 2010 was 0.8°C, ECS = 3, and the rise in all GHG levels was equivalent to a rise in CO2 from 280 to 430 ppm, then the residual “warming-in-progress” (WIP) was just over 1°C. That it is the WIP exceeds the total revealed warming in well over a century. If there is a short-term temperature response is half or more of the value of full ECS, it would imply even the nineteenth century emissions are yet to have the full impact on global average temperatures.

What justification is there for effectively disregarding the impact of other greenhouse emissions when it was not done previously?

This offset is to be found in section C – The Drivers of Climate Change – in AR5 WG1 SPM . In particular the breakdown, with uncertainties, in table SPM.5. Another story is how AR5 reached the very same conclusion as AR4 WG1 SPM page 4 on the impact of negative anthropogenic forcings but with a different methodology, hugely different estimates of aerosols along with very different uncertainty bands. Further, these historical estimates are only for the period 1951-2010, whilst the starting date for 1.5°C or 2°C is 1850.

From this a further assumption is made when considering AR5.

7 The estimated historical impact of other GHG emissions (Methane, Nitrous Oxide…) has been effectively offset by the cooling impacts of aerosols and precusors. It is assumed that this will carry forward into the future.

UNEP Emissions Gap Report 2014

Figure 1 above is figure 3.1 from the UNEP Emissions GAP Report 2017. The equivalent report from 2014 puts this 1000 GtCO2 of emissions in a clearer context. First a quotation with two accompanying footnotes.

As noted by the IPCC, scientists have determined that an increase in global temperature is proportional to the build-up of long-lasting greenhouse gases in the atmosphere, especially carbon dioxide. Based on this finding, they have estimated the maximum amount of carbon dioxide that could be emitted over time to the atmosphere and still stay within the 2 °C limit. This is called the carbon dioxide emissions budget because, if the world stays within this budget, it should be possible to stay within the 2 °C global warming limit. In the hypothetical case that carbon dioxide was the only human-made greenhouse gas, the IPCC estimated a total carbon dioxide budget of about 3 670 gigatonnes of carbon dioxide (Gt CO2 ) for a likely chance3 of staying within the 2 °C limit . Since emissions began rapidly growing in the late 19th century, the world has already emitted around 1 900 Gt CO2 and so has used up a large part of this budget. Moreover, human activities also result in emissions of a variety of other substances that have an impact on global warming and these substances also reduce the total available budget to about 2 900 Gt CO2 . This leaves less than about 1 000 Gt CO2 to “spend” in the future4 .

3 A likely chance denotes a greater than 66 per cent chance, as specified by the IPCC.

4 The Working Group III contribution to the IPCC AR5 reports that scenarios in its category which is consistent with limiting warming to below 2 °C have carbon dioxide budgets between 2011 and 2100 of about 630-1 180 GtCO2

The numbers do not fit, unless the impact of other GHGs are ignored. As found from slide 33, there is 2900 GtCO2 to raise atmospheric CO2 levels by 170 ppm, of which 1900 GtC02 has been emitted already. The additional marginal impact of other historical greenhouse gases of 770 GtCO2 is ignored. If those GHG emissions were part of historical emissions as the statement implies, then that marginal impact would be equivalent to an additional 45 ppm (770/17) on top of the 390 ppm CO2 level. That is not far off the IPCC estimated CO2-eq concentration in 2011 of 430 ppm (uncertainty range 340 to 520 ppm). But by the same measure 3670 GTCO2e would increase CO2 levels by 216 ppm (3670/17) from 280 to 496 ppm. With ECS = 3, this would eventually lead to a temperature increase of almost 2.5°C.

Figure 1 above is figure 3.1 from the UNEP Emissions GAP Report 2017. The equivalent report from the 2014 report ES.1

Figure 6 : From the UNEP Emissions Gap Report 2014 showing two emissions pathways to constrain warming to 2°C by 2100.

Note that this graphic goes through to 2100; only uses the CO2 emissions; does not have quantities; and only looks at constraining temperatures to 2°C.  To achieve the target requires a period of negative emissions at the end of the century.

A new assumption is thus required to achieve emissions targets.

8 Sufficient to achieve the 1.5°C or 2°C warming targets likely requires many years of net negative emissions at the end of the century.

A Lower Level Perspective from AR5

A simple pie chart does not seem to make sense. Maybe my conclusions are contradicted by the more detailed scenarios? The next level of detail is to be found in table SPM.1 on page 22 of the AR5 Synthesis Report – Summary for Policymakers.

Figure 7 : Table SPM.1 on Page 22 of AR5 Synthesis Report SPM, without notes. Also found as Table 3.1 on Page 83 of AR5 Synthesis Report 

The comment for <430 ppm (the level of 2010) is "Only a limited number of individual model studies have explored levels below 430 ppm CO2-eq. ” Footnote j reads

In these scenarios, global CO2-eq emissions in 2050 are between 70 to 95% below 2010 emissions, and they are between 110 to 120% below 2010 emissions in 2100.

That is, net global emissions are negative in 2100. Not something mentioned in the Paris Agreement, which only has pledges through to 2030. It is consistent with the UNEP Emissions GAP report 2014 Table ES.1. The statement does not refer to a particular level below 430 ppm CO2-eq, which equates to 1.86°C. So how is 1.5°C of warming not impossible without massive negative emissions? In over 600 words of notes there is no indication. For that you need to go to the footnotes to the far more detailed Table 6.3 AR5 WG3 Chapter 6 (Assessing Transformation Pathways – pdf) Page 431. Footnote 7 (Bold mine)

Temperature change is reported for the year 2100, which is not directly comparable to the equilibrium warming reported in WGIII AR4 (see Table 3.5; see also Section 6.3.2). For the 2100 temperature estimates, the transient climate response (TCR) is the most relevant system property.  The assumed 90% range of the TCR for MAGICC is 1.2–2.6 °C (median 1.8 °C). This compares to the 90% range of TCR between 1.2–2.4 °C for CMIP5 (WGI Section 9.7) and an assessed likely range of 1–2.5 °C from multiple lines of evidence reported in the WGI AR5 (Box 12.2 in Section 12.5).

The major reason that 1.5°C of warming is not impossible (but still more unlikely than likely) for CO2 equivalent levels that should produce 2°C+ of warming being around for decades is because the full warming impact takes so long to filter through.  Further, Table 6.3 puts Peak CO2-eq levels for 1.5-1.7°C scenarios at 465-530 ppm, or eventual warming of 2.2 to 2.8°C. Climate WIP is the difference. But in 2018 WIP might be larger than all the revealed warming in since 1870, and certainly since the mid-1970s.

Within AR5 when talking about constraining warming to 1.5°C or 2.0°C it is only the warming which is estimated to be revealed in 2100. There is no indication of how much warming in progress (WIP) there is in 2100 under the various scenarios, therefore I cannot reconcile back the figures. However, for GHG  would appear that the 1.5°C figure relies upon a period of over 100 years for impact of GHGs on warming failing to come through as (even netting off other GHGs with the negative impact of aerosols) by 2100 CO2 levels would have been above 400 ppm for over 85 years, and for most of those significantly above that level.

Conclusions

The original aim of this post was to reconcile the emissions sufficient to prevent 1.5°C or 2°C of warming being exceeded through some calculations based on a series of restrictive assumptions.

  • ECS = 3.0°C, despite the IPCC being a best estimate across different studies. The range is 1.5°C to 4.5°C.
  • All the temperature rise since the 1800s is assumed due to rises in GHGs. There is evidence that this might not be the case.
  • Other GHGs are netted off against aerosols and precursors. Given that “CO2-eq concentration in 2011 is estimated to be 430 ppm (uncertainty range 340 to 520 ppm)” when CO2 levels were around 390 ppm, this assumption is far from robust.
  • Achieving full equilibrium takes many decades. So long in fact that the warming-in-progress (WIP) may currently exceed all the revealed warming in over 150 years, even based on the assumption that all of that revealed historical warming is due to rises in GHG levels.

Even with these assumptions, keeping warming within 1.5°C or 2°C seems to require two assumptions that were not recognized a few years ago. First is to assume net negative global emissions for many years at the end of the century. Second is to talk about projected warming in 2100 rather than warming as a resultant on achieving full ECS.

The whole exercise appears to rest upon a pile of assumptions. Amending the assumptions means one way means admitting that 1.5°C or 2°C of warming is already in the pipeline, or the other way means admitting climate sensitivity is much lower. Yet there appears to be a very large range of empirical assumptions to chose from there could be there are a very large number of scenarios that are as equally valid as the ones used in the UNEP Emissions Gap Report 2017.

Kevin Marshall

Increasing Extreme Weather Events?

Over at Cliscep, Ben Pile posted Misleading Figures Behind the New Climate Economy. Ben looked at the figures behind the recent New Climate Economy Report from the Global Commission on the Economy and Climate, which claims to be

… a major international initiative to examine how countries can achieve economic growth while dealing with the risks posed by climate change. The Commission comprises former heads of government and finance ministers and leaders in the fields of economics and business, and was commissioned by seven countries – Colombia, Ethiopia, Indonesia, Norway, South Korea, Sweden and the United Kingdom – as an independent initiative to report to the international community.

In this post I will briefly look at Figure 1 from the report, re-posted by Ben Pile.

Fig 1 – Global Occurrences of Extreme Weather Events from New Economy Climate Report

Clearly these graphs seem to demonstrate a rapidly worsening situation. However, I am also aware of a report a few years ago authored by Indur Goklany, and published by The Global Warming Policy Foundation  – GLOBAL DEATH TOLL FROM EXTREME WEATHER EVENTS DECLINING

Figure 2 : From Goklany 2010 – Global Death and Death Rates Due to Extreme Weather Events, 1900–2008. Source: Goklany (2009), based on EM-DAT (2009), McEvedy and Jones (1978), and WRI (2009).

 

Note that The International Disaster Database is EM-DAT. The website is here to check. Clearly these show two very different pictures of events. The climate consensus (or climate alarmist) position is that climate change is getting much worse. The climate sceptic (or climate denier) position is that is that human-caused climate change is somewhat exaggerated. Is one side outright lying, or is their some truth in both sides?

Indur Goklany recognizes the issue in his report. His Figure 2, I reproduce as figure 3.

Figure 3: Average Number of Extreme Weather Events per Year by Decade, 1900–2008.  Source: Goklany (2009), based on EM-DAT (2009).

I am from a management accounting background. That means that I check my figures. This evening I registered at the EM-DAT website and downloaded the figures to verify the data. The website looks at all sorts of disaster information, not just climate information. It collates

Figure 4 : No of Climatic Occurrences per decade from EM-DAT. Note that 2010-2016 pro rata is similar to 2000-2009

The updated figures through to 2016 show that pro rata, in the current decade occurrences if climate-related events as similar to the last decade. If one is concerned about the human impacts, deaths are more relevant.

Figure 5 : No of Climatic Deaths per decade from EM-DAT. Note that 2010-2016 pro rata is similar to 2000-2009

This shows unprecedented flood deaths in the 1930s. Of the 163218 flood deaths in 6 occurrences, 142000 were due to a flood in China in 1935. Wikipedia’s Ten deadliest natural disasters since 1900 lists at No.8 1935 Yangtze river flood, with 145000 dead. At No.1 is 1931 China floods with 1-4 million deaths. EM-DAT has not registered this disaster.

The decade 1970-1979 was extreme for deaths from storms. 300000 deaths were due to a Bangladesh storm in 1970. Wikipedia’s Ten deadliest natural disasters since 1900 lists at No.2 1970 Bhola cyclone, with ≥500,000.

The decade 1990-1999 had a high flood death toll. Bangladesh 1991 stands out with 138987 dead. Wikipedia No.10 is 1991 Bangladesh cyclone with 138866 dead.

In the decade 2000-2009 EM-DAT records the Myanmar Storm of 2008 with 138366 dead. If Wikipedia had a top 11 deadliest natural disasters since 1900, then Cyclone Nargis of 2 May 2008 could have made the list. From the BBC, with 200000 estimated dead, it would have qualified. But from the Red Cross 84500 Cyclone Nargis may have not made the top 20.

This leaves a clear issue of data. The International Disaster Database will accept occurrences of disasters according to clear criteria. For the past 20-30 years disasters have been clearly recorded. The build-up of a tropical cylone / hurricane is monitored by satellites and film crews are on hand to televise across the world pictures of damaged buildings, dead bodies, and victims lamenting the loss of homes. As I write Hurricane Florence is about to pound the Carolinas, and evacuations have been ordered. The Bhola Cyclone of 1970 was no doubt more ferocious and impacted on a far greater number of people. But the primary reason for the extreme deaths in 1970 Bangladesh was lack of warning and a lack of evacuation places. Even in the Wizard of Oz, based on 1930s United States, in a Tornado most families had a storm cellar. In the extreme poverty of 1970 Bangladesh there was nothing. Now, after decades of moderate growth and some rudimentary warning systems, it is unlikely that a similar storm would cause even a tenth of the death toll.

Even more significant, is that even if (as I hope) Hurricane Florence causes no deaths and limited property damage, it will be sufficiently documented to qualify for an entry on the International Disaster Database. But the quality of evidence for the 1931 China Floods, occurring in a civil war between the Communists and the Kuomintang forces, would be insufficient to qualify for entry. This is why one must be circumspect in interpreting this sort of data over periods when the quality and availability of data varies significantly. The issue I have is not with EM-DAT, but those who misinterpret the data for an ideological purpose.

Kevin Marshall