Plan B Environmental Activists deservedly lose High Court battle over Carbon Target

Breaking News

From Belfast Telegraph & itv.com and Science Matters (my bold)

Lawyers for the charity previously argued the Government should have, in light of the current scientific consensus, gone further than its original target of reducing carbon levels by 2050 to 80% of those present in 1990.

They said the decision not to amend the 2050 target put the UK in breach of its international obligations under the Paris Agreement on Climate Change and was influenced by the Government’s belief that a “more ambitious target was not feasible”.

At a hearing on July 4, Jonathan Crow QC told the court: “The Secretary of State’s belief that he needs to have regard to what is feasible, rather than what is necessary, betrays a fundamental misunderstanding of the scheme of the 2008 Act and must be quashed.

“All of the individual claimants are deeply concerned about climate change.”

The barrister argued the Secretary of State’s “continuing refusal” to amend the 2050 target means the UK is playing “Russian roulette with two bullets, instead of one”.

But, refusing permission for a full hearing, Mr Justice Supperstone said Plan B Earth’s arguments were based on an “incorrect interpretation” of the Paris Agreement.

He said: “In my view the Secretary of State was plainly entitled … to refuse to change the 2050 target at the present time.

In a previous post I wrote that

Taking court action to compel Governments to enforce the Paris Climate Agreement is against the real spirit of that Agreement. Controlling global GHG emissions consistent with 2°C, or 1.5°C is only an aspiration, made unachievable by allowing developing countries to decide for themselves when to start reducing their emissions. ……. Governments wanting to both be players on the world stage and serve their countries give the appearance of taking action of controlling emissions, whilst in substance doing very little. This is the real spirit of the Paris Climate Agreement. To take court action to compel a change of policy action in the name of that Agreement should be struck off on that basis.

Now I would not claim Mr Justice Supperstone supports my particular interpretation of the Paris Agreement as an exercise in political maneuvering allowing Governments to appear to be one thing, whilst doing another. But we are both agreed that “Plan B Earth’s arguments were based on an “incorrect interpretation” of the Paris Agreement.

The UNFCCC PDF of the Paris Agreement is here to check. Then check against my previous post, which argues that if the Government acted in the true spirit of the Paris Agreement, it would suspend the costly Climate Change Act 2008 and put efforts into being seen to be doing something about climate change. Why

  • China was praised for joining the emissions party by proposing to stop increasing emissions by 2030.
  • Very few of the INDC emissions will make real large cuts in emissions.
  • The aggregate forecast impact of all the INDC submissions, if fully enacted, will see global  emissions slightly higher than today in 2030, when according to the UNEP emissions GAP report 2017 for 1.5°C warming target they need to be 30% lower in just 12 years time. Paris Agreement Article 4.1 states something that is empirically incompatible with that aim.

In order to achieve the long-term temperature goal set out in Article 2, Parties aim to reach global peaking of greenhouse gas emissions as soon as possible, recognizing that peaking will take longer for developing country Parties,

  • The Paris Agreement allows “developing” countries to keep on increasing their emissions. With about two-thirds of global emissions (and over 80% of the global population), 30% emissions cuts may not be achieved even if all the developed countries cut emissions to zero in 12 years.
  • Nowhere does the Paris Agreement recognize the many countries who rely on fossil fuels for a large part of their national income, for instance in the Middle East and Russia. Cutting emissions to near zero by mid-century would impoverish them within a generation. Yet, with the developing countries also relying on cheap fossil fuels to promote high levels of economic growth for political stability and to meeting the expectations of their people (e.g. Pakistan, Indonesia, India, Turkey) most of the world can carry on for decades whilst some enlightened Governments in the West damage the economic futures of their countries for appearances sake. Activists trying to dictate Government policy through the Courts in a supposedly democratic country ain’t going to change their minds.

Plan B have responded to the judgement. I find this statement interesting.

Tim Crosland, Director of Plan B and former government lawyer, said: ‘We are surprised and disappointed by this ruling and will be lodging an appeal.

‘We consider it clear and widely accepted that the current carbon target is not compatible with the Paris Agreement. Neither the government nor the Committee on Climate Change suggested during our correspondence with them prior to the claim that the target was compatible.

Indeed, it was only in January of this year that the Committee published a report accepting that the Paris Agreement was ‘likely to require’ a more ambitious 2050 target

What I find interesting is that only point that a lawyer has for contradicting Mr Justice Supperstone’s statement that “Plan B Earth’s arguments were based on an “incorrect interpretation” of the Paris Agreement” is with reference to a report by the Committee on Climate Change. From the CCC website

The Committee on Climate Change (the CCC) is an independent, statutory body established under the Climate Change Act 2008.

Our purpose is to advise the UK Government and Devolved Administrations on emissions targets and report to Parliament on progress made in reducing greenhouse gas emissions and preparing for climate change.

The Committee is set up for partisan aims and, from its’s latest report, appears to be quite zealous in fulfilling those aims. Even as a secondary source (to a document which is easy to read) it should be tainted. But, I would suggest that to really understand the aims of the Paris Agreement you need to read the original and put it in the context of the global empirical and political realities. From my experience, the climate enlightened will keep on arguing for ever, and get pretty affronted when anyone tries to confront their blinkered perspectives.

Kevin Marshall

Why Plan B’s Climate Court Action should be dismissed

Summary

Taking court action to compel Governments to enforce the Paris Climate Agreement is against the real spirit of that Agreement. Controlling global GHG emissions consistent with 2°C, or 1.5°C is only an aspiration, made unachievable by allowing developing countries to decide for themselves when to start reducing their emissions. In the foreseeable future, the aggregate impact of emissions reduction policies will fail to even reduce global emissions. Therefore, costly emissions reductions policies will always end up being net harmful to the countries where they are imposed. Governments wanting to both be players on the world stage and serve their countries give the appearance of taking action of controlling emissions, whilst in substance doing very little. This is the real spirit of the Paris Climate Agreement. To take court action to compel a change of policy action in the name of that Agreement should be struck off on that basis. I use activist group Plan B’s case before the British Court to get the British Government to make even deeper emissions cuts than those under the Climate Change Act 2008.

Plan B’s Case at the High court

Last week BBC’s environment analyst Roger Harrabin reported Court action to save young from climate bill.

The campaigners – known collectively as Plan B – argue that if the UK postpones emissions cuts, the next generation will be left to pick up the bill.

It is seeking permission from a judge to launch formal legal action.

The government has promised to review its climate commitments.

A spokesperson said it was committed to tackling emissions.

But Plan B believes ministers may breach the law if they don’t cut emissions deeper – in line with an international agreement made in Paris at the end of 2015 to restrict global temperature rise to as close to 1.5C as possible.

From an obscure website crowdjustice

Plan B claim that the government is discriminating against the young by failing to cut emissions fast enough. During the hearing, they argued that the UK government’s current target of limiting global temperature rises to 2°C was not ambitious enough, and that the target ought to be lowered to 1.5°C, in line with the Paris Agreement that the UK ratified in 2015. Justice Supperstone postponed the decision until a later date.

Plan B on their own website state

Plan B is supporting the growing global movement of climate litigation, holding governments and corporations to account for climate harms, fighting for the future for all people, all animals and all life on earth.

What is the basis of discrimination?

The widely-accepted hypothesis is that unless global greenhouse gas (GHG) emissions are reduced to near zero in little more than a generation, global average temperature rise will rise more than 2°C above pre-industrial levels. A further hypothesis is that this in turn will cause catastrophic climate change. Consequent on both hypotheses being true gives the case for policy action. Therefore, failure to reduce global GHG emissions will imperil the young.

A further conjecture is that if all signatories to the Paris Agreement fulfil their commitments it is sufficient to prevent 1.5°C or 2°C of warming. There are a number of documents to consider.

First is the INDC submissions (i.e. Nation States communications of their intended nationally determined contributions), collected together at the UNFCCC website. Most are in English.  To find a country submission I suggest clicking on the relevant letter of the alphabet.

Second, to prevent my readers being send on a wild goose chase through small country submissions, some perspective is needed on relative magnitude of emissions. A clear secondary source (but only based on CO2 emissions) BP Data Analysis Global CO2 Emissions 1965-2017. More data on GHG emissions are from the EU Commissions EDGAR Emissions data and the World Resources Institute CAIT Climate Data Explorer.

Third is the empirical scale of the policy issue. The UNEP emissions Gap Report 2017 (pdf), published in October last year is the latest attempt to estimate the scale of the policy issue. The key is the diagram reproduced below.

The total of all commitments will still see aggregate emissions rising into the future. That is, the aggregate impact of all the nationally determined contributions is to see emissions rising well into the future. So the response it to somehow persuade Nations States to change their vague commitments to such an extent that aggregate emissions pathways sufficient to prevent 1.5°C or 2°C of warming?

The relevant way to do this ought to be through the Paris Agreement.

Fourth is the Adoption Paris Agreement itself, as held on the UNFCCC website (pdf).

 

Paris Agreement key points

I would draw readers to Article 2.1(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;

Article 2.2

  • This Agreement will be implemented to reflect equity and the principle of common but differentiated responsibilities and respective capabilities, in the light of different national circumstances.

My interpretation is that, the cumulative aggregate reduction will be only achieved by if those countries hat, (in the light of their national circumstances), fail to follow the aggregate pathways, are offset by other countries cutting their emissions by a greater amount. It is a numbers game. It is not just a case of compelling some countries to meet the 1.5°C pathway but to compel them to exceed it by some margin.

I would also draw readers to Article 4.1

In order to achieve the long-term temperature goal set out in Article 2, Parties aim to reach global peaking of greenhouse gas emissions as soon as possible, recognizing that peaking will take longer for developing country Parties, and to undertake rapid reductions thereafter in accordance with best available science, so as to achieve a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century, on the basis of equity, and in the context of sustainable development and efforts to eradicate poverty.

My reading is that any country defined as “developing” has only an aim of reducing emissions after peaking of their emissions. When they choose to do so depends on a number of criteria. There is not clear mechanism for deciding this, and no surrender of decision-making by countries to external bodies.

Implications of the Paris Agreement

Many developing countries emissions are increasing their emissions. They agreement does not compel them to change course in the near future. Empirically that means to achieve the goals the aggregate emission reductions of countries reducing their emissions must be such that they cancel out the emissions increases in the developing countries. Using EDGAR figures for GHG emissions, and the Rio Declaration 1992 for developing countries (called Non-Annex countries) I estimate they accounted for 64% of global GHG emissions in 2012, the latest year available.

 

All other sources sum to 19 GtCO2e, the same as the emissions gap between the unconditional INDC case and the 1.5°C case. This presents a stark picture. Even if emissions from all other sources are eliminated by 2030, AND the developing countries do not increase their emissions to 2030, cumulative global emissions are very likely to exceed the 1.5°C and the 2°C warming targets unless the developing countries reduce their emissions rapidly after 2030. That is close down fairly new fossil fuel power stations; remove from the road millions of cars, lorries and buses; and reduce the aspirations of the emerging middle classes to improving life styles. The reality is quite the opposite. No new policies are on the horizon that would significantly reduce global GHG emissions, either from the developed countries in the next couple of years, or the developing countries to start in just over a decade from now. Reading the comments in the INDC emissions (e.g. Indonesia, Pakistan, India), a major reason is that these governments are not willing to sacrifice the futures of their young through risking economic growth and political stability to cut their emissions. So rather than Plan B take the UK Government  to a UK Court, they should be persuading those Governments who do not share their views (most of them) of the greater importance of their case. After all, unlike proper pollution (such as smoke), it does not matter where the emissions are generated in relation to the people affected.

It gets worse. It could be argued that the countries that most affected by mitigation policies are not the poorest seeing economic growth and political stability smashed. It is the fossil fuel dependent countries. McGlade and Ekins 2015 (The geographical distribution of fossil fuels unused when limiting global warming to 2°C) estimated, said to achieve even 2°C target 75% of proven reserves and 100% of new discoveries must be left in the ground. Using these global estimates and the BP estimated proven reserves of fossil fuels I created the following apportionment by major countries.

 

The United States has the greatest proven fossil fuel reserves in terms of potential emissions. But if one looks at fossil fuel revenues relative to GDP, it is well down the league table. To achieve emission targets countries such like Russia, Saudi Arabia, Kuwait, Turkmenistan, Iraq, and Iran must all be persuaded to shut down their down sales of fossil fuels long before the reserves are exhausted, or markets from developing countries dry up. To do this in a generation would decimate their economies. However, given the increase in fossil fuel usage from developing countries, and the failure of developed countries to significantly reduce emissions through policy this hardly seems a large risk.

However, this misses the point. The spirit of the Paris Agreement is not to cut emissions, but to be seen to be doing something about climate change. For instance, China were held up by the likes of President Obama for aiming to both top out its emissions by 2030, and reduce emissions per unit of GDP. The USA and the EU did this decades ago, so China’s commitments are little more than a Business-as-usual scenario. Many other countries emissions reduction “targets” are attainable without much actual policy. For example, Brazil’s commitment is to “reduce greenhouse gas emissions by 43% below 2005 levels in 2030.” It sounds impressive, until one reads this comment under “Fairness and Ambition

Brazil’s current actions in the global effort against climate change represent one of the largest undertakings by any single country to date, having reduced its emissions by 41% (GWP-100; IPCC SAR) in 2012 in relation to 2005 levels.

Brazil intends to reduce emissions by a further 2% compared to 2005 levels. Very few targets are more than soft targets relative to current or projected trends. Yet the outcome of COP21 Paris enabled headlines throughout the world to proclaim a deal had been reached “to limit global warming to “well below” 2C, aiming for 1.5C”. It enables most Governments to juggle being key players on a world stage, have alarmists congratulating them on doing their bit on saving the planet, whilst making sure that serving the real needs of their countries is not greatly impeded. It is mostly win-win as long as countries do not really believe that targets are achievable. This is where Britain has failed. Under Tony Blair, when the fever of climate alarmism at its height, backed up by the political spin of New Labour and a Conservative opposition wanting to ditch its unelectable image, Green activists wrote the Climate Change Act 2008 with the strict targets to be passed. Britain swallowed climate alarmism whole, and now as a country that keep its promises is implementing useless and costly policies. But they have kept some form of moderation in policies until now. This is illustrated by a graphic from a Committee on Climate Change report last week “Reducing UK emissions 2018 – Progress Report to Parliament” (pdf) (and referenced at cliscep)

Whilst emissions have come down in the power sector they are flat in transport, industry and in buildings. Pushing real and deep reductions in these sectors means for young people pushing up the costs of motoring (placing driving a car out of the reach of many), of industry (raising costs relative to the countries – especially the non-policy developing countries) and buildings in a country where planning laws make home-owning unaffordable for many and where costs of renting is very high. This on top of further savings in the power industry will be ever more costly as the law of diminishing returns sets in. Forcing more urgent policy actions will increase the financial and other burdens on the young people of today, but do virtually nothing to reach the climate aspirations of the Paris Agreement due to Britain now having less than 1% of global emissions. The Government could be forced out of political fudging to impose policies that will be net harmful to the young and future generations.

Plan B are using an extreme activist interpretation. As reported in Climate Home News after the postponement.

“The UK is not doing enough,” Tim Crosland, director of Plan B told Climate Home News. “The benchmark target is now out of place. We are arguing that it is a breach of human rights.”

The UK has committed to cut emissions by at least 80% of 1990 levels by 2050, with an aim to limit global temperature rise to 2C.

Under the 2008 Climate Change Act, the secretary can revise the target to reflect significant developments in climate change science or in international law or policy.

Plan B want to see the target lowered to be in line with 1.5C, the lower target of the Paris Agreement, which the UK ratified in 2016.

As stated, insofar as the Paris Climate Agreement is a major development of policy, it is one of appearing to do a lot whilst doing very little. By these terms, the stronger case is for repealing the Act, not strengthening its clauses. 

But what if I am wrong on this Paris Agreement being just an exercise in appearances? This then it should be recognized that developing countries will only start to reduce their emissions at some time in the future. By implication, for the world to meet the 1.5°C warming limit, developing countries should be pursuing and emissions reduction pathway much steeper than the 25% reduction between 2015 and 2030 implied in the Emissions GAP Report graphic. It should be at least 50% and nearer 100% in the next decade. Given that the Climate Change Act was brought in so that Britain could lead the world on climate change, Plan B should be looking for a 100% reduction by the end of the year. 

Kevin Marshall

 

Hansen et al 1988 Global Warming Predictions 30 Years on

Last month marked the 30th anniversary of the James Hansen’s Congressional Testimony that kicked off the attempts to control greenhouse gas emissions. The testimony was clearly an attempt, by linking human greenhouse emissions to dangerous global warming, to influence public policy. Unlike previous attempts (such as by then Senator Al Gore), Hansen’s testimony was hugely successful. But do the scientific projections that underpinned the testimony hold up against the actual data? The key part of that testimony was a graph from the Hansen et al 1988* Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model, produced below.


Figure 1: Hansen et al 1988 – Figure 3(a) in the Congressional Testimony

Note the language of the title of the paper. This is a forecast of global average temperatures contingent upon certain assumptions. The ambiguous part is the assumptions.

The assumptions of Hansen et. al 1988

From the paper.

4. RADIATIVE FORCING IN SCENARIOS A, B AND C

4.1. Trace Gases

  We define three trace gas scenarios to provide an indication of how the predicted climate trend depends upon trace gas growth rates. Scenarios A assumes that growth rates of trace gas emissions typical of the 1970s and 1980s will continue indefinitely; the assumed annual growth averages about 1.5% of current emissions, so the net greenhouse forcing increase exponentially. Scenario B has decreasing trace gas growth rates, such that the annual increase of the greenhouse climate forcing remains approximately constant at the present level. Scenario C drastically reduces trace gas growth between 1990 and 2000 such that the greenhouse climate forcing ceases to increase after 2000.

Scenario A is easy to replicate. Each year increase emissions by 1.5% on the previous year. Scenario B assumes that growth emissions are growing, and policy takes time to be enacted. To bring emissions down to the current level (in 1987 or 1988), reduction is required. Scenario C one presumes are such that trace gas levels are not increasing. As trace gas levels were increasing in 1988 and (from Scenario B) continuing emissions at the 1988 level would continue to increase atmospheric levels the levels of emissions would have been considerably lower than in 1988 by the year 2000. They might be above zero, as small amounts of emissions may not have an appreciable impact on atmospheric levels.

The graph formed Fig. 3. of James Hansen’s testimony to Congress. The caption to the graph repeats the assumptions.

Scenario A assumes continued growth rates of trace gas emissions typical of the past 20 years, i.e., about 1.5% yr-1 emission growth; scenario B has emission rates approximately fixed at current rates; scenario C drastically reduces traces gas emissions between 1990 and 2000.

This repeats the assumptions. Scenario B fixes annual emissions at the levels of the late 1980s, whilst scenario C sees drastic emission reductions.

James Hansen in his speech gave a more succinct description.

We have considered cases ranging from business as usual, which is scenario A, to draconian emission cuts, scenario C, which would totally eliminate net trace gas growth by year 2000.

Note that the resultant warming from fixing emissions at the current rate (Scenario B) is much closer in warming impacts to Scenario A (emissions growth of +1.5% year-on-year) than Scenario C that stops global warming. Yet Scenario B results from global policy being successfully implemented to stop the rise in global emissions.

Which Scenario most closely fits the Actual Data?

To understand which scenario most closely fits the data, we need to look at that trace gas emissions data. There are a number of sources, which give slightly different results. One source, and that which ought to be the most authoritative, is the IPCC Fifth Assessment Report WG3 Summary for Policy Makers graphic SPM.1 is reproduced in Figure 2.

 Figure 2 : AR5 WG3 SPM.1 Total annual anthropogenic GHG emissions (GtCO2eq/yr) by groups of gases 1970-2010. FOLU is Forestry and Other Land Use.

Note that in Figure 2 the other greenhouse gases – F-Gases, N2O and CH4 – are expressed in CO2 equivalents. It is very easy to see which of the three scenarios fits. The historical data up until 1988 shows increasing emissions. After that data emissions have continued to increase. Indeed there is some acceleration, stated on the graph comparing 2000-2010 (+2.2%/yr) with 1970-2000 (+1.3%/yr) . In 2010 GHG emissions were not similar to those in the 1980s (about 35 GtCO2e) but much higher. By implication, Scenario C, which assumed draconian emissions cuts is the furthest away from the reality of what has happened. Before considering how closely Scenario A compares to temperature rise, the question is therefore how close actual emissions have increased compared to the +1.5%/yr in scenario A.

From my own rough calculations, total GHG emissions from 1990 to 2010 rose about 29% or 1.3% a year, compared to 41% or 1.7% a year in the period 1970 to 1990. Exponential growth of 1.3% is not far short of the 1.5%. The assumed 1.5% growth rates would have resulted in 2010 emissions of 51 GtCO2e instead of the 49 GtCO2e estimated, well within the margin of error. That is actual trends over 20 years were pretty much the business as usual scenario. The narrower CO2 emissions from fossil fuels and industrial sources from 1990 to 2010 rose about 42% or 1.8% a year, compared to 51% or 2.0% a year in the period 1970 to 1990, above the Scenario A.

The breakdown is shown in Figure 3.

Figure 3 : Rough calculations of exponential emissions growth rates from AR5 WG1 SPM Figure SPM.1 

These figures are somewhat out of date. The UNEP Emissions Gap Report 2017 (pdf) estimated GHG emissions in 2016 at 51.9 GtCO2e. This represents a slowdown in emissions growth in recent years.

Figure 4 shows are the actual decadal exponential growth trends in estimated GHG emissions (with a linear trend to the 51.9 GtCO2e of emissions in 2016 from the UNEP Emissions Gap Report 2017 (pdf)) to my interpretations of the scenario assumptions. That is, from 1990 in Scenario A for 1.5% annual growth in emissions; in Scenario B for emissions to reduce from 38 to 35 GtCO2e in(level of 1987) in the 1990s and continue indefinitely: in Scenario C to reduce to 8 GtCO2e in the 1990s.

Figure 4 : Hansen et al 1988 emissions scenarios, starting in 1990, compared to actual trends from UNIPCC and UNEP data. Scenario A – 1.5% pa emissions growth; Scenario B – Linear decline in emissions from 38 GtCO2e in 1990 to 35 GtCO2e in 2000, constant thereafter; Scenario C – Linear decline  in emissions from 38 GtCO2e in 1990 to 8 GtCO2e in 2000, constant thereafter. 

This overstates the differences between A and B, as it is the cumulative emissions that matter. From my calculations, although in Scenario B 2010 emissions are 68% of Scenario A, cumulative emissions for period 1991-2010 are 80% of Scenario A.

Looking at cumulative emissions is consistent with the claims from the various UN bodies, that limiting to global temperature rise to 1.5°C or 2.0°C of warming relative to some point is contingent of a certain volume of emissions not been exceeded. One of the most recent the key graphic from the UNEP Emissions Gap Report 2017.

Figure 5 : Figure ES.2 from the UNEP Emissions Gap Report 2017, showing the projected emissions gap in 2030 relative to 1.5°C or 2.0°C warming targets. 

Warming forecasts against “Actual” temperature variation

Hansen’s testimony was a clear case of political advocacy. By making Scenario B constant the authors are making a bold policy statement. That is, to stop catastrophic global warming (and thus prevent potentially catastrophic changes to climate systems) requires draconian reductions in emissions. Simply maintaining emissions at the levels of the mid-1980s will make little difference. That is due to the forcing being related to the cumulative quantity of emissions.

Given that the data is not in quite in line with scenario A, if the theory is correct, then I would expect:-

  1. Warming trend to be somewhere between Scenario A and Scenario B. Most people accept 4.2equilibrium climate sensitivity of the Hansen model was 4.2ºC for a doubling of CO2 was too high. The IPCC now uses 3ºC for ECS. More recent research has it much lower still. However, although the rate of the warming might be less, the pattern of warming over time should be similar.
  2. Average temperatures after 2010 to be significantly higher than in 1987.
  3. The rate of warming in the 1990s to be marginally lower than in the period 1970-1990, but still strongly positive.
  4. The rate of warming in the 2000s to be strongly positive marginally higher than in the 1990s.

From the model Scenario C, there seems to be about a five year lag in the model between changes in emission rates and changes in temperatures. However, looking at the actual temperature data there is quite a different warming pattern. Five years ago C3 Headlines had a post 2013: The NASA/Hansen Climate Model Prediction of Global Warming Vs. Climate Reality.  The main graphic is in Figure 6

Figure 6 : C3 Headlines – NASA Hansen Prediction Vs Reality

The first thing to note is that the Scenario Assumptions are incorrect. Not only are they labelled as CO2, not GHG emissions, but are all stated wrongly. Stating them correctly would show a greater contradiction between forecasts and reality. However, the Scenario data appears to be reproduced correctly, and the actual graph appears to be in line with a graphic produced last month by Gavin Schmidt last month in his defense of Hansen’s predictions.

The data contradicts the forecasts. Although average temperatures are clearly higher than in in 1987, they are not in line with the forecast of Scenario A which is closest to the actual emissions trends. The rise is way below 70% of the model implied by inputting the lower IPCC climate sensitivity, and allowing for GHG emissions being fractional below the 1.5% per annum of Scenario A. But the biggest problem is where the main divergence occurred. Rather than warming accelerating slightly in the 2000s (after a possible slowdown in the 1990s),  there was no slowdown in the 1990s, but it either collapsed to zero, or massively reduced, depending on the data set was used. This is in clear contradiction of the model. Unless there is an unambiguous and verifiable explanation (rather than a bunch of waffly and contradictory excuses ), the model should be deemed to be wrong. There could be natural and largely unknown natural factors or random data noise that could explain the discrepancy. But equally (and quite plausibly) those same factors could have contributed to the late twentieth century warming.

This simple comparison has an important implication for policy. As there is no clear evidence to link most of the observed warming to GHG emissions, by implication there is no clear support for the belief that reducing GHG emissions will constrain future warming. But reducing global GHG emissions is merely an aspiration. As the graphic in Figure 5 clearly demonstrates, over twenty months after the Paris Climate Agreement was signed there is still no prospect of aggregate GHG emissions falling through policy. Hansen et. al 1988 is therefore a double failure; both as a scientific forecast and a tool for policy advocacy in terms of reducing GHG emissions. If only the supporters would realize their failure, and the useless and costly climate policies could be dismantled.

Kevin Marshall

*Hansen, J., I. Fung, A. Lacis, D. Rind, S. Lebedeff, R. Ruedy, G. Russell, and P. Stone, 1988: Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model. J. Geophys. Res., 93, 9341-9364, doi:10.1029/JD093iD08p09341.

Does data coverage impact the HADCRUT4 and NASA GISS Temperature Anomalies?

Introduction

This post started with the title “HADCRUT4 and NASA GISS Temperature Anomalies – a Comparison by Latitude“.  After deriving a global temperature anomaly from the HADCRUT4 gridded data, I was intending to compare the results with GISS’s anomalies by 8 latitude zones. However, this opened up an intriguing issue. Are global temperature anomalies impacted by a relative lack of data in earlier periods? The leads to a further issue of whether infilling of the data can be meaningful, and hence be considered to “improve” the global anomaly calculation.

A Global Temperature Anomaly from HADCRUT4 Gridded Data

In a previous post, I looked at the relative magnitudes of early twentieth century and post-1975 warming episodes. In the Hadley datasets, there is a clear divergence between the land and sea temperature data trends post-1980, a feature that is not present in the early warming episode. This is reproduced below as Figure 1.

Figure 1 : Graph of Hadley Centre 7 year moving average temperature anomalies for Land (CRUTEM4), Sea (HADSST3) and Combined (HADCRUT4)

The question that needs to be answered is whether the anomalous post-1975 warming on the land is due to real divergence, or due to issues in the estimation of global average temperature anomaly.

In another post – The magnitude of Early Twentieth Century Warming relative to Post-1975 Warming – I looked at the NASA Gistemp data, which is usefully broken down into 8 Latitude Zones. A summary graph is shown in Figure 2.

Figure 2 : NASA Gistemp zonal anomalies and the global anomaly

This is more detail than the HADCRUT4 data, which is just presented as three zones of the Tropics, along with Northern and Southern Hemispheres. However, the Hadley Centre, on their HADCRUT4 Data: download page, have, under  HadCRUT4 Gridded data: additional fields, a file HadCRUT.4.6.0.0.median_ascii.zip. This contains monthly anomalies for 5o by 5o grid cells from 1850 to 2017. There are 36 zones of latitude and 72 zones of longitude. Over 2016 months, there are over 5.22 million grid cells, but only 2.51 million (48%) have data. From this data, I have constructed a global temperature anomaly. The major issue in the calculation is that the grid cells are of different areas. A grid cell nearest to the equator at 0o to 5o has about 23 times the area of a grid cell adjacent to the poles at 85o to 90o. I used the appropriate weighting for each band of latitude.

The question is whether I have calculated a global anomaly similar to the Hadley Centre. Figure 3 is a reconciliation with the published global anomaly mean (available from here) and my own.

Figure 3 : Reconciliation between HADCRUT4 published mean and calculated weighted average mean from the Gridded Data

Prior to 1910, my calculations are slightly below the HADCRUT 4 published data. The biggest differences are in 1956 and 1915. Overall the differences are insignificant and do not impact on the analysis.

I split down the HADCRUT4 temperature data by eight zones of latitude on a similar basis to NASA Gistemp. Figure 4 presents the results on the same basis as Figure 2.

Figure 4 : Zonal surface temperature anomalies a the global anomaly calculated using the HADCRUT4 gridded data.

Visually, there are a number of differences between the Gistemp and HADCRUT4-derived zonal trends.

A potential problem with the global average calculation

The major reason for differences between HADCRUT4 & Gistemp is that the latter has infilled estimated data into areas where there is no data. Could this be a problem?

In Figure 5, I have shown the build-up in global coverage. That is the percentage of 5o by 5o grid cells with an anomaly in the monthly data.

Figure 5 : HADCRUT4 Change in the percentage coverage of each zone in the HADCRUT4 gridded data. 

Figure 5 shows a build-up in data coverage during the late nineteenth and early twentieth centuries. The World Wars (1914-1918 & 1939-1945) had the biggest impact on the Southern Hemisphere data collection. This is unsurprising when one considers it was mostly fought in the Northern Hemisphere, and European powers withdrew resources from their far-flung Empires to protect the mother countries. The only zones with significantly less than 90% grid coverage in the post-1975 warming period are the Arctic and the region below 45S. That is around 19% of the global area.

Finally, comparing comparable zones in the Northen and Southern hemispheres, the tropics seem to have comparable coverage, whilst for the polar, temperate and mid-latitude areas the Northern Hemisphere seems to have better coverage after 1910.

This variation in coverage can potentially lead to wide discrepancies between any calculated temperature anomalies and a theoretical anomaly based upon one with data in all the 5o by 5o grid cells. As an extreme example, with my own calculation, if just one of the 72 grid cells in a band of latitude had a figure, then an “average” would have been calculated for a band right around the world 555km (345 miles) from North to South for that month for that band. In the annual figures by zone, it only requires one of the 72 grid cells, in one of the months, in one of the bands of latitude to have data to calculate an annual anomaly. For the tropics or the polar areas, that is just one in 4320 data points to create an anomaly. This issue will impact early twentieth-century warming episode far more than the post-1975 one. Although I would expect the Hadley centre to have done some data cleanup of the more egregious examples in their calculation, potentially lack of data in grid cells could have quite random impacts, thus biasing the global temperature anomaly trends to an unknown, but significant extent. An appreciation of how this could impact can be appreciated from an example of NASA GISS Global Maps.

NASA GISS Global Maps Temperature Trends Example

NASA GISS Global Maps from GHCN v3 Data provide maps with the calculated change in average temperatures. I have run the maps to compare annual data for 1940 with a baseline of 1881-1910, capturing much of the early twentieth-century warming. I have run the maps at both the 1200km and 250km smoothing.

Figure 6 : NASA GISS Global anomaly Map and average anomaly by Latitude comparing 1940 with a baseline of 1881 to 1910 and a 1200km smoothing radius

Figure 7 : NASA GISS Global anomaly Map and average anomaly by Latitude comparing 1940 with a baseline of 1881 to 1910 and a 250km smoothing radius. 

With respect to the maps in figures 6 & 7

  • There is no apparent difference in the sea data between the 1200km and 250km smoothing radius, except in the polar regions with more cover in the former. The differences lie in the land area.
  • The grey areas with insufficient data all apply to the land or ocean areas in polar regions.
  • Figure 6, with 1200km smoothing, has most of the land infilled, whilst the 250km smoothing shows the lack of data coverage for much of South America, Africa, the Middle East, South-East Asia and Greenland.

Even with these land-based differences in coverage, it is clear that from either map that at any latitude there are huge variations in calculated average temperature change. For instance, take 40N. This line of latitude is North of San Francisco on the West Coast USA, clips Philidelphia on the East Coast. On the other side of the Atlantic, Madrid, Ankara and Beijing are at about 40N. There are significant points on the line on latitude with estimate warming greater than 1C (e.g. California), whilst at the same time in Eastern Europe, cooling may have exceeded 1C in the period. More extreme is at 60N (Southern Alaska, Stockholm, St Petersburg) the difference in temperature along the line of latitude is over 3C. This compares to a calculated global rise of 0.40C.

This lack of data may have contributed (along with a faulty algorithm) to the differences in the Zonal mean charts by Latitude. The 1200km smoothing radius chart bears little relation to the 250km smoothing radius. For instance:-

  •  1200km shows 1.5C warming at 45S, 250km about zero. 45S cuts through South Island, New Zealand.
  • From the equator to 45N, 1200km shows rise from 0.5C to over 2.0C, 250km shows drop from less than 0.5C to near zero, then rise to 0.2C. At around 45N lies Ottowa, Maine, Bordeaux, Belgrade, Crimea and the most Northern point in Japan.

The differences in the NASA Giss Maps, in a period when available data covered only around half the 2592 5o by 5o grid cells, indicate quite huge differences in trends between different areas. As a consequence, trying to interpolate warming trends from one area to adjacent areas appears to give quite different results in terms of trends by latitude.

Conclusions and Further Questions

The issue I originally focussed upon was the relative size of the early twentieth-century warming to the Post-1975. The greater amount of warming in the later period seemed to be due to the greater warming on land covering just 30% of the total global area. The sea temperature warming phases appear to be pretty much the same.

The issue that I focussed upon was a data issue. The early twentieth century had much less data coverage than after 1975. Further, the Southern Hemisphere had worse data coverage than the Northern Hemisphere, except in the Tropics. This means that in my calculation of a global temperature anomaly from the HADCRUT4 gridded data (which in aggregate was very similar to the published HADCRUT4 anomaly) the average by latitude will not be comparing like with like in the two warming periods. In particular, in the early twentieth-century, a calculation by latitude will not average right the way around the globe, but only on a limited selection of bands of longitude. On average this was about half, but there are massive variations. This would be alright if the changes in anomalies were roughly the same over time by latitude. But an examination of NASA GISS global maps for a period covering the early twentieth-century warming phase reveals that trends in anomalies at the same latitude are quite different over time. This implies that there could be large, but unknown, biases in the data.

I do not believe the analysis ends here. There are a number of areas that I (or others) can try to explore.

  1. Does the NASA GISS infilling of the data get us closer or further away from a what a global temperature anomaly would look like with full data coverage? My guess, based on the extreme example of Antartica trends (discussed here) is that the infilling will move away from the more perfect trend. The data could show otherwise.
  2. Are the changes in data coverage on land more significant than the global average or less? Looking at CRUTEM4 data could resolve this question.
  3. Would anomalies based upon similar grid coverage after 1900 give different relative trend patterns to the published ones based on dissimilar grid coverage?

Whether I get the time to analyze these is another issue.

Finally, the problem of trends varying considerably and quite randomly across the globe is the same issue that I found with land data homogenisation discussed here and here. To derive a temperature anomaly for a grid cell, it is necessary to make the data homogeneous. In standard homogenisation techniques, it is assumed that the underlying trends in an area is pretty much the same. Therefore, any differences in trend between adjacent temperature stations will be as a result of data imperfections. I found numerous examples where there were likely differences in trend between adjacent temperature stations. Homogenisation will, therefore, eliminate real but local climatic trends. Averaging incomplete global data where missing data could contain regional but unknown data trends may cause biases at a global scale.

Kevin Marshall

 

 

More Coal-Fired Power Stations in Asia

A lovely feature of the GWPF site is its extracts of articles related to all aspects of climate and related energy policies. Yesterday the GWPF extracted from an opinion piece in the Hong Kong-based South China Morning Post A new coal war frontier emerges as China and Japan compete for energy projects in Southeast Asia.
The GWPF’s summary:-

Southeast Asia’s appetite for coal has spurred a new geopolitical rivalry between China and Japan as the two countries race to provide high-efficiency, low-emission technology. More than 1,600 coal plants are scheduled to be built by Chinese corporations in over 62 countries. It will make China the world’s primary provider of high-efficiency, low-emission technology.

A summary point in the article is not entirely accurate. (Italics mine)

Because policymakers still regard coal as more affordable than renewables, Southeast Asia’s industrialisation continues to consume large amounts of it. To lift 630 million people out of poverty, advanced coal technologies are considered vital for the region’s continued development while allowing for a reduction in carbon emissions.

Replacing a less efficient coal-fired power station with one of the latest technology will reduce carbon (i.e CO2) emissions per unit of electricity produced. In China, these efficiency savings replacement process may outstrip the growth in power supply from fossil fuels. But in the rest of Asia, the new coal-fired power stations will be mostly additional capacity in the coming decades, so will lead to an increase in CO2 emissions. It is this additional capacity that will be primarily responsible for driving the economic growth that will lift the poor out of extreme poverty.

The newer technologies are important in other types emissions. That is the particle emissions that has caused high levels of choking pollution and smogs in many cities of China and India. By using the new technologies, other countries can avoid the worst excesses of this pollution, whilst still using a cheap fuel available from many different sources of supply. The thrust in China will likely be to replace the high pollution power stations with new technologies or adapt them to reduce the emissions and increase efficiencies. Politically, it is a different way of raising living standards and quality of life than by increasing real disposable income per capita.

Kevin Marshall

 

HADCRUT4, CRUTEM4 and HADSST3 Compared

In the previous post, I compared early twentieth-century warming with the post-1975 warming in the Berkeley Earth Global temperature anomaly. From a visual inspection of the graphs, I determined that the greater warming in the later period is due to more land-based warming, as the warming in the oceans (70% of the global area) was very much the same. The Berkeley Earth data ends in 2013, so does not include the impact of the strong El Niño event in the last three years.

Global average temperature series page of the Met Office Hadley Centre Observation Datasets has the average annual temperature anomalies for CRUTEM4 (land-surface air temperature) and HADSST3 (sea-surface temperature)  and HADCRUT4 (combined). From these datasets, I have derived the graph in Figure 1.

Figure 1 : Graph of Hadley Centre annual temperature anomalies for Land (CRUTEM4), Sea (HADSST3) and Combined (HADCRUT4)

  Comparing the early twentieth-century with 1975-2010,

  • Land warming is considerably greater in the later period.
  • Combined land and sea warming is slightly more in the later period.
  • Sea surface warming is slightly less in the later period.
  • In the early period, the surface anomalies for land and sea have very similar trends, whilst in the later period, the warming of the land is considerably greater than the sea surface warming.

The impact is more clearly shown with 7 year centred moving average figures in Figure 2.

Figure 2 : Graph of Hadley Centre 7 year moving average temperature anomalies for Land (CRUTEM4), Sea (HADSST3) and Combined (HADCRUT4)

This is not just a feature of the HADCRUT dataset. NOAA Global Surface Temperature Anomalies for land, ocean and combined show similar patterns. Figure 3 is on the same basis as Figure 2.

Figure 3 : Graph of NOAA 7 year moving average temperature anomalies for Land, Ocean and Combined.

The major common feature is that the estimated land temperature anomalies have shown a much greater warming trend that the sea surface anomalies since 1980, but no such divergence existed in the early twentieth century warming period. Given that the temperature data sets are far from complete in terms of coverage, and the data is of variable quality, is this divergence a reflection of the true average temperature anomalies based on far more complete and accurate data? There are a number of alternative possibilities that need to be investigated to help determine (using beancounter terminology) whether the estimates are a true and fair reflection of the prespective that more perfect data and techniques would provide. My list might be far from exhaustive.

  1. The sea-surface temperature set understates the post-1975 warming trend due to biases within data set.
  2. The spatial distribution of data changed considerably over time. For instance, in recent decades more data has become available from the Arctic, a region with the largest temperature increases in both the early twentieth century and post-1975.
  3. Land data homogenization techniques may have suppressed differences in climate trends where data is sparser. Alternatively, due to relative differences in climatic trends between nearby locations increasing over time, the further back in time homogenization goes, the more accentuated these differences and therefore the greater the suppression of genuine climatic differences. These aspects I discussed here and here.
  4. There is deliberate manipulation of the data to exaggerate recent warming. Having looked at numerous examples three years ago, this is a perspective that I do not believe to have had any significant impact. However, simply believing something not to be the case, even with examples, does not mean that it is not there.
  5. Strong beliefs about how the data should look have, over time and multiple data adjustments created biases within the land temperature anomalies.

What I do believe is that an expert opinion to whether this divergence between the land and sea surface anomalies is a “true and fair view” of the actual state of affairs can only be reached by a detailed examination of the data. Jumping to conclusions – which is evident from many people across the broad spectrum of opinions on catastrophic anthropogenic global warming debate – will fall short of the most rounded opinion that can be gleaned from the data.

Kevin Marshall

 

The magnitude of Early Twentieth Century Warming relative to Post-1975 Warming

I was browsing the Berkeley Earth website and came across their estimate of global average temperature change. Reproduced as Figure 1.

Figure 1 – BEST Global Temperature anomaly

What clearly stands out is the 10-year moving average line. It clearly shows warming from in the early twentieth century, (the period 1910 to 1940) being very similar warming from the mid-1970s to the end of the series in both time period and magnitude. Maybe the later warming period is up to one-tenth of a degree Celsius greater than the earlier one. The period from 1850 to 1910 shows stasis or a little cooling, but with high variability. The period from the 1940s to the 1970s shows stasis or slight cooling, and low variability.

This is largely corroborated by HADCRUT4, or at least the version I downloaded in mid-2014.

Figure 2 – HADCRUT4 Global Temperature anomaly

HADCRUT4 estimates that the later warming period is about three-twentieths of a degree Celsius greater than the earlier period and that the recent warming is slightly less than the BEST data.

The reason for the close fit is obvious. 70% of the globe is ocean and for that BEST use the same HADSST dataset as HADCRUT4. Graphics of HADSST are a little hard to come by, but KevinC at skepticalscience usefully produced a comparison of the latest HADSST3 in 2012 with the previous version.

Figure 3  – HADSST Ocean Temperature anomaly from skepticalscience 

This shows the two periods having pretty much the same magnitudes of warming.

It is the land data where the differences lie. The BEST Global Land temperature trend is reproduced below.

Figure 4 – BEST Global Land Temperature anomaly

For BEST global land temperatures, the recent warming was much greater than the early twentieth-century warming. This implies that the sea surface temperatures showed pretty much the same warming in the two periods. But if greenhouse gases were responsible for a significant part of global warming then the warming for both land and sea would be greater after the mid-1970s than in the early twentieth century. Whilst there was a rise in GHG levels in the early twentieth century, it was less than in the period from 1945 to 1975, when there was no warming, and much less than the post-1975 when CO2 levels rose massively. Whilst there can be alternative explanations for the early twentieth-century warming and the subsequent lack of warming for 30 years (when the post-WW2 economic boom which led to a continual and accelerating rise in CO2 levels), without such explanations being clear and robust the attribution of post-1975 warming to rising GHG levels is undermined. It could be just unexplained natural variation.

However, as a preliminary to examining explanations of warming trends, as a beancounter, I believe it is first necessary to examine the robustness of the figures. In looking at temperature data in early 2015, one aspect that I found unsatisfactory with the NASA GISS temperature data was the zonal data. GISS usefully divide the data between 8 bands of latitude, which I have replicated as 7 year centred moving averages in Figure 5.

Figure 5 – NASA Gistemp zonal anomalies and the global anomaly

What is significant is that some of the regional anomalies are far greater in magnitude

The most Southerly is for 90S-64S, which is basically Antarctica, an area covering just under 5% of the globe. I found it odd that there should a temperature anomaly for the region from the 1880s, when there were no weather stations recording on the frozen continent until the mid-1950s. The nearest is Base Orcadas located at 60.8 S 44.7 W, or about 350km north of 64 S. I found that whilst the Base Orcadas temperature anomaly was extremely similar to the Antarctica Zonal anomaly in the period until 1950, it was quite dissimilar in the period after.

Figure 6. Gistemp 64S-90S annual temperature anomaly compared to Base Orcadas GISS homogenised data.

NASA Gistemp has attempted to infill the missing temperature anomaly data by using the nearest data available. However, in this case, Base Orcadas appears to climatically different than the average anomalies for Antarctica, and from the global average as well. The result of this is to effectively cancel out the impact of the massive warming in the Arctic on global average temperatures in the early twentieth century. A false assumption has effectively shrunk the early twentieth-century warming. The shrinkage will be small, but it undermines the NASA GISS being the best estimate of a global temperature anomaly given the limited data available.

Rather than saying that the whole exercise of determining a valid comparison the two warming periods since 1900 is useless, I will instead attempt to evaluate how much the lack of data impacts on the anomalies. To this end, in a series of posts, I intend to look at the HADCRUT4 anomaly data. This will be a top-down approach, looking at monthly anomalies for 5o by 5o grid cells from 1850 to 2017, available from the Met Office Hadley Centre Observation Datasets. An advantage over previous analyses is the inclusion of anomalies for the 70% of the globe covered by ocean. The focus will be on the relative magnitudes of the early twentieth-century and post-1975 warming periods. At this point in time, I have no real idea of the conclusions that can be drawn from the analysis of the data.

Kevin Marshall

 

 

Ocean Impact on Temperature Data and Temperature Homgenization

Pierre Gosselin’s notrickszone looks at a new paper.

Temperature trends with reduced impact of ocean air temperature – Frank LansnerJens Olaf Pepke Pedersen.

The paper’s abstract.

Temperature data 1900–2010 from meteorological stations across the world have been analyzed and it has been found that all land areas generally have two different valid temperature trends. Coastal stations and hill stations facing ocean winds are normally more warm-trended than the valley stations that are sheltered from dominant oceans winds.

Thus, we found that in any area with variation in the topography, we can divide the stations into the more warm trended ocean air-affected stations, and the more cold-trended ocean air-sheltered stations. We find that the distinction between ocean air-affected and ocean air-sheltered stations can be used to identify the influence of the oceans on land surface. We can then use this knowledge as a tool to better study climate variability on the land surface without the moderating effects of the ocean.

We find a lack of warming in the ocean air sheltered temperature data – with less impact of ocean temperature trends – after 1950. The lack of warming in the ocean air sheltered temperature trends after 1950 should be considered when evaluating the climatic effects of changes in the Earth’s atmospheric trace amounts of greenhouse gasses as well as variations in solar conditions.

More generally, the paper’s authors are saying that over fairly short distances temperature stations will show different climatic trends. This has a profound implication for temperature homogenization. From Venema et al 2012.

The most commonly used method to detect and remove the effects of artificial changes is the relative homogenization approach, which assumes that nearby stations are exposed to almost the same climate signal and that thus the differences between nearby stations can be utilized to detect inhomogeneities (Conrad and Pollak, 1950). In relative homogeneity testing, a candidate time series is compared to multiple surrounding stations either in a pairwise fashion or to a single composite reference time series computed for multiple nearby stations. 

Lansner and Pederson are, by implication, demonstrating that the principle assumption on which homogenization is based (that nearby temperature stations are exposed to almost the same climatic signal) is not valid. As a result data homogenization will not only eliminate biases in the temperature data (such a measurement biases, impacts of station moves and the urban heat island effect where it impacts a minority of stations) but will also adjust out actual climatic trends. Where the climatic trends are localized and not replicated in surrounding areas, they will be eliminated by homogenization. What I found in early 2015 (following the examples of Paul Homewood, Euan Mearns and others) is that there are examples from all over the world where the data suggests that nearby temperature stations are exposed to different climatic signals. Data homogenization will, therefore, cause quite weird and unstable results. A number of posts were summarized in my post Defining “Temperature Homogenisation”.  Paul Matthews at Cliscep corroborated this in his post of February 2017 “Instability og GHCN Adjustment Algorithm“.

During my attempts to understand the data, I also found that those who support AGW theory not only do not question their assumptions but also have strong shared beliefs in what the data ought to look like. One of the most significant in this context is a Climategate email sent on Mon, 12 Oct 2009 by Kevin Trenberth to Michael Mann of Hockey Stick fame, and copied to Phil Jones of the Hadley centre, Thomas Karl of NOAA, Gavin Schmidt of NASA GISS, plus others.

The fact is that we can’t account for the lack of warming at the moment and it is a travesty that we can’t. The CERES data published in the August BAMS 09 supplement on 2008 shows there should be even more warming: but the data are surely wrong. Our observing system is inadequate. (emphasis mine)

Homogenizing data a number of times, and evaluating the unstable results in the context of strongly-held beliefs will bring the trends evermore into line with those beliefs. There is no requirement for some sort of conspiracy behind deliberate data manipulation for this emerging pattern of adjustments. Indeed a conspiracy in terms of a group knowing the truth and deliberately perverting that evidence does not really apply. Another reason for the conspiracy not applying is the underlying purpose of homogenization. It is to allow that temperature station to be representative of the surrounding area. Without that, it would not be possible to compile an average for the surrounding area, from which the global average in constructed. It is this requirement, in the context of real climatic differences over relatively small areas, I would suggest leads to the deletions of “erroneous” data and the infilling of estimated data elsewhere.

The gradual bringing the temperature data sets into line will beliefs is most clearly shown in the NASA GISS temperature data adjustments. Climate4you produces regular updates of the adjustments since May 2008. Below is the March 2018 version.

The reduction of the 1910 to 1940 warming period (which is at odds with theory) and the increase in the post-1975 warming phase (which correlates with the rise in CO2) supports my contention of the influence of beliefs.

Kevin Marshall

 

Climate Alarmist Bob Ward’s poor analysis of Research Data

After Christopher Booker’s excellent new Report for the GWPF “Global Warming: A Case Study In Groupthink” was published on 20th February, Bob Ward (Policy and Communications Director at the Grantham Research Institute on Climate Change and the Environment at the LSE) typed a rebuttal article “Do male climate change ‘sceptics’ have a problem with women?“. Ward commenced the article with a highly misleading statement.

On 20 February, the Global Warming Policy Foundation launched a new pamphlet at the House of Lords, attacking the mainstream media for not giving more coverage to climate change ‘sceptics’.

I will lead it to the reader to judge for themselves how misleading the statement is by reading the report or alternatively reading his summary at Capx.co.

At Cliscep (reproduced at WUWT), Jaime Jessop has looked into Ward’s distractive claims about the GWPF gender bias. This comment by Ward particularly caught my eye.

A tracking survey commissioned by the Department for Business, Energy and Industrial Strategy showed that, in March 2017, 7.6% answered “I don’t think there is such a thing as climate change” or “Climate change is caused entirely caused by natural processes”, when asked for their views. Among men the figure was 8.1%, while for women it was 7.1%.

I looked at the Tracking Survey. It is interesting that the Summary of Key Findings contains no mention of gender bias, nor of beliefs on climate change. It is only in the Wave 21 full dataset spreadsheet that you find the results of the question 22.

Q22. Thinking about the causes of climate change, which, if any, of the following best describes your opinion?
[INVERT ORDER OF RESPONSES 1-5]
1. Climate change is entirely caused by natural processes
2. Climate change is mainly caused by natural processes
3. Climate change is partly caused by natural processes and partly caused by human activity
4. Climate change is mainly caused by human activity
5. Climate change is entirely caused by human activity
6. I don’t think there is such a thing as climate change.
7. Don’t know
8. No opinion

Note that the first option presented to the questionee is 5, then 4, then 3, then 2, then 1. There may, therefore, be an inbuilt bias in overstating the support for Climate Change being attributed to human activity. But the data is clearly presented, so a quick pivot table was able to check Ward’s results.

The sample was of 2180 – 1090 females and 1090 males. Adding the responses  to “I don’t think there is such a thing as climate change” or “Climate change is caused entirely caused by natural processes” I get 7.16% for females – (37+41)/1090 – and 8.17% for males – (46+43)/1090. Clearly, Bob Ward has failed to remember what he was taught in high school about roundings.

Another problem is that this is raw data. The opinion pollsters have taken time and care to adjust for various demographic factors by adding a weighting to each line. On this basis, Ward should have reported 6.7% for females, 7.6% for males and 7.1% overall.

More importantly, if males tend to be more sceptical of climate change than females, then they will be less alarmist than females. But the data says something different. Of the weighted responses, to those who opted for the most extreme “Climate change is entirely caused by natural processes“, 12.5% were female and 14.5% were male. Very fractionally at the extreme, men are proportionality more alarmist than females than they are sceptical. More importantly, men are slightly more extreme in their opinions on climate change (for or against) than women.

The middle ground is the response to “Climate change is partly caused by natural processes and partly caused by human activity“. The weighted response was 44.5% female and 40.7% male, confirming that men are more extreme in their views than women.

There is a further finding that can be drawn. The projections by the IPCC for future unmitigated global warming assume that all, or the vast majority of, global warming since 1850 is human-caused. Less than 41.6% of British women and 43.2% of British men agree with this assumption that justifies climate mitigation policies.

Below are my summaries. My results are easily replicated for those with an intermediate level of proficiency in Excel.

Learning Note

The most important lesson for understanding data is to analyse that data from different perspectives, against different hypotheses. Bob Ward’s claim of a male gender bias towards climate scepticism in an opinion survey, upon a slightly broader analysis, becomes one where British males are slightly more extreme and forthright in their views than British females whether for or against. This has parallels to my conclusion when looking at the 2013 US study The Role of Conspiracist Ideation and Worldviews in Predicting Rejection of Science – Stephan Lewandowsky, Gilles E. Gignac, Klaus Oberauer. Here I found that rather than the paper’s finding that conspiracist ideation being “associated with the rejection of all scientific propositions tested”, the data strongly indicated that people with strong opinions on one subject, whether for or against, tend to have strong opinions on other subjects, whether for or against. Like with any bias of perspective, (ideological, religious, gender, race, social class, national, football team affiliation etc.) the way to counter bias is to concentrate on the data. Opinion polls are a poor starting point, but at least they may report on perspectives outside of one’s own immediate belief systems. 

Kevin Marshall

“Were going to miss the 2°C Warming target” study and IPCC AR5 WG3 Chapter 6

WUWT had a post on 22nd January

Study: we’re going to miss (and overshoot) the 2°C warming target

This comment (from a University of Southhampton pre-publication news release) needs some explanation to relate it to IPCC AR5.

Through their projections, Dr Goodwin and Professor Williams advise that cumulative carbon emissions needed to remain below 195-205 PgC (from the start of 2017) to deliver a likely chance of meeting the 1.5°C warming target while a 2°C warming target requires emissions to remain below 395-455 PgC.

The PgC is peta-grams of Carbon. For small weights, one normally uses grams. For larger weights one uses kilograms. For still larger weights one uses tonnes. Under the Imperial measurement system, one uses ounces, pounds and tons. So one peta-gram is a billion (or giga) tonne.
Following the IPCC’s convention, GHG emissions are expressed in units of CO2, not carbon. Other GHGs are expressed in CO2e. So 1 PgC = 3.664 GtCO2e.

So the emissions from the start of 2017 are 715-750 GtCO2e for 1.5°C of warming and 1447-1667 GtCO2e for 2°C of warming. To make comparable to IPCC AR5, (specifically to table 6.3 from IPCC AR5 WG3 Chapter 6 p431), one needs to adjust for two things – the IPCC’s projections are from 5 years earlier, and for CO2 emissions only, about 75% of GHG emissions.

The IPCC’s projections of CO2 emissions are 630-1180 GtCO2 for 1.5-1.7°C of warming and 960-1550 GtCO2e for 1.7-2.1°C of warming.

With GHG emissions roughly 50 GtCO2e a year and CO2 emissions 40 GtCO2 a year, from the IPCC’s figures updated from the start of 2017 and expressed in GtCO2e are 570-1300 GtCO2e for 1.5-1.7°C of warming and 1010-1800 GtCO2e for 1.7-2.1°C of warming.

Taking the mid-points of the IPCC’s and the Goodwin-Williams figures, the new projections are saying that at current emissions levels, 1.5°C will be breached four years earlier, and 2°C will be breached one year later. Only the mid-points are 1.6°C and 1.9°C, so it makes no real difference whatsoever. The Goodwin-Williams figures just narrow the ranges and use different units of measure.

But there is still a major problem. Consider this mega table 6.3 reproduced, at lower quality, below.

Notice Column A is for CO2 equivalent concentration in 2100 (ppm CO2eq). Current CO2 levels are around 405 ppm, but GHG gas levels are around 450 ppm CO2eq. Then notice columns G and H, with a joint heading of Concentration (ppm). Column G is for CO2 levels in 2100 and Column H is for CO2 equivalent levels. Note also that for the first few rows of data, Column H is greater than Column A, implying that sometime this century peak CO2 levels will be higher than at the end of the century, and (subject to the response period of the climate system to changes in greenhouse gas levels)  average global temperatures could (subject to the models being correct) exceed the projected 2100 levels. How much though?

Using a magic equation at the skeptical science blog, and (after correcting to make a doubling of CO2 convert to exactly 3°C of warming) assume that all changes in CO2 levels instantly translate into average temperature changes. Further, I assume that other greenhouse gases are irrelevant to the warming calculation, and peak CO2 concentrations are calculated from peak GHG, 2100 GHG, and 2100 CO2 concentrations. I derived the following table.

The 1.5°C warming scenario is actually 1.5-1.7°C warming in 2100, with a mid-point of 1.6°C. The peak implied temperatures are about 2°C.

The 2°C warming scenario is actually 1.7-2.1°C warming in 2100, with a mid-point of 1.9°C. The peak implied temperatures are about 2.3°C, with 2.0°C of warming in 2100 implying about 2.4°C peak temperature rise.

So when the IPCC talk about constraining temperature rise, it is about projected temperature rise in 2100, not about stopping global average temperature rise breaching 1.5°C or 2°C barriers.

Now consider the following statement from the University of Southhampton pre-publication news release, emphasis mine.

“Immediate action is required to develop a carbon-neutral or carbon-negative future or, alternatively, prepare adaptation strategies for the effects of a warmer climate,” said Dr Goodwin, Lecturer in Oceanography and Climate at Southampton. “Our latest research uses a combination of a model and historical data to constrain estimates of how long we have until 1.5°C or 2°C warming occurs. We’ve narrowed the uncertainty in surface warming projections by generating thousands of climate simulations that each closely match observational records for nine key climate metrics, including warming and ocean heat content.”

Professor Williams, Chair in Ocean Sciences at Liverpool, added: “This study is important by providing a narrower window of how much carbon we may emit before reaching 1.5°C or 2°C warming. There is a real need to take action now in developing and adopting the new technologies to move to a more carbon-efficient or carbon-neutral future as we only have a limited window before reaching these warming targets.” This work is particularly timely given the work this year of the Intergovernmental Panel on Climate Change (IPCC) to develop a Special Report on the Impacts of global warming of 1.5°C above pre-industrial levels.

Summary

The basic difference between IPCC AR5 Chapter 6 Table 6.3 and the new paper is the misleading message that various emissions policy scenarios will prevent warming breaching either 1.5°C or 2°C of warming when the IPCC scenarios are clear that this is the 2100 warming level. The IPCC scenarios imply that before 2100 warming could peak at respectively around 1.75°C or 2.4°C.  My calculations can be validated through assuming (a) a doubling of CO2 gives 3°C of warming, (b) other GHGs are irrelevant, (c) there no significant lag between the rise in CO2 level and rise in global average temperature.

Kevin Marshall