by Judith Curry
At one level, analyzing climate risks is a matter of due diligence, given mounting scientific evidence. However, there is no consensus about the means for doing so nor about whether climate models are even fit for the purpose. An alternative to the scenario- led strategy, such as an approach based on a vulnerability analysis (“stress test”), may identify practical options for resource managers. – Brown and Wilby
At the recent Royal Society Workshop on Handling Uncertainty in Weather and Climate Prediction, among the interesting people that I met was Robert Wilby, who has an article in the latest issue of EOS.
Citation: Brown, C. and R. L. Wilby (2012), An alternate approach to assessing climate risks, Eos Trans. AGU,93(41), 401, doi:10.1029/2012EO410001. [link]
Some excerpts:
The recognized limitations of GCMs, including the lack of credibility on extremes, imply that GCM-based projections may have difficulty providing the information decision makers typically look for or even adding value to a risk analysis . One problem is the tendency for some stakeholders to perceive and treat projections as forecasts. Indeed, it is difficult to communicate exactly what climate projections mean from a decision standpoint— they simulate what might happen under some conditions but do not preclude other outcomes. In fact, climate analysts are often reluctant to say that one future is more or less likely than others.
In other disciplines such as decision analysis, scenarios are constructed to help decision makers explore the range of uncertainty in the key variables that affect their system or decision. However, climate change projections from GCMs are ill formed for doing so because of incomplete process representation, parameterization, and small effective sample sizes of models. As a result, the possible range of climate changes might not be fully explored if an analysis relies exclusively on climate projections. Changes beyond what current models project are possible. So if a decision maker wants to conduct a formal scenario analysis, restricting the analysis to this minimum range of uncertainty could result in a lack of consideration of possible climate outcomes.
Multimodel experiments such as the Coupled Model Intercomparison Project phase 3 (CMIP3), ENSEMBLES, Climateprediction .net, and others have helped to characterize aspects of climate uncertainty but not necessarily for those variables of greatest relevance to natural resource managers, such as variability statistics. Other climate modelers assert that the spread of uncertainty may be reduced by adjusting known model biases in simulating present climate. Some researchers are beginning to think that it is better to generate climate scenarios in such a way that one can control, by design, the range of climate changes in the specific variables of interest.
Given these concerns, climate risk analysis in a decision-making context should consider analyses other than climate projections. In some cases, a vulnerability analysis, or stress test, may provide greater insight. Like a sensitivity analysis, a vulnerability analysis provides information on how much a system of interest would respond (how sensitive it is) to changes in climate. Once risks are identified, model projections can be used to assess the plausibility, likelihood, or ranking of climate threats and opportunities based on the latest scientific evidence.
Climate scenarios can be generated parametrically or stochastically to explore uncertainty in climate variables that affect the system of interest. This allows sampling changes in climate that include but are not constrained by the range of GCM projections. The definition of scenarios can be developed as part of a stakeholder-driven, negotiated process, and climate projections can be used in this process. Alternatively, a very wide range of climate alterations can be developed independent of their plausibility and used to identify risks. For scenarios in which the climate consequences exceed coping thresholds, it is then fruitful to evaluate the plausibility of the scenarios. Climate projections, paleo- climate reconstructions, and subjective climate knowledge could all inform such discussions.
Hydrologists and engineers are developing methods based on sensitivity analysis that shift attention back on the water system of interest and use GCM projections to inform, rather than drive, the analysis. These include “scenario neutral” approaches and “decision scaling,” which uses decision analysis as a framework for incorporating climate information including GCM projections. These approaches might be termed “bottom-up meets top-down,” as they focus first on the issues of concern and then on how climate information might add value to the analysis. The basic steps in these methods are to (1) identify the problem, includ- ing defining objectives and performance measures; (2) use a stress test to identify the hazard and evaluate the performance of the system under a wide range of nonclimatic and climate variability and change; and (3) evaluate the risk using climate information including model projections.
An additional advantage of sensitivity approaches is that they may preclude the need for an expensive climate impact assessment and associated opportunity costs (i.e., time and money). For example, if a stress test is performed and no risks to operations emerge over a wide range of plausible climates, then a decision maker will have assessed climate risk, found little or none, and satisfied the review requirements without the large effort involved in typical GCM-led end-to-end uncertainty analysis. For instance, for many water systems, climate pressures may not be significant relative to other considerations [e.g. population increase], especially when economic discount rates in cost benefit analysis diminish the importance of the distant future.
JC comments: This article echoes many of the same themes developed in my presentation at the RS Workshop (.ppt; audio recording). Note, my interest in a follow on RS post has been stymied by only the audio recordings being available (no ppt, no podcast).
That’s very dissapointing. I am amazed that the RS sells its self as the peak body of science and doesn’t even have the capability to disseminate information effectively from workshops like this – that you and others put so much effort into preparing for and presenting at.
Effective dissemination from the workshop is provided by Josh’s cartoons
This entire approach hits me as a classic case of beginning implementation before the requirements are settled. This is always one of the most expensive mistakes you can make. There simply is no substitute for waiting for a finished requirement.
In this case, with conflicting data and conflicting ideas as to what the data means, how would it be possible to determine success in contingency planning? I think you’d only wind up with something new to argue about.
We live in mountains near the ocean. When we go down to town, I throw a jacket in the truck (accepting the real possibility of Monterrey Bay fog). That costs me nothing. I’m all for things that cost nothing or contingencies that would occur anyway but planning long term in the current environment seems ludicrous.
I agree. This is the approach Professor Bob Carter has been advocating for years – but he is condemned as a “denier” by the CAGW alarmists.
+ 1
With our level of knowledge, planning can almost not help being wrong. Better to prepare for early detection of(and response to) catastrophic weather events, and more efficient to prepare for the devastations of a cooling globe than for the general beneficences of a warming one.
==============
General benificences – I like that.
In fact I think I’m going to call my next motorbike General B – just to remind me of all the pleasant aspects of a warmer world :)
This approach is logically equivalent to spending resources on the most urgent and effective adaptations available, when and if they become necessary. It is not only clearly superior, it is where events and financial realities will force us to end up anyway.
So, the Royal Society wants to be relevant; but, skeptics still are ‘deniers,’ right?
This approach appeals to me:
assessing climate risks like?
The University of Illinois has today reported that the Arctic Sea Ice Anomaly has broken a new record low. Sea ice area is now 2.7 million square kilometres beneath normal for this date. It’ll probably get lower too. If it breaches 3 million square kilometers, cryosphere today is going to have to update its graph format.
And the risk to me in Brisbane is … ?
Faustino,
I’d have been happier if you’d said “and the risk to me in Sydney is”?
Look, Queenslanders have to suffer enough jibes from fellow Aussies about low IQ as it is, without you making it easy for them!
lolwot,
You did not define the risk?
In project management risks can have positive or negative consequences. Similarly for climate change. The PMBOK definition of risk is:
Regarding distinguishing causes, risks and effects:
Here is a meta-language that helps to make it clear:
http://www.risk-doctor.com/pdf-files/cause0900.pdf
In your case, you have identified a cause but have not stated the uncertain event or the effect, e.g.:
“As a result of <reducing extent of Arctic sea ice>, <more oil drilling > may occur, which would lead to <more cheap energy for the world hence more people lifted out of poverty more quickly>”
Lyndon LaRouche, is that you? :wink: :smile: :grin: :lol: :!:
Simples.
The change we see in arctic ice during the summer if it continues on its current path may lead to changes in
snowfall in the Nh
weather patterns in the NH
arctic shoreline erosion
food production in the NH
ocean circulation
methane concentrations in the atmosphere
Steven Mosher,
Are you trying to define a risk? If so, it is not clear to me what the risk is. This is a common problem when people talk about risks but do not clarify whether they are talking about the cause, the event or the consequence. That is why I explained the meta-language in my previous comment.
To illustrate the problem with your example, your comment does not define the risk. I am left wondering what is the risk of “changes in snow fall in the NH”?. Is that the ’cause’, the ‘uncertain event’ or the consequence? If it is the uncertain event, what is the consequence.
The consequence needs to be stated in such a way that we can estimate the cost/benefit, or the increased/reduced fatalities, or some other measure that will be applicable for all the risks to be analysed.
Looks like I might have bagged the quanloons at the blackboard. I had 2.89 million km^2 because of the Atlantic water temperatures.
@lolwot
Remind me exactly what terrible things are happening as a consequence of this observation? Beyond somebody having to change the axis on a graph?
Latimer Alder, your post has made an *EXCELLENT* and outstandingly *IMPORTANT* point! :wink: :smile: :grin: :lol: :!:
For rational skeptics, the observed acceleration of Arctic sea-ice melting (per for example Neven’s post this week “Record dominoes 12: CT SIA anomaly”) is very *GOOD* news!
The reason is simple: the year 2012’s cascading “dominos” of heat, drought, and ice-melt are serving to affirm, that scientific theory, observation, and simulation are all three in near-perfect accord with a message that Nature is sending us in plain-text: AGW is real, serious, and accelerating, eh? :shock: :!: :shock:
Rational skeptics no doubt are pleased, that scientific predictions are proving to be in excellent accord with Nature, eh?
Because this increasingly solid science, allows us to make long-range moral and economic choices, regarding carbon-based energy economies, that are rational eh?
As contrasted with short-sighted neodenialist choices, that (as the experience of recent decades shows us) lead straight to moral and economic disaster! :shock: :!: :shock:
Thank you Latimer Alder, for pointing out so plainly, the moral and economic virtues, of strengthening climate-change science, in debunking the short-sighted doctrines, of neodenialist ideologies! :wink: :smile: :grin: :lol: :!:
Because as all on Climate Etc are coming to appreciate, “Nature cannot be fooled”, eh Latimer Alder? :wink: :smile: :grin: :lol: :!:
You must have misunderstood the purpose of this topic for discussion. It’s about alternate approaches to assessing risk. Your post is off topic as it does not discuss a risk and it is certainly nothing new.
Bill, the common-sense risk is that “alternative approaches to assessing climate risk” will create a doctrinal aegis for a toxic brand of neodenialism that is ignorantly short-sighted, morally wrong, economically catastrophic, and deeply stupid.
That’s pure common-sense, eh Bill? :wink: :smile: :grin: :lol: :!:
“The definition of scenarios can be developed as part of a stakeholder-driven, negotiated process …” First, define the stakeholders. In CAGW, that’s the whole community, the whole world. Who would choose? If government in Australia under the ALP chose the “stakeholder” participants, it would be those who were likely to support the government’s existing warmist, statist view (and after the next election, probably those supporting the Coalition’s more muddled but perhaps less harmful view). We’d be moving the same arguments to the pre-assessment level. Post-assessment, any stakeholders who feel that they have been sidelined or not properly represented will carry on the debate as now.
Judith, before the RS meeting, I asked whether policy-makers and businessmen would be invited, to help ensure that policy-relevant questions would be asked. Was the meeting broad-based or largely confined to climate scientists?
Stakeholders means stakeholders. The difficulty of choosing participants is not a reason to reject the process. There have been many successful products in the face of highly complex and contested problems that have resulted from stakeholder engagement. One key principle of participatory processes of that type is that the playing field should be leveled, and participants should be given equal power in affecting outcomes to the extent possible.
“Some researchers are beginning to think that it is better to generate climate scenarios in such a way that one can control, by design, the range of climate changes in the specific variables of interest.” Specific variables of interest: rainfall, temperature, extreme events etc at the regional level. I don’t see that this advances the process at all. The first thing is to fully understand what is going on, many of the sceptical posts here consider that climate processes are not fully understood and are mis-represented in GCMs. If so, then better understanding is still needed if we are to adopt a scenario-based approach. The “who chooses” the variables of interest and range of variations to be investigated still arises.
Would we have had a “no temperature rise from 1998-2012” scenario if B&W’s approach had been adopted in 1997? I doubt it, the bandwagon would not have permitted it.
First, thank you for posting the audio of your talk. It was interesting and easy to listen to. I had thought 24 slides for the time was ambitious–and it is for many presenters–but you are exceptionally efficient. Things flowed. When I looked at the slides alone nothing clicked in my worn brain, but the slides and audio…well, damn nice job. ‘nuf said.
Second, your characterization and critique of GCMs from the perspective of application in decision processes make some good points that need to be repeated time and again. However, refocusing the modeling approach alone is not enough. The expectations of the policy makers regarding the role (informing) and limitations of modeling in decision processes also needs some refocusing.
This seems to me like a very interesting approach. Kind of cuts above the petty bickering that fills up so many jr. high school lunchroom cafeteria tables.
First fix corrupt politics on flood plain development – then adapt to anthropogenic global warming.
Consider the challenge of “climate change” evaluation for a city built on a flood plain and the city council promoted “development” in areas where the “probable” flood level was less than half the historic flood level. The “climate change” contribution appears negligible compared with the challenge of corrupt city government. See the report of the Brisbane flood of January 2011. The 2011 Brisbane Floods: Causes, Impacts and Implications. Robin C. van den Honert, and John McAneney, Water 2011, 3, 1149-1173; doi:10.3390/w3041149
See the consequent 2012 Brisbane interim plan.
New Orleans has similar problems having had inadequate defenses against the Category III hurricane Katrina when the region is known to be in danger of Category V hurricanes. Contrast the Dutch for prudent flood planning.
Demetris D. Koutsoyiannis et al. have been developing flood prediction and design methods incorporating climate persistence using Hurst Kolmogorov Dynamics.
I strongly endorse the sanity of your “alternative approach to assessing climate risk”.
PS I really must protest the ambiguity of today’s English language, when the “norm for engineering and regulatory science” is considered to be having “a lack of formal model verification & validation”!
(in slide 4)
Ah yes. i remember the good old days when there was no ambiguity in language
Steven
Or of fondly harking back to discoursing on “catastrophic anthropogenic global warming”, compared to today’s equivocations of “global warming” or “climate change” – otherwise described as an
How about:
“Engineering and regulatory science norms of formal model verification & validation are missing!”
(PS The greater challenge is to write clear unambiguous patent claims.)
> One problem is the tendency for some stakeholders to perceive and treat projections as forecasts. Indeed, it is difficult to communicate exactly what climate projections mean from a decision standpoint— they simulate what might happen under some conditions but do not preclude other outcomes.
I am shocked.
Breaking News The Met Office has kindly provided a nice summary graph of 150 years of surface temperature data that very nicely shows:
• Ten-year “pauses” in warming are commonly seen in the data,
• Twenty-year “pauses” in warming are *NOT* seen, and
• Warming accelerated sharply beginning circa 1950.
Gosh golly … the trends and fluctuations that we see in the Met surface temperature data matches pretty closely to what the theory-driven simulations tell us!
And of course, the earth’s global energy budget affirms the Met data’s warming picture.
Summary This mutual theory/data affirmation is good news for rational skeptics … it means we humans now appreciate, sooner rather than later, with greater confidence, that climate-change is real, serious, and accelerating … and so we can make rational decisions regarding carbon-based energy economies, eh? :wink: :smile: :grin: :lol: :!:
Pauses are readily seen when natural variability was assumed to dominate. They were not supposed to be seen when the IPCC gatekeepers had decided that they could model natural variability and that it was in decline, ie after 1950. Of course they could not really model natural variability, they just pretended they could and the new pause, now 15 years long, took them and their models by surprise. It just wasn’t supposed to happen!
After a lot of prevarication, hoping the problem would just go away, it was finally realised that this lack of warming had to be acknowledged and explained away. So we saw several more model-driven scenarios that the pause would continue (due to the natural variability that was previously assumed to be declining) following by rapid warming, These predictions failed too; the latest being a Hadley affort that predicted a rapid warming from 2009..Now they have fallen back on the climateers favourite bodge – manmade aerosols – to explain the warming. Of course some still like to alternatively postulate the ridiculous notion that the randomness induced in the models is somehow equivalent to randomness in nature which only proves they know nothing at all about the numerical modeling.
So the real summary is that the models are totally inadequate and nature has made fools of those who rely on them. Trying to pretend you predicted something after the fact or that something was expected when it patently wasn’t is merely fooling yourselves in the climate echo chamber, not the rest of us in the real world..
Now of course the stratosphere not cooling since 1995, the troposphere not warming since 1997 and the seas not warming since 2003 or earlier (we don’t have real data before that – just bad guesses) and all this happening at the same time – tells anyone rational that the hypothesis of AGW is disproven and that the models are obviously not fit for purpose. That fanatics like yourself can’t quite bring yourselves to admit these truths is because for some time you have all been totally irrational!
Perhaps you ain’t been lookin’ at the latest Met data, have yah James G?
Or readin’ the Met’s explanation of it?
Or correlating the observed land-temperature rise with the observed ocean heat-content rise?
Gosh-golly, it sure looks like theory, observation, and simulation are all three in near-perfect accord with what Nature is telling us plainly: AGW is real, serious, and accelerating, eh? :shock: :!: :shock:
Rational skeptics no doubt are pleased, that scientific predictions are proving to be in excellent accord with Nature, eh? Because as Feynman said: “Nature cannot be fooled.”
And the same is true of citizenry … in the long run. :wink: :smile: :grin: :lol: :!:
Thank you, James G, for reminding Climate Etc readers not to be fooled, by the cherry-picking rhetorical tricks of demagogic denialism! :wink: :smile: :grin: :lol: :!:
Off topic. The topic of this post is ALTERNATE methods of assessing risk. Your post is very similar to what you always post. Same old, same old. Not new or alternate. And lots of :):):):):):):):):):):):):)
Bill, the increasing strength of consensus climate-change science sets the stage for the next phase of the climate-change debate, in which neodenialists find themselves so greatly beleaguered, that they fall-back to the position that Lyndon LaRouche and Chris Monckton already have claimed:
• Neodenialists claim “We can’t predict the future.” :?:
• Neodenialists conclude “We needn’t care about the future.” :eek:
• Neodenialists advocate “So let’s ‘party’ with cheap carbon energy!” :roll:
Needless to say, climate-change science assures us that neodenialist ideologies are ignorantly short-sighted, morally wrong, economically catastrophic, and deeply stupid, eh? :wink: :smile: :grin: :lol: :!:
And *THAT* is why neodenialists dislike climate-change science! :wink: :smile: :grin: :lol: :!:
So it’s simple, eh Bill? :wink: :smile: :grin: :lol: :!:
I’ll stop using ‘alternate’ when there is a consensus surrounding this approach :)
Thanks but I saw this on WUWT a few days ago. :):):) ;)
“Near-zero and even negative trends are common for intervals of a decade or less in the simulations, due to the model’s internal climate variability. The simulations rule out (at the 95% level) zero trends for intervals of 15 yr or more, suggesting that an observed absence of warming of this duration is needed to create a discrepancy with the expected present-day warming rate.”
Source: http://www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-2008-lo-rez.pdf
Dr. Roger Pielke Jr. said in 2009:
“Kudos to NOAA for being among the first to explicitly state what sort of observation would be inconsistent with model predictions — 15 years of no warming.”
(h/t wuwt)
Professor Curry,
An alternative approach to assessing climate risks will be totally useless if formulated by any organization that still tries to whitewash, excuse, or ignore evidence of fraudulent global temperature data generated with public funds in the Nov 2009 Climategate emails:
http://joannenova.com.au/2010/01/finally-the-new-revised-and-edited-climategate-timeline/
There is no alternative approach to data!
Oliver K. Manuel
http://omanuel.wordpress.com/about/#comment-1369
Yes, this does agree with the points made towards the end of Judith’s slides. It says, rather than throw the models out, use them to help develop scenarios, and not only that, go beyond what they predict and try to get the real uncertainty covered. We already see why the AR4 models may have underestimated things, as nobody then in 2007 thought sea-ice would disappear so fast, but with the events of 2012 people are saying that by 2020 (even 2015) the Arctic sea ice could all melt.
Jim D
Yes. Reducing uncertainty in the models sounds to me like a winner.
While AR4 models did not specifically project the short-term Arctic (or Antarctic) sea ice loss rates to which you refer, we have seen that the AR4 models overestimated the GH effect on atmospheric temperature in projecting warming of 0.2C per decade when we observed slight cooling instead, despite unabated GHG emissions and GHG concentrations reaching record levels.
A first logical conclusion for this would be that they used a climate sensitivity which was exaggerated.
And this occurred very likely because of overlooked uncertainty of natural versus anthropogenic attribution of past climate change (i.e. underestimating the natural portion while overestimating the anthropogenic portion).
I’d agree with you that this uncertainty should, indeed, be reduced to reflect the most recent temperature observations.
Max
As we approach the third anniversary of Climategate revelations in late Nov 2009, here’s my inventory of where we are and what we know:
1. AGW is a scam, despite Nobel Prizes for Al Gore and the UN’s IPCC.
2. The FORCE that made our elements, birthed the world, and sustains our lives will ultimately defeat manipulation of data and deceit.
3. The UK’s Royal Society and the US National Academy of Science were national institutions, as were British and American Intelligence Agencies and Armed Forces, that compromised their founding purposes.
Conclusions: Truth will be victorious; Deceit cannot achieve noble goals.
See: http://omanuel.wordpress.com/about/#comment-1292
And: http://omanuel.wordpress.com/about/#comment-1369
– Oliver K. Manuel
Former NASA Principal
Investigator for Apollo
The B&W paper described above is very good in that it follows fairly closely engineering practice. Figure out your specific vulnerabilities are and include that info in your planning. Folks should keep in mind that worldwide our infrastructure is continuously evolving. Buildings, roads, and facilities of all sorts age and are upgraded, replaced, or moved. Few remain unchanged for more that a couple decades. Planning for those changes is built into our engineering and project approval procedures at all levels. Potential climate change impacts are but ONE input to that process. As a simple example, it would be silly to plan to protect a building from sea level rise flooding in the next century if it is likely to be abandoned and torn down within twenty years. Unfortunately so much of what I see described as potential impacts of climate change fall into that class of problem – protect something that won’t be there when the problem occurs. In the mean time, population changes, non climate change related weather impacts, and land use changes will require substantial infrastructure changes and deserve our attention.
GaryW,
Excellent comment. I agree 100%. This is a really important point that I think is being missed in the cost benefit analyses that are being done to justify carbon pricing. I suspect, if allowance was made for the continual replacement, upgrading and refurbishment of infrastructure, the damage cost estimates would be much lower than stated in the estimates done to date.
The estimated global damage cost of a 1 m sea level rise to 2100 is $1 trillion (http://www.springerlink.com/content/851112j434t26502/fulltext.pdf ). To put this in perspective, the estimated cumulative GDP to 2100 is $3,500 trillion. That is about 0.03% of global GDP. The damage cost is much less for a 0.5 m sea level rise (about $200 billion).
But there is no evidence the proposed carbon pricing policies would be effective. They will make little, if any, difference to the sea level rise.
Therefore, if we impose the carbon prices we’ll get the damaged global economy AND make no difference to sea level rise. So we’ll cop the cost of the abatement policies AND the damage costs.
Why isn’t it clear to everyone how advocating carbon pricing is lunacy?
The same goes for advocating renewable energy. That’s lunacy too.
Judith, Here is an interesting look at the validity and difficulties of meta-analysis in another field.
Flip, can you provide a link, sounds interesting
Judith – Here is an interesting look at the validity and difficulties of meta-analysis in another field http://www.nytimes.com/2012/10/16/science/stanford-organic-food-study-and-vagaries-of-meta-analyses.html?nl=todaysheadlines&emc=edit_th_20121016
Mainly for entertainment, the attention of Climate Etc readers is directed to Science magazine’s hilarious-yet-thought-provoking annual competition “Dance Your PhD“.
This year’s winner in the “Social Science” category is
Riccardo Da Re’s “Governance of natural resources and development of local economies in rural areas: the Social Network Analysis and other instruments for good governance indicators,” whose themes are directly relevant to climate change.
This one’s for you, Beth Cooper! :wink: :smile: :grin: :lol: :!:
Lacking any actual science-based reasoning the True Believers of global warming have been forced to argue against a holistic view of the world. Being anti-holistic, however, doesn’t come across well to the scientifically illiterate hippies that flesh out the membership of the climatism movement. To buy into the AGW model-makers’ hooey about the Earth having a fever you also must believe that nature is totally flummoxed about what to do with man’s CO2. The model-makers of climatism created their own ‘reality’ which is a metaworld where man’s CO2 produces enhanced greenhouse effects that raise Earth’s average temperature with disastrous consequences for all living things.
A big part of climatists’ beliefs is that man or his CO2 must be abated. Climatists have an abiding conviction that long-term climate forecasting is even possible. That climate prediction is possible using mathematical models is sort of funny because most of those who share these convictions are really bad at math.
http://evilincandescentbulb.wordpress.com/2012/07/23/holistic-heretics-of-metaworld-warming/
LOL … Wagathon, yer post gets the point exactly backwards!
Most of those who are really good at mathematics share the conviction that climate-change prediction is possible
How may we further increase your appreciation of modern mathematical climatology, Wagathon? :wink: :smile: :grin: :lol: :!:
What exactly do egalitarian communitarians know about mathematics that persons skilled in numeracy do not understand? Inquiring minds want to know.
‘Prediction of weather and climate are necessarily uncertain: our observations of weather and climate are uncertain, the models into which we assimilate this data and predict the future are uncertain, and external effects such as volcanoes and anthropogenic greenhouse emissions are also uncertain. Fundamentally, therefore, therefore we should think of weather and climate predictions in terms of equations whose basic prognostic variables are probability densities ρ(X,t) where X denotes some climatic variable and t denoted time. In this way, ρ(X,t)dV represents the probability that, at time t, the true value of X lies in some small volume dV of state space.’ (Predicting Weather and Climate – Palmer and Hagedorn eds – 2006)
‘Atmospheric and oceanic computational simulation models often successfully depict chaotic space–time patterns, flow phenomena, dynamical balances, and equilibrium distributions that mimic nature. This success is accomplished through necessary but nonunique choices for discrete algorithms, parameterizations, and coupled contributing processes that introduce structural instability into the model. Therefore, we should expect a degree of irreducible imprecision in quantitative correspondences with nature, even with plausibly formulated models and careful calibration (tuning) to several empirical measures. Where precision is an issue (e.g., in a climate forecast), only simulation ensembles made across systematically designed model families allow an estimate of the level of relevant irreducible imprecision.’ http://www.pnas.org/content/104/21/8709.full
And yet FOMBS as a practicing space cadet – remains clueless.
“I think math, common sense, and our history shows us thats not a recipe for job growth.” ~Barack Obama
Is he talking about global warming fearmongering, disrespecting the productive for engaging in the business of living, blaming capitalism for emitting CO2 and demonizing oil companies for providing too much energy?
Or, is he talking about what a mistake it is to follow in the footsteps dead and dying Old Europe… as we see happening in California?
Nope. He’s talking about lowering taxes.
What’s going on?
This thread, which is about how to provide more relevant information about climate change and its potential consequences, has attracted only 53 comments so far. Yet, two posts about Antarctic ice in the past few days which are basically irrelevant for policy decision about climate science unless the risks can be stated (which so far they have not been), have attracted over 700 comments so far.
This tells a lot. It tells me that the contributors here are more interested in arguing about temperatures and other irrelevancies than in discussing what to do about what many argue to be a catastrophe in the making.
Why would that be?
Peter, I’m struggling to find a polite response to your question.
Peter, your and a few others research and straight forward, clear headed arguments related to mitigation, absolutely expose the sham. It’s really quite stunning. I’ve thought for some time it’s the winning argument and here’s the proof. Thanks much for your hard work.
Jim
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Actually, GCM-based projections provide none of the information decision makers typically look for in setting policy. “Information” is a statistical concept referencing the idea of a statistical population but the GCM-based projections reference no statistical population. In setting policy, decision makers exhibit apparent belief in the proposition that they possess information about the outcomes from their policy decisions but any such information is fabricated.
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Grazie all’autore del post, hai detto delle cose davvero giuste. Spero di vedere presto altri post del genere, intanto mi salvo il blog trai preferiti.
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