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.

Changing a binary climate argument into understanding the issues

Last month Geoff Chambers posted “Who’s Binary, Us or Them? Being at cliscep the question was naturally about whether sceptics or alarmists were binary in their thinking. It reminded me about something that went viral on youtube a few year’s ago. Greg Craven’s The Most Terrifying Video You’ll Ever See.

To his credit, Greg Craven in introducing both that human-caused climate change can have a trivial impact recognize that mitigating climate (taking action) is costly. But for the purposes of his decision grid he side-steps these issues to have binary positions on both. The decision is thus based on the belief that the likely consequences (costs) of catastrophic anthropogenic global warming then the likely consequences (costs) of taking action. A more sophisticated statement of this was from a report commissioned in the UK to justify the draconian climate action of the type Greg Craven is advocating. Sir Nicholas (now Lord) Stern’s report of 2006 (In the Executive Summary) had the two concepts of the warming and policy costs separated when it claimed

Using the results from formal economic models, the Review estimates that if we don’t act, the overall costs and risks of climate change will be equivalent to losing at least 5% of global GDP each year, now and forever. If a wider range of risks and impacts is taken into account, the estimates of damage could rise to 20% of GDP or more. In contrast, the costs of action – reducing greenhouse gas emissions to avoid the worst impacts of climate change – can be limited to around 1% of global GDP each year.

Craven has merely simplified the issue and made it more binary. But Stern has the same binary choice. It is a choice between taking costly action, or suffering the much greater possible consequences.  I will look at the policy issue first.

Action on Climate Change

The alleged cause of catastrophic anthropogenic global warming is (CAGW) is human greenhouse gas emissions. It is not just some people’s emissions that must be reduced, but the aggregate emissions of all 7.6 billion people on the planet. Action on climate change (i.e. reducing GHG emissions to near zero) must therefore include all of the countries in which those people live. The UNFCCC, in the run-up to COP21 Paris 2015, invited countries to submit Intended Nationally Determined Contributions (INDCs). Most did so before COP21, and as at June 2018, 165 INDCs have been submitted, representing 192 countries and 96.4% of global emissions. The UNFCCC has made them available to read. So these intentions will be sufficient “action” to remove the risk of CAGW? Prior to COP21, the UNFCCC produced a Synthesis report on the aggregate effect of INDCs. (The link no longer works, but the main document is here.) They produced a graphic that I have shown on multiple occasions of the gap between policy intentions on the desired policy goals. A more recent graphic is from the UNEP Emissions Gap Report 2017, published last October and

Figure 3 : Emissions GAP estimates from the UNEP Emissions GAP Report 2017

In either policy scenario, emissions are likely to be slightly higher in 2030 than now and increasing, whilst the policy objective is for emissions to be substantially lower than today and and decreasing rapidly. Even with policy proposals fully implemented global emissions will be at least 25% more, and possibly greater than 50%, above the desired policy objectives. Thus, even if proposed policies achieve their objective, in Greg Craven’s terms we are left with pretty much all the possible risks of CAGW, whilst incurring some costs. But the “we” is for 7.6 billion people in nearly 200 countries. But the real costs are being incurred by very few countries. For the United Kingdom, with the Climate Change Act 2018 is placing huge costs on the British people, but future generations of Britain’s will achieve very little or zero benefits.

Most people in the world live in poorer countries that will do nothing significant to constrain emissions growth if it that conflicts with economic growth or other more immediate policy objectives. In terms of the some of the most populous developing countries, it is quite clear that achieving the policy objectives will leave emissions considerably higher than today. For instance, China‘s main aims of peaking CO2 emissions around 2030 and lowering carbon emissions per unit of GDP in 2030 by 60-65% compared to 2005 by 2020 could be achieved with emissions in 2030 20-50% higher than in 2017. India has a lesser but similar target of reducing emissions per unit of GDP in 2030 by 30-35% compared to 2005 by 2020. If the ambitious economic growth targets are achieve, emissions could double in 15 years, and still be increasing past the middle of the century. Emissions in Bangladesh and Pakistan could both more than double by 2030, and continue increasing for decades after.

Within these four countries are over 40% of the global population. Many other countries are also likely to have emissions increasing for decades to come, particularly in Asia and Africa. Yet without them changing course global emissions will not fall.

There is another group of countries that are have vested interests in obstructing emission reduction policies. That is those who are major suppliers of fossil fuels. In a letter to Nature in 2015, McGlade and Ekins (The geographical distribution of fossil fuels unused when limiting global warming to 2°C) estimate that the proven global reserves of oil, gas and coal would produce about 2900 GtCO2e. They further estimate that the “non-reserve resources” of fossil fuels represent a further 8000 GtCO2e of emissions. The estimated that to constrain warming to 2C, 75% of proven reserves, and any future proven reserves would need to be left in the ground. Using figures from the BP Statistical Review of World Energy 2016 I produced a rough split by major country.

Figure 4 : Fossil fuel Reserves by country, expressed in terms of potential CO2 Emissions

Activists point to the reserves in the rich countries having to be left in the ground. But in the USA, Australia, Canada and Germany production of fossil fuels is not a major part of the economy. Ceasing production would be harmful but not devastating. One major comparison is between the USA and Russia. Gas and crude oil production are similar volumes in both countries. But, the nominal GDP of the US is more than ten times that of Russia. The production of both countries in 2016 was about 550 million tonnes or 3900 million barrels. At $70 a barrel that is around $275bn, equivalent to 1.3% of America’s GDP and 16% of Russia’s. In gas, prices vary, being very low in the highly competitive USA, and highly variable for Russian supply, with major supplier Gazprom acting as a discriminating monopolist. But America’s revenue is likely to be less than 1% of GDP and Russia’s equivalent to 10-15%. There is even greater dependency in the countries of the Middle East. In terms of achieve emissions targets, what is trying to be achieved is the elimination of the major source of the countries economic prosperity in a generation, with year-on-year contractions in fossil fuel sales volumes.

I propose that there are two distinct groups of countries that appear to have a lot lose from a global contraction in GHG emissions to near zero. There are the developing countries who would have to reduce long-term economic growth and the major fossil fuel-dependent countries, who would lose the very foundation of their economic output in a generation. From the evidence of the INDC submissions, there is now no possibility of these countries being convinced to embrace major economic self-harm in the time scales required. The emissions targets are not going to be met. The emissions gap will not be closed to any appreciable degree.

This leaves Greg Craven’s binary decision option of taking action, or not, as irrelevant. As taking action by a country will not eliminate the risk of CAGW, pursuing aggressive climate mitigation policies will impose net harms wherever they implemented. Further, it is not the climate activists who are making the decisions, but policy-makers countries themselves. If the activists believe that others should follow another path, it is them that must make the case. To win over the policy-makers they should have sought to understand their perspectives of those countries, then persuade them to accept their more enlightened outlook. The INDCs show that the climate activists gave failed in this mission. Until such time, when activists talk about the what “we” are doing to change the climate, or what “we” ought to be doing, they are not speaking about

But the activists have won over the United Nations, those who work for many Governments and they dominate academia. For most countries, this puts political leaders in a quandary. To maintain good diplomatic relations with other countries, and to appear as movers on a world stage they create the appearance of taking significant action on climate change for the outside world. On the other hand they are serving their countries through minimizing the real harms that imposing the policies would create. Any “realities” of climate change have become largely irrelevant to climate mitigation policies.

The Risks of Climate Apocalypse

Greg Craven recognized a major issue with his original video. In the shouting match over global warming who should you believe? In How it all Ends (which was followed up by further videos and a book) Craven believes he has the answer.

Figure 5 : Greg Craven’s “How it all Ends”

It was pointed out that the logic behind the grid is bogus. As in Devil’s advocate guise Craven says at 3:50

Wouldn’t that grid argue for action against any possible threat, no matter how costly the action or how ridiculous the threat? Even giant mutant space hamsters? It is better to go broke building a load of rodent traps than risk the possibility of being hamster chow. So this grid is useless.

His answer is to get a sense of how likely the possibility of global warming being TRUE or FALSE is. Given that science is always uncertain, and there are divided opinions.

The trick is not to look at what individual scientists are saying, but instead to look at what the professional organisations are saying. The more prestigious they are, the more weight you can give their statements, because they have got huge reputations to uphold and they don’t want to say something that later makes them look foolish. 

Craven points to the “two most respected in the world“. The National Academy of Sciences (NAS) and the American Association for the Advancement of Science (AAAS). Back in 2007 they had “both issued big statements calling for action, now, on global warming“.  The crucial question from scientists (that is people will a demonstrable expert understanding of the natural world) is not for political advocacy, but whether their statements say their is a risk of climate apocalypse. These two bodies still have statements on climate change.

National Academy of Sciences (NAS) says

There are well-understood physical mechanisms by which changes in the amounts of greenhouse gases cause climate changes. The US National Academy of Sciences and The Royal Society produced a booklet, Climate Change: Evidence and Causes (download here), intended to be a brief, readable reference document for decision makers, policy makers, educators, and other individuals seeking authoritative information on the some of the questions that continue to be asked. The booklet discusses the evidence that the concentrations of greenhouse gases in the atmosphere have increased and are still increasing rapidly, that climate change is occurring, and that most of the recent change is almost certainly due to emissions of greenhouse gases caused by human activities.

Further climate change is inevitable; if emissions of greenhouse gases continue unabated, future changes will substantially exceed those that have occurred so far. There remains a range of estimates of the magnitude and regional expression of future change, but increases in the extremes of climate that can adversely affect natural ecosystems and human activities and infrastructure are expected.

Note, this is conjunction with the Royal Society, which is arguably is (or was) the most prestigious  scientific organisation of them all. It is what not said that is as important as what is actually said. They are saying that there is a an expectation that extremes of climate could get worse. There is nothing that solely backs up the climate apocalypse, but a range of possibilities, including changes somewhat trivial on a global scale. The statement endorses a spectrum of possible positions that undermines the binary TRUE /FALSE position on decision-making.

The RS/NAS booklet has no estimates of the scale of possible climate catastrophism to be avoided. Point 19 is the closest.

Are disaster scenarios about tipping points like ‘turning off the Gulf Stream’ and release of methane from the Arctic a cause for concern?

The summary answer is

Such high-risk changes are considered unlikely in this century, but are by definition hard to predict. Scientists are therefore continuing to study the possibility of such tipping points beyond which we risk large and abrupt changes.

This appears not to support Stern’s contention that unmitigated climate change will costs at least 5% of global GDP by 2100. Another context of the back-tracking on potential catastrophism is to to compare with  Lenton et al 2008 – Tipping elements in the Earth’s climate system. Below is a map showing the the various elements considered.

Figure 6 : Fig 1 of Lenton et al 2008, with explanatory note.

Of the 14 possible tipping elements discussed, only one makes it into the booklet six years later. Surely if the other 13 were still credible more would have been included in booklet, and less on documenting trivial historical changes.

American Association for the Advancement of Science (AAAS) has a video

Figure 7 : AAAS “What We Know – Consensus Sense” video

 

It starts with the 97% Consensus claims. After asking the listener on how many,  Marshall Sheppard, Prof of Geography at Univ of Georgia states.

The reality is that 97% of scientists are pretty darn certain that humans are contributing to the climate change that we are seeing right now and we better do something about it to soon.

There are two key papers that claimed a 97% consensus. Doran and Zimmerman 2009 asked two questions,

1. When compared with pre-1800s levels, do you think that mean global temperatures have generally risen, fallen, or remained relatively constant?

2. Do you think human activity is a significant contributing factor in changing mean global temperatures?

The second of these two responses was answered in the affirmative by 77 of 79 climate scientists. This was reduced from 3146 responses received. Read the original to find out why it was reduced.

Dave Burton has links to a number of sources on these studies. A relevant quote on Doran and Zimmerman is from the late Bob Carter

Both the questions that you report from Doran’s study are (scientifically) meaningless because they ask what people “think”. Science is not about opinion but about factual or experimental testing of hypotheses – in this case the hypothesis that dangerous global warming is caused by human carbon dioxide emissions.

The abstract to Cook et al. 2013 begins

We analyze the evolution of the scientific consensus on anthropogenic global warming (AGW) in the peer-reviewed scientific literature, examining 11 944 climate abstracts from 1991–2011 matching the topics ‘global climate change’ or ‘global warming’. We find that 66.4% of abstracts expressed no position on AGW, 32.6% endorsed AGW, 0.7% rejected AGW and 0.3% were uncertain about the cause of global warming. Among abstracts expressing a position on AGW, 97.1% endorsed the consensus position that humans are causing global warming. 

Expressing a position does not mean a belief. It could be an assumption. The papers were not necessarily by scientists, but merely authors of academic papers that involved the topics ‘global climate change’ or ‘global warming’. Jose Duarte listed some of the papers that were included in the survey, along with looking at some that were left out.

Neither paper asked a question concerning belief in future climate catastrophism. Sheppard does not make clear the scale of climate change trends from the norm, so the human-caused element could be insignificant. The 97% consensus does not include the policy claims.

The booklet is also misleading as well in the scale of changes. For instance on sea-level rise it states.

Over the past two decades, sea levels have risen almost twice as fast as the average during the twentieth century.

You will get that if you compare the tide gauge data with the two decades of satellite data. The question is whether those two sets of data are accurate. As individual tide gauges do not tend to show acceleration, and others cannot find statistically significant acceleration, the claim seems not to be supported.

At around 4.15 in the consensus video AAAS CEO Alan I. Leshner says

America’s leaders should stop debating the reality of climate change and start deciding the best solutions. Our What we Know report makes clear that climate change threatens us at every level. We can reduce the risk of global warming to protect out people, businesses and communities from harm. At every level from our personal and community health, our economy and our future as a global leader.  Understanding and managing climate change risks is an urgent problem. 

The statement is about combating the potential risks from CAGW. The global part of global warming is significant for policy. The United States share of global emissions is around 13% of global emissions. That share has been falling as America’s emissions have been falling why the global aggregate emissions have been rising. The INDC submission for the United States aimed as getting US emissions in 2025 at 26-28% of 2005 levels, with a large part of that reduction already “achieved” when the report was published. The actual policy difference is likely to be less than 1% of global emissions. So any reduction in risks with respect to climate change seems to be tenuous. A consensus of the best scientific minds should have been able to work this out for themselves.

The NAAS does not give a collective expert opinion on climate catastrophism. This is shown by the inability to distinguish between banal opinions and empirical evidence for a big problem. This is carried over into policy advocacy, where they fail to distinguish between the United States and the world as a whole.

Conclusions

Greg Laden’s decision-making grid is inapplicable to real world decision-making. The decision whether to take action or not is not a unitary one, but needs to be taken at country level. Different countries will have different perspectives on the importance of taking action on climate change relative to other issues. In the real world, the proposals for action are available. In aggregate they will not “solve” the potential risk of climate apocalypse. Whatever the actual scale of CAGW, countries who pursue expensive climate mitigation policies are likely to make their own people worse off than if they did nothing at all.

Laden’s grid assumes that the costs of the climate apocalypse are potentially far greater than the costs of action, no matter how huge. He tries to cut through the arguments by getting the opinions from the leading scientific societies. To put it mildly, they do not currently provide strong scientific evidence for a potentially catastrophic problem. The NAS / Royal Society suggest a range of possible climate change outcomes, with only vague evidence for potentially catastrophic scenarios. It does not seem to back the huge potential costs of unmitigated climate change in the Stern Review. The NAAAS seems to provide vague banal opinions to support political advocacy rather than rigorous analysis based on empirical evidence that one would expect from the scientific community.

It would appear that the binary thinking on both the “science” and on “policy” leads to a dead end, and is leading to net harmful public policy.

What are the alternatives to binary thinking on climate change?

My purpose in looking at Greg Laden’s decision grid is not to destroy an alternative perspective, but to understand where the flaws are for better alternatives. As a former, slightly manic, beancounter, I would (like the Stern Review  and William Nordhaus) look at translating potential CAGW into costs. But then weight it according to a discount rate, and the strength of the evidence. In terms of policy I would similarly look at the likely expected costs of the implemented policies, against the actual expected harms foregone. As I have tried to lay out above, the costs of policy and indeed the potential costs of climate change are largely subjective. Further, those implementing policies might be boxed in by other priorities and various interest groups jostling for position.

But what of the expert scientist who can see the impending on-coming catastrophes to which I am blind and to which climate mitigation will be useless? It is to endeavor to pin down the where, when, type and magnitude of potential changes to climate. With this information ordinary people can adjust their plans. The challenge for those who believe there are real problems is to focus on the data from the natural world and away from inbuilt biases of the climate community. But the most difficult part is from such methods they may lose their beliefs, status and friends.

First is to obtain some perspective. In terms of the science, it is worth looking at the broad range of  different perspectives on the Philosophy of Science. The Stanford Encyclopedia of Philosophy article on the subject is long, but very up to date. In the conclusions, the references to Paul Hoyningen-Huene’s views on what sets science apart seems to be a way out of consensus studies.

Second, is to develop strategies to move away from partisan positions with simple principles, or contrasts, that other areas use. In Fundamentals that Climate Science Ignores I list some of these.

Third, in terms of policy, it is worthwhile having a theoretical framework in which to analyze the problems. After looking at Greg Craven’s video’s in 2010, I developed a graphical analysis that will be familiar to people who have studied Marshallian Supply and Demand curves of Hicksian IS-LM. It is very rough at the edges, but armed with it you will not fall in the trap of thinking like the AAAS that US policy will stop US-based climate change.

Fourth, is to look from other perspectives. Appreciate that other people might have other perspectives that you can learn from. Or alternatively they may have entrenched positions which, although you might disagree with, are powerless to overturn. It should then be possible to orientate yourself, whether as an individual or as part of a group, towards aims that are achievable.

Kevin Marshall

Sea Level Rise Acceleration as a sign of Impending Climate Apoclaypse

Global warming alarmism first emerged in the late 1980s, three decades ago. Put very simply, the claim is that climate change, resulting from human-caused increases in trace gases, is a BIG potential problem. The BIG solution is to control reduce global greenhouse gas emissions through a co-ordinated global action. The actual evidence shows a curious symmetry. The proponents of alarmism have failed to show that rises in greenhouse gas levels are making non-trivial difference on a global scale, and the aggregate impact of the policy proposals on global emissions, if fully implemented, will make a trivial difference to global emissions pathways. The Adoption of the Paris Agreement communique paragraph 17 clearly states the failure. My previous post puts forward reasons why the impact of mitigation policies will remain trivial.

In terms of an emerging large problem, the easiest to visualize, and the most direct impact from rising average temperatures is rising sea levels. Rising temperatures will lead to sea level rise principally through meltwater from the polar ice-caps and thermal expansion of the oceans. Given that sea levels have been rising since the last ice age, if a BIG climate problem is emerging then it should be detectable in accelerating sea level rise. If the alarmism is credible, then after 30 years of failure to implement the BIG solution, the unrelenting increases in global emissions and the accelerating rise in CO2 levels for decades, then there should be a clear response in terms of acceleration in the rate of sea level rise.

There is a strong debate as to whether sea-level rise is accelerating or not. Dr. Roy Spencer at WUWT makes a case for there being mild acceleration since about 1950. Based on the graph below (from Church and White 2013) he concludes:-

The bottom line is that, even if (1) we assume the Church & White tide gauge data are correct, and (2) 100% of the recent acceleration is due to humans, it leads to only 0.3 inches per decade that is our fault, a total of 2 inches since 1950.

As Judith Curry mentioned in her continuing series of posts on sea level rise, we should heed the words of the famous oceanographer, Carl Wunsch, who said,

“At best, the determination and attribution of global-mean sea-level change lies at the very edge of knowledge and technology. Both systematic and random errors are of concern, the former particularly, because of the changes in technology and sampling methods over the many decades, the latter from the very great spatial and temporal variability. It remains possible that the database is insufficient to compute mean sea-level trends with the accuracy necessary to discuss the impact of global warming, as disappointing as this conclusion may be.”

In metric, the so-called human element of 2 inches since 1950 is 5 centimetres. The total in over 60 years is less than 15 centimetres. The time period for improving sea defences to cope with this is way beyond normal human planning horizons. Go to any coastal strip with sea defences, such as the dykes protecting much of the Netherlands, with a measure and imagine increasing those defences by 15 centimetres.

However, a far more thorough piece is from Dave Burton (of Sealevel.info) in three comments. Below is his a repost of his comments.

Agreed. On Twitter, or when sloppy and in a hurry, I say “no acceleration.” That’s shorthand for, “There’s been no significant, sustained acceleration in the rate of sea-level rise, over the last nine or more decades, detectable in the measurement data from any of the longest, highest-quality, coastal sea-level records.” Which is right.

That is true at every site with a very long, high-quality measurement record. If you do a quadratic regression over the MSL data, depending on the exact date interval you analyze, you may find either a slight acceleration or deceleration, but unless you choose a starting date prior to the late 1920s, you’ll find no practically-significant difference from perfect linearity. In fact, for the great majority of cases, the acceleration or deceleration doesn’t even manage statistical significance.

What do I mean by “practically-significant,” you might wonder? I mean that, if the acceleration or deceleration continued for a century, it wouldn’t affect sea-level by more than a few inches. That means it’s likely dwarfed by common coastal processes like vertical land motion, sedimentation, and erosion, so it is of no practical significance.

For instance, here’s one of the very best Pacific tide gauges. It is at a nearly ideal location (mid-ocean, which minimizes ENSO effects), on a very tectonically stable island, with very little vertical land motion, and a very trustworthy, 100% continuous, >113-year measurement record (1905/1 through 2018/3):

As you can see, there have been many five-year to ten-year “sloshes-up” and “sloshes-down,” but there’s been no sustained acceleration, and no apparent effect from rising CO2 levels.

The linear trend is +1.482 ±0.212 mm/year (which is perfectly typical).

Quadratic regression calculates an acceleration of -0.00539 ±0.01450 mm/yr².

The minus sign means deceleration, but it is nowhere near statistically significant.

To calculate the effect of a century of sustained acceleration on sea-level, you divide the acceleration by two, and multiply it by the number of years squared, 100² = 10,000. In this case, -0.00539/2 × 10,000 = -27 mm (about one inch).

That illustrates a rule-of-thumb that’s worth memorizing: if you see claimed sea-level acceleration or deceleration numbers on the order of 0.01 mm/yr² or less, you can stop calculating and immediately pronounce it practically insignificant, regardless of whether it is statistically significant.

However, the calculation above actually understates the effect of projecting the quadratic curve out another 100 years, compared to a linear projection, because the starting rate of SLR is wrong. On the quadratic curve, the point of “average” (linear) trend is the midpoint, not the endpoint. So to see the difference at 100 years out, between the linear and quadratic projections, we should calculate from that mid-date, rather than the current date. In this case, that adds 56.6 years, so we should multiply half the acceleration by 156.6² = 24,524.

-0.00539/2 × 24,524 = -66 mm = -2.6 inches (still of no practical significance).

Church & White have been down this “acceleration” road before. Twelve years ago they published the most famous sea-level paper of all, A 20th Century Acceleration in Global Sea-Level Rise, known everywhere as “Church & White (2006).”

It was the first study anywhere which claimed to have detected an acceleration in sea-level rise over the 20th century. Midway through the paper they finally tell us what that 20th century acceleration was:

“For the 20th century alone, the acceleration is smaller at 0.008 ± 0.008 mm/yr² (95%).”

(The paper failed to mention that all of the “20th century acceleration” which their quadratic regression detected had actually occurred prior to the 1930s, but never mind that.)

So, applying the rule-of-thumb above, the first thing you should notice is that 0.008 mm/yr² of acceleration, even if correct, is practically insignificant. It is so tiny that it just plain doesn’t matter.

In 2009 they posted on their web site a new set of averaged sea-level data, from a different set of tide gauges. But they published no paper about it, and I wondered why not. So I duplicated their 2006 paper’s analysis, using their new data, and not only did it, too, show slight deceleration after 1925, all the 20th century acceleration had gone away, too. Even for the full 20th century their data showed a slight (statistically insignificant) deceleration.

My guess is that the reason they wrote no paper about it was that the title would have had to have been something like this:

Church and White (2009), Never mind: no 20th century acceleration in global sea-level rise, after all.

There is no real disagreement between the too accounts. Roy Spencer is saying that if the Church and White paper is correct there is trivial acceleration, Dave Burton is making a more general point about there being no statistically significant acceleration or deceleration in any data set.                                                At Key West in low-lying Florida, the pattern of near constant of sea level rise over the past century is similar to Honolulu. The rate of rise is about 50% more at 9 inches per century but more in line with the long-term global average from tide gauges. Given that Hawaii is a growing volcanic island, this should not come as a surprise.

I choose Key West from Florida, as supposedly from projecting from this real data, and climate models, the Miami-Dade Sea Level Rise Task Force produced the following Unified Sea Level Rise Projection.

The projections of significant acceleration in the rate of sea level rise are at odds with the historical data, but should be discernible as the projection includes over two decades of actual data. Further, as the IPCC AR5 RCP8.5 scenario is the projection without climate mitigation policy, the implied assumption for this report for adapting to a type of climate change is that climate mitigation policies will be completely useless. As this graphic is central to the report, it would appear it is the usage of the most biased projections that appears to be influencing public policy. Basic validation of theory against modelled trends in the peer-reviewed literature (Dr Roy Spencer) or against actual measured data (Dave Burton) appears to be rejected in favour of beliefs in the mainstream climate consensus.

The curious symmetry of climate alarmism between evidence for BIG potential climate problem and the lack of an agreed BIG mitigation policy solution is evident is sea level rise projections. Unfortunately, given that policy is based on the ridiculous projections, it is people outside of the consensus that will suffer. Expensive and unnecessary flood defences will be built and low-lying areas will be blighted by alarmist reports.

 

Kevin Marshall

 

Charles Moore nearly gets Climate Change Politics post Paris Agreement

Charles Moore of the Telegraph has long been one of the towering figures of the mainstream media. In Donald Trump has the courage and wit to look at ‘green’ hysteria and say: no deal (see also at GWPF, Notalotofpeopleknowthat and Tallbloke) he understands not only the impact of Trump withdrawing from the climate agreement on future global emissions, but recognizes that two other major developed countries – Germany and Japan – whilst committed to reduce their emissions and spending lots of money on renewables are also investing heavily in coal. So without climate policy, the United States is reducing its emissions, but with climate commitments, emissions in Japan and Germany are increasing their emissions. However, there is one slight inaccuracy in Charles Moore’s account. He states

As for “Paris”, this is failing, chiefly for the reason that poorer countries won’t decarbonise unless richer ones pay them stupendous sums.

It is worse than this. Many of the poorer countries have not said they will decarbonize. Rather they have said that they will use the money to reduce emissions relative to a business as usual scenario.

Take Pakistan’s INDC. In 2015 they estimate emissions were 405 MtCO2e, up from 182 in 1994. As a result of ambitious planned economic growth, they forecast a BAU of 1603 MtCO2e in 2030. However, they can reduce that by 20% with about $40 billion in finance. That is, with $40bn, average annual emissions growth from 2015-2030 will still be twice that of 1994-2015. Plus Pakistan would like $7-$14bn pa for adaptation to climate change. The INDC Table 7 summarizes the figures.

Or Bangladesh’s INDC. Estimated BAU increase in emissions from 2011 to 2030 is 264%. They will unconditionally cut this by 5% and conditionally by a further 15%. The BAU is 7.75% annual emissions growth, cut to 7.5% unconditionally and 6% with lots of finance. The INDC Table 7 summarizes the figures.

I do not blame either country for taking such an approach, or the many others adopting similar strategies. They are basically saying that they will do nothing that impedes trying to raise living standards through high levels of sustained economic growth. They will play the climate change game, so long as nobody demands that Governments compromise on serving the best interests of their peoples. If only the Government’s of the so-called developed nations would play similar games, rather than impose useless burdens on the people they are supposed to be serving.

There is another category of countries that will not undertake to reduce their emissions – the OPEC members. Saudi Arabia, Iran, Venezuela, Kuwait, UAE and Qatar have all made submissions. Only Iran gives a figure. It will unilaterally cut emissions by 4% against BAU. With the removal of “unjust sanctions” and some financial assistance and technology transfer it conditional offer would be much more. But nowhere is the BAU scenario stated in figures. The reason these OPEC countries will not play ball is quite obvious. To achieve the IPCC objective of constraining warming to 2°C according to McGlade and Ekins 2015 (The geographical distribution of fossil fuels unused when limiting global warming to 2°C) would mean leaving 75% of proven reserves of fossil fuels in the ground and all of the unproven reserves. I did an approximate breakdown by major countries last year, using the BP Statistical Review of World Energy 2016.

It does not take a genius to work out that meeting the 2°C climate mitigation target would shut down a major part of the economies of fossil fuel producing countries in about two decades. No-one has proposed either compensating them, or finding alternatives.

But the climate alarmist community are too caught up in their Groupthink to notice the obvious huge harms that implementing global climate mitigation policies would entail.

Kevin Marshall

Did Brexit Influence the General Election 2017 Result?

In the year following the EU Referendum, I wrote a number of posts utilizing Chris Hanretty’s estimates of the vote split by constituency for England and Wales. Hanretty estimates that 421 of the 573 constituencies in England and Wales voted to leave. These estimates were necessary as the vote was counted by different – and mostly larger – areas than the parliamentary constituencies.

Politically, my major conclusion was that it was the Labour Party who could potentially suffer more from Brexit. There are two major reasons for this situation.

First, is that the Labour constituencies had a far greater spread of views than the Conservative constituencies. This is in both the divergence between regions and the disproportionate numbers of constituencies that are were either extreme Remain or extreme Leave in the referendum. Figure 1 is for the result for constituencies with Conservative MPs in 2016, and Figure 2 for constituencies with Labour MPs.

Figure 1: Constituencies in England and Wales with Conservative MPs in 2016, by estimated Leave or Remain Band. 

Figure 2: Constituencies in England and Wales with Labour Party MPs in 2016, by estimated Leave or Remain Band. 

In particular, London, where much of the current Labour Leadership are based, has views on the EU diametrically opposed views to the regions where most of the traditional Labour vote resides. Further analysis, from July 2016, is here.

Second, is the profile of the Leave supports. Based on an extensive poll conducted by Lord Ashcroft on EU Referendum day, Leave support was especially strong on those retired on a State Pension, council and housing association tenants, those whose formal education did not progress beyond secondary school, and the C2DEs. That is, groups that traditionally disproportionately vote Labour. Further details, from May 2017, are here.

Yet, the results of the snap General Election in June 2017 suggest that it was the Conservatives that suffered from Brexit. Despite their share of the popular vote increasing by over 5%, to the highest share in 25 years, they had a net loss of 13 seats and lost their majority. Labour increased their share of the vote by 10%, but only had a net gain of 30 seats.

Do the positions on Brexit appear to have had an influence? The Conservatives were seeking a stronger mandate for the Brexit negotiations, whilst Labour strongly avoided taken a firm position one way or the other. Chris Hanretty has revised his estimates, with the number of Leave-majority constituencies in England and Wales reduced from 421 to 401. The general picture is unchanged from the previous analysis. I have taken these revised figures, put them into the eight bands used previously and compared to the full election results available from the House of Commons Library.

The main seat results are in Figure 3.

Main points from Figure 3 (for England and Wales) are

  • Conservatives had a net loss of 25 seats, 14 of which likely voted Remain in the EU Referendum and 11 likely voted Leave. Remain seats reduced by 18% and Leave seats by 4%.
  • All 6 gains from Labour were in strongly Remain constituencies. This includes Copeland, which was gained in a by-election in early 2017 and retained in the General Election.
  • Labour had a net gain of 24 seats, 13 of which likely voted Remain in the EU Referendum and 11 likely voted Leave. Remain seats increased by 16% and Leave seats by 7%.

Figure 4 is the average percentage change in the constituency vote from 2015 to 2017 for the Conservative Party.

Main point from Figure 4 for the Conservative Party is

  • The estimated Referendum vote is a strong predictor of change in Conservative Party vote share from 2015 to 2017 General Election.

Figure 5 is the average percentage change in the constituency vote from 2015 to 2017 for the Labour Party.

Main points from Figure 5 for the Labour Party are

  • Overall average constituency vote share increased by 10% on the 2015 General Election.
  • In the 6 seats lost to the Conservatives, Labour’s share of the vote increased.
  • In every area, Labour increased its share of the constituency vote with one exception. In the 6 seats that the Liberal Democrats gained from the Conservatives, the Labour share of the vote was on average unchanged. This suggests some tactical voting.
  • In Conservative “hold” seats Labour’s increase in vote share did not have a “Remain” bias.
  • In Labour “hold” seats Labour’s increase in vote share had a strong “Remain” bias.

In summary, it would appear that the Conservatives in implementing Brexit have mostly suffered at the ballot in Remain areas. Labour, in being the Party of Opposition and avoiding taking a clear position on Brexit, benefited from the Remain support without being deserted by the Leave vote. I will leave it for another day – and for others – to draw out further conclusions.

Kevin Marshall

Update 23rd May

Whilst writing the above, I was unaware of a report produced by political pundit Prof John Curtice last December Has Brexit Reshaped British Politics?

Key findings

In the 2017 election the Conservatives gained support amongst Leave voters but fell back amongst Remain supporters. Labour, in contrast, advanced more strongly amongst Remain than amongst Leave voters.

That is pretty much my own findings by a different method. Both methods can produce different insights. My own approach can give regional analysis.

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