THE BRIGGS DOCUMENT : LINK: https://www.thegwpf.org/content/uploads/2021/04/Briggs-Climate-Attribution.pdf

THIS IS A BRIEF VERSION OF WHAT THE BRIGGS DOCUMENT SAYS. FOR THE FULL TEXT PLEASE VISIT THE PDF FILE LINKED ABOVE.

ABSTRACT: WE SUGGEST THAT A CRITICAL EVALUATION OF EVENT ATTRIBUTION SUCH AS THE ANALYSIS OFFERED BY BRIGGS BELOW, SHOULD BEGIN WITH ITS ORIGINS IN THE WARSAW INTERNATIONAL MECHANISM UNITED NATIONS MEETING OF 2013 WHERE THE IDEA WAS BORN BUT IN A VERY DIFFERENT CONTEXT THAN THE WAY IT IS USED TODAY.

BACK THEN THE UN’S ABILITY TO SOLVE CLIMATE CHANGE SEEMED LIKE A SLAM DUNK BECAUSE IT WAS ASSUMED THAT SINCE THE UN HAD SOLVED THE OZONE DEPLETION PROBLEM WITH THE MONTREAL PROTOCOL THEY WOULD SIMPLY REPEAT THE PROCEDURE WITH A “MONTEAL PROTOCOL” FOR CLIMATE CHANGE. FROM THAT POSITION OF STRENGTH THE UN HAD PROPOSED THE SO CALLED “FAMEWORK COMVENTION OF CLIMATE CHANGE” THAT DEMANDED MILLIONS OF DOLLARS FROM THE RICH COUNTRIES THAT HAD CREATED THE CLIMATE CRISIS WITH THEIR INDUSTRIAL REVOLUTION (ANNEX-1 COUNTRIES) FOR CLIMATE ADAPTATION FUNDS THAT THE UN WOULD DISTRIBUTE TO THE POOR COUNTRIES THAT HAD NO ROLE IN THE CREATION OF THE CLIMATE CRISIS (NON-ANNEX COUNTRIES) BUT WERE SUBJECTED TO CLIMATE CHANGE IMPACTS IN THE FORM OF EXTREME WEATHER EVENTS, FLOODS, DROUGHTS, AND, SEA LEVEL RISE. AT SOME POINT IN THIS PROCESS, THE COUNTRIES PROVIDING THE FUNDS TO THE FRAMEWORK CONVENTION DEMANDED THAT THE DISTRIBUTION OF THESE FUNDS SHOULD BE BASED ON EVIDENCE THAT THE EXTREME EVENT WAS CAUSED BY CLIMATE CHANGE AND NOT SOMETHING THAT WOULD HAVE HAPPENED ANYWAY. THE WARSAW MEETING WAS HELD TO SETTLE THIS ISSUE. THE DETAILS OF WHAT CAME OUT OF THE WARSAW MEETING ARE DESCRIBED IN A RELATED POST ON THIS SITE WHERE WE FIND: { Initially, all such events in the nonAnnex countries were fundable under the Framework Convention but later it was argued that this funding policy is arbitrary because natural variability is known to cause extreme weather events anyway even in the absence of fossil fuel emissions and that therefore not all extreme weather events can be attributed to fossil fuel emissions and not all extreme weather events are relevant in the context of climate adaptation assistance from the Annex I countries to the nonAnnex countries (Allen, 2003). This principle was formalized in the Warsaw International Mechanism (WIM) for Loss and Damage Associated with Climate Change Impacts (UNFCCC, 2013). The Warsaw International Mechanism (WIM) has redefined climate change adaptation funding as a form of compensation for “loss and damage” suffered by nonAnnex countries because of sea level rise or extreme weather events caused by fossil fuel emissions which are thought to be mostly a product of the industrialized countries. Accordingly, the WIM requires that loss and damage suffered by the nonAnnex countries for which compensation is sought from climate adaptation funds must be attributable to fossil fuel emissions. A probabilistic methodology was devised to address the need for attribution in the WIM and it has gained widespread acceptance in both technical and policy circles as a tool for the allocation of limited climate adaptation funds among competing needs of the VNAL countries. The probabilistic event attribution methodology (PEA) uses a large number of climate model experiments with multiple models and a multiplicity of initial conditions. A large sample size is used because extreme weather events are rare and their probability small by definition. The probability of an observed extreme weather event with anthropogenic emissions and the probability without anthropogenic emissions are derived from climate model experiments as P1 and P0. If the probability with emissions (P1) exceeds the probability without emissions (P0), the results are interpreted to indicate that emissions played a role in the occurrence of the event in question. Otherwise the event is assumed to be a product of natural variation alone. The probability that fossil fuel emissions played a role in the extreme weather event is represented as P = (P1-P0)/P0. }

A contentious issue immediately arose in PEA analysis. This issue is uncertainty in the values of P0 and P1 derived from uncertainty in the model results derived from different results from multiple model runs. Leading climate scientists and academics immediately opposed the WIM on this ground arguing that the large uncertainty makes it possible to deny adaptation funding to poor countries even when the extreme weather in question really was attributable to climate change. See for example (Hulme, M. (2011, Is weather event attribution necessary for adaptation funding? Science , 334.6057 (2011): 764-765). The uncertainty issue eventually killed the UN’s adaptation funding program and to this day we find the UN’s Guterres going around begging for adaptation funding. THE BOTTOM LINE IS THAT THE WIM PROCEDURE FOR CLIMATE ADAPTATION FUND ALLOCATION DIED BECAUSE OF UNCERTAINTY IN THE RESULTS AND THIS PROCEDURE WAS THEN TURNED INTO A CLIMATE SCIENCE PROCEDURE FOR EVENT ATTRIBUTION AND RENAMED AS EVENT ATTRIBUTION SCIENCE.

THE UNCERTAINTY PROBLEM CAN BE OVERCOME IN CLIMATE SCIENCE WITH THE PRACTICE OF UNDERSTANDING UNCERTAINTY ONLY AS CONFIDENCE INTERVALS AND THEN INTERPRETING THE RESULT IN TERMS OF THE EXTREME END OF THE CONFIDENCE INTERVAL THAT SUITS THEIR NEED FOR ATTRIBUTION. THIS ODD INTERPRETATION OF UNCERTAINTY IN CLIMATE SCIENCE IS DESCRIBED IN A RELATED POST WHERE WE NOTE “UNCERTAINTY DOES NOT MEAN OH! LOOK HOW HIGH IT COULD BE. IT MEANS WE DON’T REALLY KNOW. THE LESS WE KNOW THE HIGHER IT COULD BE AND IN PERFECT IGNORANCE IT COULD BE AS HIGH AS INFINITYBECAUSE THE ANSWER IS NOT CONSTRAINED BY INFORMATION“. AN ADDITIONAL CONSIDERATION IS SUPERSTITION AND CONFIRMATION BIAS.

HUMAN BEINGS ARE NATURALLY SUPERSTITIOUS AS SUPERSTITION HAD PLAYED A ROLE IN THE SURVIVAL OF PRIMITIVE HUMANS AND SUPERSTITION AND CONFIRMATION BIAS ARE STILL IMPORTANT DRIVERS OF HOW OUR BRAIN WORKS. MUCH OF THE ODDITY OF SUPERSTITION IN MODERN HUMANS FOUND EVEN IN THE SCIENCE OF CLIMATE SCIENCE CAN BE UNDERSTOOD IN THAT WAY.

CITATION: SUPERSTITION EVOLVED TO HELP US SURVIVE: LINK: https://www.newscientist.com/article/dn14694-superstitions-evolved-to-help-us-survive/

PART-1: WHAT THE BRIGGS DOCUMENT SAYS

Kinds of claims: There are two main kinds of attribution claim: comparing current observations with respect to past,
and claiming there have been changes in frequencies and severity of certain events. Examining models of so-called climate change and comparing them with models of so-called natural climates. In theory, the events studied can be anything. In practice, it is always ‘bad’ events. Some examples: heat waveS and cold snaps, heavy rains18 and missing rains. Again, it’s odd and troubling that only bad events are discovered. It’s both too hot and too cold, or too wet or too dry, too cloudy or too clear in the changed climate. It’s never pleasanter. That climate change can only be unfortunate, and in contradictory ways, says more about the researchers than it does about the atmosphere. Statements about what doesn’t exist. The changed climate is said to be the climate we now live with,
or will do sometime in the near future; a climate that has adjusted to man’s activities (and only his), activities which are usually limited to atmospheric carbon dioxide production. The ‘natural‘ climate is said to be the climate as it would have been had man not produced so many greenhouse gases, or as it was in the past. It is possible to guess what a natural atmosphere would look like if man had not influenced the climate, but this guess can never be verified. This means any claim about this non-observable natural climate will therefore be uncertain to a high degree. This uncertainty turns out to be important, as we shall see.

Event probabilities: The simplest kind of attribution claim is made using probability statements. Two probabilities are calculated. First, the probability of a given event in the changed climate, and second, the same but for the natural climate; the climate that we don’t live in and which cannot be observed. If the ratio of these two numbers is larger than 1, the event is said to be more frequent in the changed climate, and if it is less than 1 it is said to be less frequent. If the event is more frequent, the argument is that man caused an increase in the frequency. Figure 1 is a exaggerated example from leading proponents of event attribution, Stott and Walton.20 In this cartoon, the arbitrary event (a climate variable such as maximum daily temperature) has a range of possible values. A threshold is taken such that beyond it the event is said to be ‘extreme’. The probability of the extreme event given a changed climate, what they are calling the ‘Actual world’, is shaded red. The probability of the event given the ‘Natural world’, is shaded green. The red area is larger than the green, which implies the event is more likely under the changed climate. This is also indicated by the ratio P1/P0>1. Another way to phrase an attribution claim is to say that the observed event would have still appeared but been of a different magnitude in a natural climate.

Model-based claims: Recall that the output of models of a changed climate and the natural climate are compared to compute probability ratios for a particular event. The use of physical climate models introduces immediate problems because there is not just one model of the climate; there are many. Each purports to well represent the climate as it is now, and as it was before the industrial age. But unless they are duplicates of each other, they can’t all be right, and it remains a possibility none of them are. Attribution claims will change, as Osaka and Bellamy noted, depending on the model used. Crucially, all claims are conditional on the quality of these models. If there is any uncertainty in a model’s ability, it must be added to the uncertainty in the attribution claims themselves which is never done.23 In other words, model-based climate-attribution claims assume perfect models – which is absurd. This criticism cannot be over-emphasised. All attribution claims assume model perfection. The models can’t be ‘good enough’ – they have to be faultless for the attribution to have a definite meaning. Since models are imperfect, this is never the case. Models of the present or future climate can in principle be verified predictively, but there is no reliable way to check the veracity of the pre-industrial or natural models. This makes all attribution claims that rely on natural climate models immediately suspect. Note also that the climate models used must demonstrate skill in predicting the kinds of extremes studied. This is no simple task. Indeed, skill at predicting extremes is low or absent – models tend to exaggerate them.24 Models don’t even do that well at predicting means.25 The global models have to also predict local events well, which they do not. All this necessarily implies actual or changed climate models exaggerate the frequencies of extreme events compared to natural models, meaning the probability ratios are too high, thus claims of attribution are too certain.

Event uncertainties, Calibration and accuracy of models : The events studied are usually those that have recently occurred and generated interest in some way. For example, one study asked whether a recent notable flood was caused by ‘climate change’. Being influenced by current events is unsystematic, which leads to bias in reporting. The temptation not to publish or pursue ‘null’ or beneficial attribution claims is a painful problem. The literature includes only those claims that are thought ‘significant’, leading to an over-estimate of the importance of climate change. This is deeper criticism than it might seem. The actual or changed climate model used in an attribution study gives probabilities for an event. But it could have given probabilities of other events, or the same event at other times. The attribution claims thus represent forecasts in themselves, and they therefore can and should be used to verify model accuracy. As far as we can tell, this never happens. In other words, an attribution study says the event now has probability P1. That is also a forecast, easily subject to verification. So why no verifications? There is also the rank arbitrariness in choosing what precise measures represent an event. It is too easy to cherry pick. For instance, Vautard and others examined heat waves in Europe in June and July of 2019.28 For one month they used ‘highest 3-day averaged daily mean temperature’, and then in another month they abruptly switched to ‘all-year 3-day maximum’. This random switch makes their results highly suspect. It’s as if the authors were hunting for measures that would confirm their biases. The multiplicity of models represents a similar problem to the use of arbitrary and ad hoc measures to represent an event. Since any number of climate models (in pairs representing the actual and natural climates) may be referenced in any attribution study, the temptation to only report or emphasise the ‘best’ one may be irresistible.

History-based comparisons: No model needed: Climate modeling isn’t necessary to make attribution claims, as noted above. Another way to make a claim is to show that events were less frequent historically and are more frequent now, judged by observations made before and after an arbitrary date. The flexibility in the date makes it easy to move to give the ‘best’ results, another point of entry for bias. The difficulty is that measurements of the past, come with more uncertainty than measurements of the present, and often substantially more. This uncertainty must be carried through all levels of an attribution analysis, but isn’t. The greater the uncertainty in the measure, the more difficult it is to make an attribution claim. For example, events from the past almost always have a ‘plus-or-minus’ attached to them. We can account for these mathematically, but this never happens. The critique about statistical estimates of extremes applies here as well.

Conclusion: The desire to say that current notable, harmful or extreme events are caused by man’s activities is strong. This is accompanied by a lack of desire to claim man’s activities produce any beneficial effects. All events investigated are ‘bad’ events, so these are all that will be reported. This introduces a strong bias in attribution reports, one that is likely tied to a desire to blame every untoward weather event on global warming. The journal Climate Change even boasted as much in a call for papers on attributions. They said pushing attributions in the press can produce ‘teachable moments within a short time after an event’, and ‘can bring clarity to a complex question’. It is true enough that claims of attribution are clear, but they are also wrong or misleading, as we have seen. Unfortunately, the clarity that direct observation shows things just aren’t that bad outside, and that harmful events have not been increasing, or have even been decreasing, has not penetrated the climate attribution studies community. Climate change event attribution studies rely on one of two assumptions, both of which are false or unproven. Model-based studies assume models are perfect and represent the atmosphere with no or trivial error. All observations prove this assumption wrong. Models have too much mean prediction error, and unknown but presumably large prediction error of extreme events. The are thus not trustworthy. Again, models must demonstrate skill at all frequencies and scales of events for which attributions are claimed. Plus, models of the past, or so-called ‘natural‘ climate, can never be independently confirmed, leaving us with doubt about their usefulness. If the models are wrong or uncertain, then so are claims of attributions. Observation-based attribution studies assume that man is the sole or most important cause of the changes in observations from before and after an ad hoc date. Claims that this is so are unproven because the actual or changed climate models used to make them are imperfect. Also, the uncertainty in measurements of past events, which can be substantial, is never accounted for, rendering these studies meaningless. It is not that attribution studies are impossible; it is just that they are poor, or worse. They should therefore not be used for decision making in any public way.

PART-2: CRITICAL COMMENTARY

WE SUGGEST THAT A STUDY OF EVENT ATTRIBUTION SHOULD BEGIN WITH ITS ORIGINS IN THE WARSAW INTERNATIONAL MECHANISM UNITED NATIONS MEETING OF 2013 WHERE THE IDEA WAS BORN BUT IN A VERY DIFFERENT CONTEXT THAN THE WAY IT IS USED TODAY. BACK THEN THE UN’S ABILITY TO SOLVE CLIMATE CHANGE SEEMED LIKE A SLAM DUNK BECAUSE IT WAS ASSUMED THAT SINCE THE UN HAD SOLVED THE OZONE DEPLETION PROBLEM WITH THE MONTREAL PROTOCOL THEY WOULD SIMPLY REPEAT THE PROCEDURE WITH A “MONTEAL PROTOCOL” FOR CLIMATE CHANGE. FROM THAT POSITION OF STRENGTH THE UN HAD PROPOSED THE SO CALLED “FAMEWORK COMVENTION OF CLIMATE CHANGE” THAT DEMANDED MILLIONS OF DOLLARS FROM THE RICH COUNTRIES THAT HAD CREATED THE CLIMATE CRISIS WITH THEIR INDUSTRIAL REVOLUTION (ANNEX-1 COUNTRIES) FOR CLIMATE ADAPTATION FUNDS THAT THE UN WOULD DISTRIBUTE TO THE POOR COUNTRIES THAT HAD NO ROLE IN THE CREATION OF THE CLIMATE CRISIS (NON-ANNEX COUNTRIES) BUT WERE SUBJECTED TO CLIMATE CHANGE IMPACTS IN THE FORM OF EXTREME WEATHER EVENTS, FLOODS, DROUGHTS, AND, SEA LEVEL RISE.

AT SOME POINT IN THIS PROCESS, THE COUNTRIES PROVIDING THE FUNDS TO THE FRAMEWORK CONVENTION DEMANDED THAT THE DISTRIBUTION OF THESE FUNDS SHOULD BE BASED ON EVIDENCE THAT THE EXTREME EVENT WAS CAUSED BY CLIMATE CHANGE AND NOT SOMETHING THAT WOULD HAVE HAPPENED ANYWAY. THE WARSAW MEETING WAS HELD TO SETTLE THIS ISSUE. THE DETAILS OF WHAT CAME OUT OF THE WARSAW MEETING ARE DESCRIBED IN A RELATED POST ON THIS SITE: LINK: https://tambonthongchai.com/2018/07/10/event-attribution-science-a-case-study/ WHERE WE FIND: { Initially, all such events in the nonAnnex countries were fundable under the Framework Convention but later it was argued that this funding policy is arbitrary because natural variability is known to cause extreme weather events anyway even in the absence of fossil fuel emissions and that therefore not all extreme weather events can be attributed to fossil fuel emissions and not all extreme weather events are relevant in the context of climate adaptation assistance from the Annex I countries to the nonAnnex countries (Allen, 2003). This principle was formalized in the Warsaw International Mechanism (WIM) for Loss and Damage Associated with Climate Change Impacts (UNFCCC, 2013).
The Warsaw International Mechanism (WIM) has redefined climate change adaptation funding as a form of compensation for “loss and damage” suffered by nonAnnex countries because of sea level rise or extreme weather events caused by fossil fuel emissions which are thought to be mostly a product of the industrialized countries.

Accordingly, the WIM requires that loss and damage suffered by the nonAnnex countries for which compensation is sought from climate adaptation funds must be attributable to fossil fuel emissions. A probabilistic methodology was devised to address the need for attribution in the WIM and it has gained widespread acceptance in both technical and policy circles as a tool for the allocation of limited climate adaptation funds among competing needs of the VNAL countries. The probabilistic event attribution methodology (PEA) uses a large number of climate model experiments with multiple models and a multiplicity of initial conditions. A large sample size is used because extreme weather events are rare and their probability small by definition. The probability of an observed extreme weather event with anthropogenic emissions and the probability without anthropogenic emissions are derived from climate model experiments as P1 and P0. If the probability with emissions (P1) exceeds the probability without emissions (P0), the results are interpreted to indicate that emissions played a role in the occurrence of the event in question. Otherwise the event is assumed to be a product of natural variation alone. The probability that fossil fuel emissions played a role in the extreme weather event is represented as P = (P1-P0)/P0. }

A contentious issue immediately arose in PEA analysis. This issue is uncertainty in the values of P0 and P1 derived from uncertainty in the model results derived from different results from multiple model runs. Leading climate scientists and academics immediately opposed the WIM on this ground arguing that the large uncertainty makes it possible to deny adaptation funding to poor countries even when the extreme weather in question really was attributable to climate change. See for example (Hulme, M. (2011, Is weather event attribution necessary for adaptation funding? Science , 334.6057 (2011): 764-765). The uncertainty issue eventually killed the UN’s adaptation funding program and to this day we find the UN’s Guterres going around begging for adaptation funding. See for example LINK: https://news.un.org/en/story/2021/01/1082842 where we find Gurerres in a desperate begging spree and counting on COP26 to come through with some funding for the climate adaptation fund.

THE BOTTOM LINE IS THAT THE WIM PROCEDURE FOR CLIMATE ADAPTATION FUND ALLOCATION DIED BECAUSE OF UNCERTAINTY IN THE RESULTS AND THIS PROCEDURE WAS THEN TURNED INTO A CLIMATE SCIENCE PROCEDURE FOR EVENT ATTRIBUTION AND RENAMED AS EVENT ATTRIBUTION SCIENCE. THE UNCERTAINTY PROBLEM CAN BE OVERCOME IN CLIMATE SCIENCE WITH THE PRACTICE OF UNDERSTANDING UNCERTAINTY ONLY AS CONFIDENCE INTERVALS AND THEN INTERPRETING THE RESULT IN TERMS OF THE EXTREME END OF THE CONFIDENCE INTERVAL THAT SUITS THEIR NEED FOR ATTRIBUTION. THIS ODD INTERPRETATION OF UNCERTAINTY IN CLIMATE SCIENCE IS DESCRIBED IN A RELATED POST: LINK: https://tambonthongchai.com/2020/04/22/climate-science-uncertainty/ WHERE WE NOTE “UNCERTAINTY DOES NOT MEAN OH! LOOK HOW HIGH IT COULD BE. IT MEANS WE DON’T REALLY KNOW. THE LESS WE KNOW THE HIGHER IT COULD BE AND IN PERFECT IGNORANCE IT COULD BE AS HIGH AS INFINITYBECAUSE THE ANSWER IS NOT CONSTRAINED BY INFORMATION“.

HUMAN BEINGS ARE NATURALLY SUPERSTITIOUS AS SUPERSTITION HAD PLAYED A ROLE IN THE SURVIVAL OF PRIMITIVE HUMANS AND SUPERSTITION AND CONFIRMATION BIAS ARE STILL IMPORTANT DRIVERS OF HOW OUR BRAIN WORKS. MUCH OF THE ODDITY OF SUPERSTITION IN MODERN HUMANS FOUND EVEN IN THE SCIENCE OF CLIMATE SCIENCE AND SPECIFICALLY IN EVENT ATTRIBUTION POST HOC CAN BE UNDERSTOOD IN THAT WAY.

RELATED POST ON SUPERSTITION AND CONFIMATION BIAS:

LINK: https://tambonthongchai.com/2018/08/03/confirmationbias/

RELATED POST ON EVENT ATTRIBUTION: LINK: https://wordpress.com/post/tambonthongchai.com/28347

RELATED POST ON STATISTICS ERRORS IN CLIMATE SCIENCE:

LINK: https://tambonthongchai.com/2021/05/18/climate-science-vs-statistics/

YET ANOTHER ISSUE IN EVENT ATTRIBUTION IS THAT IT VIOLATES THE CLIMATE SCIENCE POSITION THAT LOCALIZED EVENTS OF SHORT DURATION MUST BE UNDERSTOOD AS INTERNAL CLIMATE VARIABILITY WITH NO AGW INTERPRETATION. LINK: https://tambonthongchai.com/2020/07/16/the-internal-variability-issue/

AND IN ANOTHER RELATED POST WE SHOW THAT SINCE EVENT ATTRIBUTION ANALYSIS IS CARRIED OUT AFTER THE FACT ON A SELECTED EXTREME WEATHER EVENT, IT SUFFERS FROM CONFIRMATION BIAS. LINK: https://tambonthongchai.com/2020/06/29/diffenbaugh-2017-extreme-weather-of-climate-change/

AND BECAUSE THE EXTREME WEATHER EVENT IS LOCALIZED AND BRIEF IN DURATION IT CAN ONLY BE UNDERSTOOD AS INTERNAL CLIMATE VARIABILITY AND THEREFORE IT CANNOT BE INTERPRETED IN TERMS OF ANTHROPOGBENIC GLOBAL WARMING. LINK: https://tambonthongchai.com/2020/07/16/the-internal-variability-issue/

THE EUROPEAN FLOOD EVENT OF 2021 SERVES AS EVIDENCE OF CONFIRMATION BIAS IN EVENT ATTRIBUTION ANALYSIS WHERE THE ATTRIBUTION TO CLIMATE CHANGE IS IMMEDIATELY ASSUMED. THE ANALYSIS AND CONCLUSIONS DERIVE THEREFROM.

RELATED POST ON EVENT ATTRIBUTION:

LINK: https://tambonthongchai.com/2021/06/07/extreme-weather-attribution/