What would constitute AGW being a major problem?

Ron Clutz has an excellent post. This time on he reports on A Critical Framework for Climate Change. In the post Ron looks at the Karoly/Tamblyn–Happer Dialogue on Global Warming at Best Schools particularly at Happer’s major statement. In my opinion these dialogues are extremely useful, as (to use an old-fashioned British term) are antagonists are forces by skilled opponents to look at the issues in terms of a level playing field. With the back and forth of the dialogue, the relative strengths and weaknesses are exposed. This enables those on the outside to compare and contrast for themselves. Further, as such dialogues never fully resolve anything completely, can point to new paths to develop understanding. 

Ron reprints two flow charts. Whilst the idea is of showing the issues in this way to highlight the issues is extremely useful correct. I have issues with the detail. 

 

In particular on the scientific question “Is it a major problem?“, I do not think the “No” answers are correct.
If there was no MWP, Roman warming, or Bronze Age warming then this would be circumstantial evidence for current warming being human-caused. If there has been 3 past warming phases at about  1000, 2000 and 3000 years ago, then this is strong circumstantial evidence that current warming is at least in part due to some unknown natural or random factors. Without any past warming phases at all then it would point to the distinctive uniqueness of the current warming, but that still does not mean not necessarily mean that it is a major net problem. There could be benefits as well as adverse consequences to warming. But the existence of previous warming phases under many studies and only being able to claim by flawed statistics that the majority of warming since 1950 in human-caused (when there was some net warming for at least 100 years before that suggests a demonstrable marginal impact of human causes far less than 100% of total warming. Further there is issues with

(a) the quantity of emissions a trace gas to raise that the atmospheric levels by a unit amount

(b) the amount of warming from a doubling of the trace gas – climate sensitivity

(c) the time taken for rises on a trace gas to raise temperatures.

As these are all extremely difficult to measure, so a huge range of equally valid answers. It is an example of the underdetermination of scientific theory.

At the heart of the underdetermination of scientific theory by evidence is the simple idea that the evidence available to us at a given time may be insufficient to determine what beliefs we should hold in response to it.

But even if significant human-caused warming can be established, this does not constitute a major problem. Take sea-level rise. If it could be established that human-caused warming was leading to sea level rise, this may not, on a human scale, be a major problem. At current rates sea levels from the satellites are rising on average by 3.5mm per year. The average adjusted level from the tide gauges are less than that – and the individual tide gauges show little or no acceleration in the last century. But if that rate accelerated to three or four times that level, it is not catastrophic in terms of human planning timescales. 

The real costs to humans are expressed in values. The really large costs of climate change are based not so much on the physical side, but implausible assumptions about the lack of human responses to ongoing changes to the environment. In economics, the neoclassical assumptions of utility maximisation and profit maximisation are replaced by the dumb actor assumption.

An extreme example I found last year. In Britain it was projected that unmitigated global warming could lead to 7000 excess heatwave deaths in the 2050s compared to today. The projection was most of these deaths would occur in over 75s dying in hospitals and care homes. The assumption was that medical professionals and care workers would carry on treating those in the care in the same way as currently, oblivious to increasing suffering and death rates.  

Another extreme example from last year was an article in Nature Plants (a biology journal) Decreases in global beer supply due to extreme drought and heatThere were at least two examples of the dumb actor assumption. First was failure by farmers to adjust output according to changing yields and hence profits. For instance in Southern Canada (Calgary / Edmonton) barley yields under the most extreme warming scenario were projected to fall by around 10-20% by the end of the century. But in parts of Montana and North Dakota – just a few hundred miles south – they would almost double. It was assumed that farmers would continue producing at the same rates regardless, with Canadian farmers making losses and those in Northern USA making massive windfall profits. The second was in retail. For instance the price of a 500ml bottle of beer in Ireland was projected to increase under the most extreme scenario in Ireland by $4.84 compared to $1.90 in neighbouring Britain. Given that most of the beer sold comes from the same breweries; current retail prices in UK and Ireland are comparable (In Ireland higher taxes mean prices up to 15% higher); cost of a 500ml bottle is about $2.00-$2.50 in the UK; and lack of significant trade barriers, there is plenty of scope with even a $1.00 differential for an entrepreneur to purchase a lorry load of beer in the UK and ship it over the Irish Sea. 

On the other hand nearly of the short-term forecasts of an emerging major problem have turned out to be false, or highly extreme. Examples are

  • Himalayan Glaciers will disappear by 2035
  • Up to 50% reductions in crop yields in some African Countries by 2020
  • Arctic essentially ice-free in the summer of 2013
  • Children in the UK not knowing what snow is a few years after 2000
  • In the UK after 2009, global warming will result in milder and wetter summers

Another example of the distinction between a mere difference and a major problem is the February weather. Last week the UK experienced some record high daytime maximum temperatures of 15-20C. It was not a problem. In fact, accompanied by very little wind and clear skies it was extremely pleasant for most people. Typical weather for the month is light rain, clouds and occasional gales. Children on half-term holidays were able to play outside, and when back in school last week many lessons were diverted to the outdoors. Over in Los Angeles, average highs were 61F (16C) compared to  February average of 68F (20C). This has created issues for the elderly staying warm, but created better skiing conditions in the mountains. More different than a major problem. 

So in summary, for AGW to be a major problem it is far from sufficient to establish that most of the global warming is human caused. It is necessary to establish that the impact of that warming is net harmful on a global scale.

Kevin Marshall

 

Two false claims on climate change by the IPPR

An IPPR report  This is a crisis: Facing up to the age of environmental breakdown published yesterday, withing a few hours received criticism from Paul Homewood at notalotofpeopleknowthat, Paul Matthews at cliscep and Andrew Montford at The GWPF.  has is based on an April 2018 paper by billionaire Jeremy Grantham. Two major issues, that I want cover in this post are contained in a passage on page 13.

Climate Change : Average global surface temperature increases have accelerated, from an average of 0.007 °C per year from 1900–1950 to 0.025 °C from 1998–2016 (Grantham 2018). ……. Since 1950, the number of floods across the world has increased by 15 times, extreme temperature events by 20 times, and wildfires sevenfold (GMO analysis of EM-DAT 2018).

These two items are lifted from an April 2018 paper The Race of Our Lives Revisited by British investor Jeremy Grantham CBE. I will deal with each in turn.

Warming acceleration

The claim concerning how warming has accelerated comes from Exhibit 2 of The Race of Our Lives Revisited.

The claimed Gistemp trends are as follows

1900 to 1958  – 0.007 °C/year

1958 to 2016  – 0.015 °C/year

1998 to 2016  – 0.025 °C/year

Using the Skeptical Science trend calculator for Gistemp I get the following figures.

1900 to 1958  – 0.066 ±0.024 °C/decade

1958 to 2016  – 0.150 ±0.022 °C/decade

1998 to 2016  – 0.139 ±0.112 °C/decade

That is odd. Warming rates seem to be slightly lower for 1998-2016 compared to 1958-2016, not higher. This is how Grantham may have derived the incorrect 1998-2016 figure.

For 1998-2016 the range of uncertainty is 0.003 to 0.025 °C/year.

It would appear that the 1900 to 1958 & 1958 to 2016 warming rates are as from the trend calculator, whilst the 1998 to 2016 warming rate of 0.025 °C/year is at the top end of the 2σ uncertainty range.

Credit for spotting this plausible explanation should go to Mike Jackson.

Increase in climate-related disasters since 1950

The IPPR report states

Since 1950, the number of floods across the world has increased by 15 times, extreme temperature events by 20 times, and wildfires sevenfold

Exhibit 7 of The Race of Our Lives Revisited.

The 15 times “Floods” increase is for 2001-2017 compared to 1950-1966.
The 20 times “Extreme Temperature Events” increase is for 1996-2017 compared to 1950-1972.
The 7 times “Wildfires” increase is for 1984-2017 compared to 1950-1983.

Am I alone in thinking there is something a bit odd in the statement about being from 1950? Grantham is comparing different time periods, yet IPPR make it appear the starting point is from a single year?

But is the increase in the data replicated in reality?

Last year I downloaded all the EM-DAT – The International Disasters Database – from 1900 to the present day. Their disaster types I have classified into four categories.

Over 40% are the “climate”-related disaster types from Grantham’s analysis. Note that this lists the number of “occurrences” in a year. If, within a country in a year there is more than one occurrence of a disaster type, they are lumped together.

I have split the number of occurrences by the four categories by decade. The 2010s is only for 8.5 years.

Climate” disasters have increased in the database. Allowing for 8.5 years in the current decade, compared to 1900-1949, “Climate” disasters are 65 times more frequent. Similarly epidemics are 47 times more frequent, geological events 16 times and “other” disasters 34 times.

Is this based on reality, or just vastly improved reporting of disasters from the 1980s? The real impacts are indicated by the numbers of reports deaths. 

The number of reported disaster deaths has decreased massively compared to the early twentieth century in all four categories, despite the number of reported disasters increasing many times. Allowing for 8.5 years in the current decade, compared to 1900-1949, “Climate” disaster deaths are down 84%. Similarly epidemic deaths are down by 98% and”other” disasters down by 97%. Geological disaster deaths are, however, up by 27%. The reported 272,431 deaths in the 2010s that I have classified under “Geology” includes the estimated 222,570 estimated deaths in the 2010 Haitian Earthquake.

If one looks at the death rate per reported occurrence, “Climate” disaster death rates have declined by 97.7% between 1900-1949 and the 2010s. Due to the increase in reporting, and the more than doubling of the world population, this decline is most likely understated. 

The Rôle of Progressives in Climate Mitigation

The IPPR describes itself as The Progressive Policy Think Tank. From the evidence of the two issues above they have not actually thought about what they are saying. Rather they have just copied the highly misleading data from Jeremy Grantham. There appears to be no real climate crisis emerging when one examines the available data properly. The death rate from extreme weather related events has declined by at least 97.7% between the first half of the twentieth century  and the current decade. This is a very important point for policy. Humans have adapted to the current climate conditions, just have they have reduced the impact of infectious diseases and are increasingly adapting to the impacts of earthquakes and tsunamis. If the climate becomes more extreme, or sea level rise accelerates significantly humans will adapt as well.

There is a curious symmetry here between the perceived catastrophic problem and the perceived efficacy of the solution. That for governments to reduce global emissions to zero. The theory is that rising human emissions, mostly from the burning of fossil fuels, are going to cause dangerous climate change. Global emissions involve 7600 million people in nearly 200 countries. Whatever the UK does, with less than 1% of the global population and less than 1% of global emissions makes no difference to global emissions.

Globally, there are two major reasons that reducing global emissions will fail.

First is that developing countries, with 80%+ of the global population and 65% of emissions, are specifically exempted from any obligation to reduce their emissions. (see Paris Agreement Articles 2.1(a), 2.2 and 4.1) Based on the evidence of the UNEP Emissions GAP Report 2018, and from the COP24 Katowizce meeting in December, there is no change of heart in prospect.

Second is that the reserves of fossil fuels, both proven and estimated, are both considerable and spread over many countries. Reducing global emissions to zero in a generation would mean leaving in the ground fossil fuels that provide a significant part of government revenue in countries such as Russia, Iran, Saudi Arabia, and Turkmenistan. Keeping some fossil fuels in the ground in the UK, Canada, Australia or the United States will increase the global prices and thus the production elsewhere.

The IPPR is promoting is costly and ideological policies in the UK, that will have virtually zero benefits for future generations in terms of climate catastrophes averted. In my book such policies are both regressive and authoritarian, based on failing to understand to the distinction between the real very marginal impacts of policy and the theoretical total impacts.

If IPPR, or even the climate academics, gave proper thought to the issue, then they would conclude the correct response will be to more accurately predict the type, timing, magnitude and location of future climate catastrophes. This information will help people on the ground adapt to those circumstances. In the absence of that information, the best way of adapting to changing climate is the same way as people have been able to adapt to extreme events, whether weather or geological. That is through sustained long-term economic growth, in the initial stages promoted by cheap and reliable energy sources. If there is a real environmental breakdown on its way, the Progressives, with their false claims and exaggerations, will be best kept well away from the scene. Their ideological beliefs render them incapable of getting a rounded perspective on the issues and the damage their policies will cause.

Kevin Marshall

East Antarctica Glacial Melting through the filter of BBC reporting

An indication of how little solid evidence there is for catastrophic anthropogenic global warming comes from a BBC story story carried during the COP24 Katowice conference in December. It carried the headline “East Antarctica’s glaciers are stirring” and began

Nasa says it has detected the first signs of significant melting in a swathe of glaciers in East Antarctica.

The region has long been considered stable and unaffected by some of the more dramatic changes occurring elsewhere on the continent.

But satellites have now shown that ice streams running into the ocean along one-eighth of the eastern coastline have thinned and sped up.

If this trend continues, it has consequences for future sea levels.

There is enough ice in the drainage basins in this sector of Antarctica to raise the height of the global oceans by 28m – if it were all to melt out.

Reading this excerpt one could draw a conclusion that the drainage basins on “one-eighth of the eastern coastline” have sufficient ice to raise sea levels by 28m. But that is not the case, at the melting of all of Antarctica would only raise sea levels by 60m. The map reproduced from NASA’s own website is copied below.

The study area is no where near a third or more of Antarctica. Further, although it might be one eighth of the eastern coastline, it is far less than the coastline of East Antarctica, which is two-thirds or more of the total area.

NASA does not mention the 28m of potential sea level rise in its article, only 3 metres from the disappearance of the Totten Glacier. So how large is this catchment area? From a Washington Post article in 2015 there is a map.

The upper reaches of the catchment area may include Vostok Station, known for being the location of the lowest reliably measured natural temperature on Earth of −89.2 °C (−128.6 °F). The highest temperature recorded in over 60 years is −14.0 °C. In other words, what is being suggested is that a slight increase in ocean current temperatures will cause, through gravity, the slippage of a glaciers hundreds of miles long into the ocean covering ten times the Totten Glacier catchment.

The Guardian article of 11th December also does not mention the potential 28m of sea level rise. This looks to be an insertion by the BBC making the significance of the NASA research appear orders of magnitude more important than the reality.

The BBC’s audio interview with Dr Catherine Walker gives some clarification of the magnitude of the detected changes. At 2.30 there is a question on the scale of the changes.

Physically the fastest changing one is Vincennes Bay which is why we were looking at that one. And, for instance, in 2017 they changed average about .5 meters a year. So that is pretty small.

Losing 0.5 metres out of hundreds of thousands of length is not very significant. It just shows the accuracy of the measurements. Dr Walker than goes on to relate this to Fleming Glacier in West Antarctica, which is losing about 8 meters a year. The interview continues:-

Q. But the point is that compared to 2008 there is definitely an acceleration here.
A. Yes. We have shown that looking at 2008 and today they have increased their rate of mass loss by 5 times.
Q. So it is not actually a large signal is it? How do we describe this then. Is this East Antarctica waking up? Is it going to become a West Antarctica here in a few decades time or something?
A. I think its hard, but East Antarctica given how cold it is, and it still does have that layer insulating it from warm Antarctic circumpolar current … that really eats away at West Antarctica. We’ve seen it get up under Totten, so of you know, but it is not continuous you know. Every so often it comes up and (…….) a little bit.

There is acceleration detected over a decade, but for the disappearance of the glacier would take tens or hundreds of thousands of years. 

Walker goes into say that for the small changes to further increase

you would have to change the Antarctic circumpolar current significantly. But the fact that you are seeing these subtle changes I guess you could say Antartica is waking up.
We are seeing these smaller glaciers – which couldn’t be seen before – see them also respond to the oceans. So the oceans are warming enough now to make a real difference in these small glaciers.

This last carry-away point – about glaciers smaller than Totten – is not related to the earlier comments. It is not ocean warming but movements in the warm Antarctic circumpolar current that seem to impact on West Antarctica and this small section of the East Antarctica coast. That implies a heat transfer from elsewhere could be the cause as much as additional heat.

This account misses out on another possible cause of the much higher rates of glacier movement in West Antarctica. It might be just a spooky coincidence, but the areas of most rapid melt seem to have a volcanoes beneath them.

Yet even these small movements in glaciers should be looked at in the context of net change in ice mass. Is the mass loss from moving glaciers offset by snow accumulation?
In June 2018 Jay Zwally claimed his 2015 paper showing net mass gain in Antarctica is confirmed in a forthcoming study. It is contentious (as is anything that contradicts the consensus. But the mainstream estimate of 7.6 mm of sea-level rise over 25 years is just 0.30mm a year. It is in Eastern Antarctica that the difference lies. 

From the Daily Caller

Zwally’s 2015 study said an isostatic adjustment of 1.6 millimeters was needed to bring satellite “gravimetry and altimetry” measurements into agreement with one another.

Shepherd’s paper cites Zwally’s 2015 study several times, but only estimates eastern Antarctic mass gains to be 5 gigatons a year — yet this estimate comes with a margin of error of 46 gigatons.

Zwally, on the other hand, claims ice sheet growth is anywhere from 50 gigatons to 200 gigatons a year.

In perspective the Shepard study has a central estimate of 2,720 billion tonnes of ice loss in 25 years leaving about 26,500,000 billion tonnes. That is a 0.01% reduction. 

As a beancounter I prefer any study that attempts to reconcile and understanding differing data sets. It is looking at differences (whether of different data sets; different time periods; hypothesis or forecast and empirical reality, word definitions etc.) that one can greater understanding of a subject, or at least start to map out the limits of one’s understanding. 

On the measure of reconciliation, I should tend towards the Zwally estimates with isostatic adjustment. But the differences are so small in relation to the data issues that one can only say that there is more than reasonable doubt about against the claim Antarctica lost mass in the last 25 years. The data issues are most clearly shown by figure 6 Zwally et al 2015, reproduced below.

Each colour band is for 25mm per annum whereas the isostatic adjustment is 1.6mm pa. In the later period the vast majority of Antarctica is shown as gaining ice, nearly all at 0-50mm pa. The greatest ice loss from 1992 to 2008 is from West Antarctica and around the Totten Glacier in East Antarctica. This contradicts the BBC headline “East Antarctica’s glaciers are stirring“, but not the detail of the article nor the NASA headline “More glaciers in East Antarctica are waking up“.

Concluding Comments

There are a number of concluding statements that can be made about the BBC article, along with the context of the NASA study.

  1. The implied suggestion by the BBC that recent glacier loss over a decade in part of East Antarctica could be a portent to 28m of sea level rise is gross alarmism. 
  2. The BBC’s headline “East Antarctica’s glaciers are stirring” implies the melt is new in area, but the article makes clear this is not the case. 
  3. There is no evidence put forward in the BBC, or elsewhere, to demonstrate that glacier melt in Antarctica is due to increased global ocean heat content or due to average surface temperature increase. Most, or all, could be down to shifts in ocean currents and volcanic activity. 
  4. Most, or all of any ice loss from glaciers to the oceans will be offset by ice gain elsewhere.  There are likely more areas gaining ice than losing it and overall in Antarctica there could be a net gain if ice.
  5. Although satellites can perform measures with increasing accuracy, especially glacier retreat and movement, the fine changes in ice mass are so small that adjustment and modelling assumptions for East Antarctica can make the difference between net gain or loss.

The NASA study of some of East Antarctica’s glaciers has to be understood in the context of when it was published. It was during the COP24 conference to control global emissions, with the supposed aim of saving the world from potential dangerous human-caused climate change. The BBC dressed it up the study make it appear that the study was a signal of this danger, when it was a trivial, localized (and likely) example of natural climate variation. The prominence given to such a study indicates the lack of strong evidence for a big problem that could justify costly emissions reduction policies. 

Kevin Marshall

Natural Variability in Alaskan Glacier Advances and Retreats

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

The caption caught my eye

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

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

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

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

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

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

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

Kevin Marshall

UNEP Emissions Gap Report 2018 Part 1 – The BBC Response

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

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

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

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

In the report Figure 2.1 states

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

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

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

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

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

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

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

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

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

Kevin Marshall

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

Introduction

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

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

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

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

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

The aim of constraining warming to 1.5 or 2°C

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

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

The Paris Agreement states in Article 2

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

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

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

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

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

 Initial assumptions

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

This despite the 2013 AR5 WG1 SPM stating on page 16

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

And stating in a footnote on the same page.

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

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

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

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

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

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

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

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

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

These are restrictive assumptions made for ease of calculations.

Some calculations

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

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

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

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

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

100 Months and Counting Campaign 2008

Trust, yet verify has a post We are Doomed!

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

The 2006 Stern Review

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

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

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

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

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

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

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

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

IPCC AR4 Report Synthesis Report Table 5.1

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

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

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

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

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

Note the following

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

IPCC AR5 Report Highest Level Summary

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

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

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

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

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

Now for some calculations.

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

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

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

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

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

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

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

But there are issues

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

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

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

From this a further assumption is made when considering AR5.

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

UNEP Emissions Gap Report 2014

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

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

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

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

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

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

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

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

A new assumption is thus required to achieve emissions targets.

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

A Lower Level Perspective from AR5

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

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

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

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

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

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

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

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

Conclusions

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

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

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

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

Kevin Marshall

Increasing Extreme Weather Events?

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

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

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

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

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

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

 

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

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

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

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

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

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

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

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

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

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

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

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

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

Kevin Marshall

Excess Deaths from 2018 Summer Heatwaves

Last month I looked at the claims by the UK Environmental Audit Committee warning of 7,000 heat-related deaths in the 2050s, finding it was the result a making a number of untenable assumptions. Even if the forecast turned out to be true, cold deaths would still be more than five times the hot deaths. With the hottest summer since 1976, it is not surprising that there have been efforts to show there are excess heat deaths.

On the 6th August, The Daily Express headlined UK heatwave turns KILLER: 1,000 more people die this summer than average as temps soar.

Deaths were up in all seven weeks from June 2 to July 20, which saw temperatures reach as high as 95F (35C).

A total of 955 people more than the average have died in England and Wales since the summer began, according to the Office for National Statistics (ONS).

On the 3rd August the Guardian posted Deaths rose 650 above average during UK heatwave – with older people most at risk.

The height of the heatwave was from 25 June to 9 July, according to the Met Office, a run of 15 consecutive days with temperatures above 28C. The deaths registered during the weeks covering this period were 663 higher than the average for the same weeks over the previous five years, a Guardian analysis of data from the Office of National Statistics shows.

Note the Guardian’s lower figure was from a shorter time period.

I like to put figures in context, so I looked up the ONS Dataset:Deaths registered monthly in England and Wales

There they have detailed data from 2006 to July 2018. Estimating the excess deaths from these figures needs some estimation of other factors. However, some indication of excess deaths can be gleaned from taking the variation from the average. In July 2018 there were 40,624 recorded deaths, as against an average of 38,987 deaths in July in the years 2006-2018. There were therefore 1,637 deaths more than average. I have charted the variation from average for each year.

There were above average deaths in July 2018, but there similar figure in the same month in 2014 and 2015. Maybe the mean July temperatures from the Central England Temperature Record show a similar variation?

Not really. July 2006 had high mean temperatures and average deaths, whilst 2015 had low mean temperatures and higher than average deaths.

There is a further element to consider. Every month so far this year has had higher than average deaths. Below I have graphed the variation by month.

January is many times more significant than July. In the first seven months of this year there were 30,000 more deaths recorded than the January-July average for 2006 to 2018. But is this primarily due to the cold start to the year followed by a barbecue summer? Looking at the variations from average 300,000 deaths for the period January to July period, it does not seem this is the case.

Looking at individual months, if extreme temperatures alone caused excess deaths I would expect an even bigger peak during in January 2010 when there was record cold than this year. In January 2010 there were 48363 recorded deaths, against 64157 in January 2018 and a 2006-2018 average of 52383. Clearly there is a large seasonal element to deaths as the average for July is 39091, or three-quarters of the January level. But discerning the temperature related element is extremely tricky, and any estimates of excess deaths to a precise number should be treated with extreme caution.

Kevin Marshall

Milk loss yields down to heat stress

Last week, Wattupwiththat post “Climate Study: British Children Won’t Know What Milk Tastes Like”. Whilst I greatly admire Anthony Watts, I think this title entirely misses the point.
It refers to an article at the Conservation “How climate change will affect dairy cows and milk production in the UK – new study” by two authors at Aberystwyth University, West Wales. This in turn is a write up of a Plos One article published in May “Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom“. The reason I disagree is that even with very restrictive assumptions, this paper shows that even with large changes in temperature, the unmitigated costs of climate change are very small. The authors actually give some financial figures. Referring to the 2190s the PLOS One abstract ends:-

In the absence of mitigation measures, estimated heat stress-related annual income loss for this region by the end of this century may reach £13.4M in average years and £33.8M in extreme years.

The introduction states

The value of UK milk production is around £4.6 billion per year, approximately 18% of gross agricultural economic output.

For the UK on average Annual Milk Loss (AML) due to heat stress is projected to rise from 40 kg/cow to over 170 kg/cow. Based on current yields it is from 0.5% to 1.8% in average years. The most extreme region is the south-east where average AML is projected to rise from 80 kg/cow to over 320 kg/cow. That is from 1% to 4.2% in average years. That is, if UK dairy farmers totally ignore the issue of heat stress for decades the industry could see average revenue losses from heat stress rise on average from £23m to £85m. The financial losses are based on constant prices of £0.30 per litre.

With modeled estimates over very long periods, it is worth checking the assumptions.

Price per liter of milk

The profits are based upon a constant price of £0.30 a liter. But prices can fluctuate according to market conditions. Data on annual average prices paid is available from AHDB Dairy, ” a levy-funded, not-for-profit organisation working on behalf of Britain’s dairy farmers.” Each month, since 2004, there are reported the annual average prices paid by dairies over a certain size available here. That is 35-55 in any one month. I have taken the minimum and maximum prices for reported in June each year and shown in Figure 1.

Even annual average milk prices fluctuate depending on market conditions. If milk production is reduced in summer months due to an unusual heat wave causing heat stress, ceteris paribus, prices will rise. It could be that a short-term reduction in supply would increase average farming profits if prices are not fixed. It is certainly not valid to assume fixed prices over many decades.

Dumb farmers

From the section in the paper “Milk loss estimation methods

It was assumed that temperature and relative humidity were the same for all systems, and that no mitigation practices were implemented. We also assumed that cattle were not significantly different from the current UK breed types, even though breeding for heat stress tolerance is one of the proposed measures to mitigate effects of climate change on dairy farms.

This paper is looking at over 70 years in the future. If heatwaves were increasing, so yields falling and cattle were suffering, is it valid to assume that farmers will ignore the problem? Would they not learn from areas with more extreme heatwaves in summer elsewhere such as in central Europe? After all in the last 70 years (since the late 1940s) breeding has increased milk yields phenomenally (from AHDB data, milk yields per cow have increased 15% from 2001/2 to 2016/7 alone) so a bit of breeding to cope with heatwaves should be a minor issue.

The Conversation article states the implausible assumptions in a concluding point.

These predictions assume that nothing is done to mitigate the problems of heat stress. But there are many parts of the world that are already much hotter than the UK where milk is produced, and much is known about what can be done to protect the welfare of the animals and minimise economic losses from heat stress. These range from simple adaptations, such as the providing shade, to installing fans and water misting systems.

Cattle breeding for increased heat tolerance is another potential, which could be beneficial for maintaining pasture-based systems. In addition, changing the location of farming operations is another practice used to address economic challenges worldwide.

What is not recognized here is that farmers in a competitive market have to adapt in the light of new information to stay in business. That is the authors are telling farmers what they will be fully aware of to the extent that their farms conform to the average. Effectively assuming people and dumb, then telling them obvious, is hardly going to get those people to take on board one’s viewpoints.

Certainty of global warming

The Conversation article states

Using 11 different climate projection models, and 18 different milk production models, we estimated potential milk loss from UK dairy cows as climate conditions change during the 21st century. Given this information, our final climate projection analysis suggests that average ambient temperatures in the UK will increase by up to about 3.5℃ by the end of the century.

This warming is consistent with the IPCC global average warming projections using RCP8.5 non-mitigation policy scenario. There are two alternative, indeed opposite, perspectives that might lead rational decision-makers to think this quantity of warming is less than certain.

First, the mainstream media, where the message being put out is that the Paris Climate Agreement can constrain global warming to 2°C or 1.5°C above the levels of the mid-nineteenth century. With around 1°C of warming already if it is still possible to constrain additional global warming to 0.5°C, why should one assume that 3.5°C of warming for the UK is more than a remote possibility in planning?

Second, one could look at the track record of global warming projections from the climate models. The real global warming scare kicked-off with James Hansen’s testimony to Congress in 1988. Despite actual greenhouse gas emissions being closely aligned with rapid warming, actual global warming has been most closely aligned with the assumption of the impact of GHG emissions being eliminated by 2000. Now, if farming decision-makers want to still believe that emissions are the major driver of global warming, they can find plenty of excuses for the failure linked from here. But, rational decision-makers tend to look at the track record and thus take consistent decision-makers with more than a pinch of salt.

Planning horizons

The Conversation article concludes

(W)e estimate that by 2100, heat stress-related annual income losses of average size dairy farms in the most affected regions may vary between £2,000-£6,000 and £6,000-£14,000 (in today’s value), in average and extreme years respectively. Armed with these figures, farmers need to begin planning for a hotter UK using cheaper, longer-term options such as planting trees or installing shaded areas.

This compares to the current the UK average annual dairy farm business income of £80,000 according to the PLOS One article.

There are two sides to investment decision-making. There are potential benefits – in this case avoidance of profit loss – netted against the potential benefits. ADHB Dairy gives some figures for the average herd size in the UK. In 2017 it averaged 146 cows, almost double the 75 cows in 1996. In South East England, that is potentially £41-£96 a cow, if the average herd size there is same as the UK average. If the costs rose in a linear fashion, that would be around 50p to just over a pound a year per cow in the most extreme affected region. But the PLOS One article states that costs will rise exponentially. That means there will be no business justification for evening considering heat stress for the next few decades.

For that investment to be worthwhile, it would require the annual cost of mitigating heat stress to be less than these amounts. Most crucially, rational decision-makers apply some sort of NPV calculation to investments. This includes a discount rate. If most of the costs are to be incurred decades from now – beyond the working lives of the current generation of farmers – then there is no rational reason to take into account heat stress even if global warming is certain.

Summary

The Paper Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom makes a number of assumptions to reach its headline conclusion of decreased milk yields due to heat stress by the end of the century. The assumption of constant prices defies the economic reality that prices fluctuate with changing supply. The assumption of dumb farmers defies the reality of a competitive market, where they have to respond to new information to stay in business. The assumption of 3.5°C warming in the UK can be taken as unlikely from either the belief Paris Climate Agreement with constrain further warming to 1°C or less OR that the inability of past climate projections to conform to the pattern of warming should give more than reasonable doubt that current projections are credible.  Further the authors seem to be unaware of the planning horizons of normal businesses. Where there will be no significant costs for decades, applying any sort of discount rate to potential investments will mean instant dismissal of any consideration of heat stress issues at the end of the century by the current generation of farmers.

Taking all these assumptions together makes one realize that it is quite dangerous for specialists in another field to take the long range projections of climate models and apply to their own areas, without also considering the economic and business realities.

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 growth 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.