General global warming / climate change discussion

29 May 2017 04:54

midtskogen wrote:
You gave a figure, 2C, without specifying its meaning, so I had to make assumptions.

You can always ask for clarification.

But either way that is fine I will give my best feedback. I will agree with you when I think your assumptions and intuitions are accurate, or help you to correct them if they are not.

I also want to say that I am not trying to put you down -- you are very intelligent, have more world experience than I do, and I deeply respect your insights and contributions to the discussion. I agree with your motivation for looking for tests and potential falsifiability of these projections. I also encourage you to try your own hand at doing a literature review to see for yourself what the spread of expert opinion on this subject is, how that has emerged, what the uncertainties are, and how these models are constructed and tested.

It's a projection, which looks similar to what we've seen over the past 50 years or so. One which I think is very bold for the Arctic. The 1990-2015 temperature increase looks very similar to the 1920-1935 increase, which was followed by a cooling from 1945-1970. I think it's bold to declare that history wont repeat this time.

You can suggest that history would repeat itself and the Arctic would cool, but think about sources of confidence for and against it. The idea is contradicted by an overwhelming consensus of models, the magnitude of thermal energy input to the system compared to internal variations, and the physics of the ice-albedo feedback. Notice that virtually every climate model agrees with these spatial trends (in particular, the stippling pattern represents more than 2-sigma deviation from internal variability and >90% agreement in the sign of the change across the models).

Remember, in the early 20th century the magnitude of warming due to the greenhouse forcing was about the same magnitude as internal variability. But through the 21st century under moderate to high emissions scenarios, the greenhouse forcing is about an order of magnitude greater. I showed a figure demonstrating this on page 1, and I recommend looking at it again and thinking about what it implies. In my opinion this is one of the most important figures in all of climate science.

The point is, in order to give a 2C figure, we must know what the distribution will be. You indicate that we do. However, would you consider it falsified if the Arctic fails to produce significant warming by 2035?

Depending on the concentration pathway we follow (the figure I showed is for RCP 4.5), absolutely this can be falsifiable. The higher the emissions scenario, the more significant the predicted change, and therefore the greater the confidence in rejecting the model should there be an observation of insignificant warming.

You can also test these projections through other metrics. On page 2 I discussed an example of how observations are consistent with climate model predictions, based on a meteorological definition for change in mild weather. You may notice the spatial distribution closely resembles that of positive or negative impacts of climate change on agriculture.

In other words, this is observational evidence that supports the spatial distribution of change predicted by climate models.

Let's look at real data

Sure! You are correct to conclude that the economic factors, land use change, and agricultural development over this timeframe are more important than the climatological impacts over this degree of warming, and so you should not expect to see obvious decline in production in these data. Simply put, we have been farming more, and grown more efficient in how we farm. So far this more than offsets climate impacts.

If you perform a literature review, you will find that these economic and agricultural growth factors are included in the projections, and when you examine the trends, a business as usual approach does not achieve food security. Food security can only be achieved if climate sensitivity happens to be on the extreme low end of the probability distribution (possible but an unwise basis for policy-making) or by employing strategies for adaptation and/or mitigation, which do exist.

A better approach to testing observable climate effect on crops would be to consider the change in crop yield compared to expectation with and without the climate changes, using agricultural models tuned by experiment. What you will find is that the climate changes are indeed already impacting global yields.

The impacts also depend a lot on the region and on the type of crop. For example:

► Show Spoiler

Would a yield in 15-20 years that is higher than today be sufficient to falsify?

In general, almost but not quite. It depends on the emissions pathway we follow and how much emphasis humanity places on adaptive strategies. Under RCP8.5, 2040 is when we can expect roughly 50% probability of passing 2C. So I would expect to observe these impacts to just begin to dominate at the end of this period if we follow high emissions with no adaptation. I would also expect a more clear negative trend in the tropics -- particularly Africa which is known to be the most vulnerable -- and positive trend in the high latitude. A failure to observe those latitudinal trends would be a more powerful falsification, because globally they are nearly balanced at this warming threshold.

How is this all sitting with you so far? I think you are raising good questions and I hope you continue to think about it and peruse available literature and ask questions if you have them. I hope you will also take time to look at what expert opinion is with regards to how to approach the problem of achieving food security. There are quite a few papers that I have read over the years and I'd be happy to provide you with suggested reading material on both sides of the spectrum.

midtskogen · 29 May 2017 13:16

Thank you for your sharing your thoughts and knowledge, here and elsewhere on spaceengine.org. Sometimes your posts are as enjoyable as a PBS SpaceTime episode.

Watsisname wrote:
Source of the post I also encourage you to try your own hand at doing a literature review to see for yourself what the spread of expert opinion on this subject is, how that has emerged, what the uncertainties are, and how these models are constructed and tested.

I try to following the debate and my main entry points for each side are Climate Etc and RealClimate. I do not pretend that this is more than superficial, but my lack of formal education of atmospheric physics prevents my from participating in very technical discussions anyway (back in the 90's I bought and began reading the book used for the first course in atmospheric physics at the universe and it was the most difficult "101" book I have seen - it might have been easier if I had followed the lectures, but it's a complex science). Often I prefer to discuss the epistemology or philosophy of science and climate science is no different from other natural sciences in that respect. So, I don't think there is any authority in consensus. Contrary to what seems to be a popular belief these days, there is no such thing as proof by consensus. So even if the spread in expert opinion indicate a reasonable consensus, there is still room for a fair share of agnosticism until there is sufficient observational evidence. Consider the Moon formation hypotheses. Since the 80's the consensus has favoured the impact hypothesis. But, frankly, we don't know for sure. It's simply the hypothesis with the least amount of known problems, but shouldn't make us rule out that the problems of the other hypotheses can't be resolved, or that there isn't a new hypothesis that can be found to fit the observations better. Had this been a polarised, political topic, I could quickly be labelled a "Moon denier" for my agnosticism.

Watsisname wrote:
Source of the post You can suggest that history would repeat itself and the Arctic would cool, but think about sources of confidence for and against it. The idea is contradicted by an overwhelming consensus of models

Well, the models largely underestimated the recent Arctic ice loss, didn't they? Did they underestimate natural variability or did they underestimate the GHG response? It should be a fair question to ask.

Watsisname wrote:
Source of the post I showed a figure demonstrating this on page 1, and I recommend looking at it again and thinking about what it implies. In my opinion this is one of the most important figures in all of climate science.

For it to make sense I interpret that the upper uncertainty of (non-modelled, actual) internal variability is ±0.12C, compared to ±1.6C (for 2100) for models excluding differences in how they model internal variability. The figure is a bit old (2005?), by the way, which makes observation scrape the bottom of the model spread if extended to 2017. My main concern for this figure is the ±0.12C upper uncertainty range (I assume that this means that the likely range is less than ±0.1C). This is basically unverifiable. It roughly corresponds to the uncertainty range for current observations, and we're far from having a global climate record that accurate for a period before the human influence (when only internal variability ruled), and probably not accurate to falsify a small range either.

Watsisname wrote:
Source of the post If you perform a literature review, you will find that these economic and agricultural growth factors are included in the projections, and when you examine the trends, a business as usual approach does not achieve food security.

Note that the graph says yield per hectare, so yield change due to more or less land used will not show up. I think it's fairly safe to assume the "business as usual" scenario for the next couple of decades. So since the economic and agricultural factors are included, it means that climate change has not only to cancel the effect of CO2 fertilisation within the next few decades, but also the same factors from now and onwards.

Watsisname wrote:
Source of the post What you will find is that the climate changes are indeed already impacting global yields.

We have been able to increase the yield by cultivating the best crop (kind or genetically modified) for the climate and will of course continue to do so. The abstract suggested that the result didn't take an extended growing season into account. That would be surprising, but the article is paywalled, so I can't verify. Nor did it say that whether the experiments were done with the increased CO2 level associated with the temperatures.

Watsisname wrote:
Source of the post Under RCP8.5, 2040 is when we can expect roughly 50% probability of passing 2C. So I would expect to observe these impacts to just begin to dominate at the end of this period if we follow high emissions with no adaptation.

I think RCP8.5 will be the best match within that timeframe. What you say, wont leave it many years for the yield to crash from the higher levels of ~2035 back to the levels of today or lower. 2035 is not far away, and I can wait.

Watsisname wrote:
Source of the post I would also expect a more clear negative trend in the tropics -- particularly Africa which is known to be the most vulnerable

Africa is also most economical unstable, which can influence yield both ways, and this noise makes the climatic influence a bit harder to measure.

Watsisname wrote:
Source of the post How is this all sitting with you so far?

I look forward to discuss this again in 15-20 years!

theiaimpact · 30 May 2017 18:36

Hey, great discussion guys!

midtskogen · 30 May 2017 22:30

A report on the status of electric cars in Norway. The effect this has on CO2 emissions so far may be debatable, but for cities in particular electric cars now definitely have already made some good impact on local pollution. In a city like Oslo, which suffers from winter time temperature inversion and poor air quality, I estimate that about 20% of the cars you see on the road during rush hours are electric now. Carbon burning is stone age technology that should be reduced to niche uses regardless of climate change.

midtskogen · 31 May 2017 00:26

Can technology deliver on the yield challenge to 2050? For fast reading, skip to the conclusion. A relevant excerpt:

It is common that when world grain prices spike as in 2008, a small fraternity of world food watchers raises the Malthusian specter of a world running out of food. Originally premised on satiating the demon of an exploding population, the demon has evolved to include the livestock revolution, and most recently biofuels. Yet since the 1960s, the global application of science to food production has maintained a strong track record of staying ahead of these demands. Even so, looking to 2050 new demons on the supply side such as water and land scarcity and climate change raise voices that “this time it is different!” But after reviewing what is happening in the breadbaskets of the world and what is in the technology pipeline, we remain cautiously optimistic about the ability of world to feed itself to 2050.

01 Jun 2017 10:04

midtskogen wrote:
I don't think there is any authority in consensus. Contrary to what seems to be a popular belief these days, there is no such thing as proof by consensus. So even if the spread in expert opinion indicate a reasonable consensus, there is still room for a fair share of agnosticism until there is sufficient observational evidence. Consider the Moon formation hypotheses. Since the 80's the consensus has favoured the impact hypothesis. But, frankly, we don't know for sure. It's simply the hypothesis with the least amount of known problems, but shouldn't make us rule out that the problems of the other hypotheses can't be resolved, or that there isn't a new hypothesis that can be found to fit the observations better. Had this been a polarised, political topic, I could quickly be labelled a "Moon denier" for my agnosticism.

We can never know for sure. Science does not determine truth. It is not definitively true that the universe is expanding. It is simply the most successful explanation we have that fits the data, and all those data are the result of a bunch of faraway light gathered by mirrors fixed to buckets, and then something that might be magic happened, which was recorded by some fancy electronic thing that operates by principles that also may or may not be magic.

We treat it as if it is truth because we tested it a lot. It has a rigorous theoretical model to support it, and predictive success where other models are falsified. It could be very wrong, but we can also be very confident that it is not, and any new model that might replace it must also account for all the data that supported the old model.

So, to understand why scientific consensus is important we must understand how it develops. It does not happen because a bunch of people sit at a table, one of them says "I have a theory", and 97% of the others go "yeah that sounds good, I like your theory." Because science is founded on the principle of questioning everything. You can question any scientific hypothesis, theory or model, any experiment, any claim, any data plot or any piece of code, and be taken seriously in academic circles.

Now if you were to say say something like "I think a wizard made the Moon", you probably won't be taken very seriously. Similarly if you say "I doubt the impact hypothesis is correct", but your supporting arguments were formed from ignorance of the field. But if you correctly point out where the model has outstanding problems (which it does), suggest how they can be remedied from a theoretical basis or tested by new observations, or if you investigate other models and their strengths and weaknesses, then it is a lot more likely that people will take you seriously. Indeed, this is exactly what scientists spend a great deal of their time doing.

But if everything can be questioned, and if science does not determine truth, then what good is consensus? Because although 100% confidence is not obtainable, it is approachable. When a lot of independent researchers arrive at the same conclusion by other methods, that leads to confidence in that conclusion. This is what has been and continues to happen with published literature on the effect of climate change on agriculture. The IPCC, the most thorough literature review for climate science that there is, has this to say:

and spends an entire chapter reviewing the basis for these conclusions and where that confidence comes from.

Consensus does not mean that something is right, or that we should not continue to test it or alternative models. We continue to test General Relativity over 100 years after its formulation, and we seriously consider the possibility that there are regimes where its predictions could be wrong. The importance of consensus is that it arises when one model is supported by a convergence of evidence, while other models do not or are falsified, to such an extent that most experts in the field become convinced that it is the best working model and is "probably not wrong". In the context of developing policies for a sustainable future, it means the consensus of expert research on climate impacts and strategies to mitigate or adapt to it are important. And I think this is very important to recognize and understand.

YouTube · 01 Jun 2017 10:37

Watsisname wrote:
Source of the post The importance of consensus is that it arises when one model is supported by a convergence of evidence, while other models do not or are falsified, to such an extent that most experts in the field become convinced that it is the best working model and is "probably not wrong". In the context of developing policies for a sustainable future, it means the consensus of expert research on climate impacts and strategies to mitigate or adapt to it are important. And I think this is very important to recognize and understand.

This is a supremely important point, and I think it should be highlighted. Hence this quote, which I hope ensures that nobody misses it.

midtskogen · 01 Jun 2017 13:33

Watsisname wrote:
Source of the post But if everything can be questioned, and if science does not determine truth, then what good is consensus? Because although 100% confidence is not obtainable, it is approachable.

I don't think you sufficiently distinguish between consensus, confidence and verification. And I'm surprised that the consensus has become such an authority, being the weakest. The 97% figure is abused through extrapolation. The study in question says that 97% endorse a consensus "that humans are causing global warming" (count me in). Then, this figure is extrapolated to include that CO₂ emissions are the cause, that nearly all the warming is caused by humans, and that the warming will be catastrophic. I don't know what the actual catastrophe figure would be, and had this been classified in the study, its methodology would give a significant selection bias as the (vast) majority of the papers do not express a position on whether there is catastrophic warming. But this figure is irrelevant for my point on consensus, confidence and verification.

Consensus is not the same as independent verification. When you write papers and endorse the work of others, does it mean that you have replicated their work? On the contrary, you frequently cite them to avoid having to replicate their results. Of course. It would be an unreasonable burden otherwise. Ultimately, consensus means nothing. Verification matters.

Sadly perhaps, I think we must expect most scientific papers to be quite forgettable, many becoming irrelevant, shown irreproduceable, partly right, partly wrong, right but for the wrong reasons, or simply just wrong. This applies to all branches of science to some degree. Expect it in medicine, psychology, astronomy and what makes climate science fundamentally different? And this is part of scientific progress.

Ok, so while some details are uncertain, the important thing is that we're right about the main stuff, right? Humans increase atmospheric CO₂, and the increase causes warming. What I warn about is the extrapolation. We were talking about a catastrophe, famine, and it takes a chain of events to get there. The 97% card is a weak one.

Watsisname wrote:
Source of the post But if you correctly point out where the model has outstanding problems (which it does), suggest how they can be remedied from a theoretical basis or tested by new observations, or if you investigate other models and their strengths and weaknesses, then it is a lot more likely that people will take you seriously. Indeed, this is exactly what scientists spend a great deal of their time doing.

There's no obligation to provide new theories or observations by pointing out problems (which you just did). In the case of global warming theory, one of the most debated problems recently has been the hiatus. The problem seems to have been addressed in a couple of ways: By adjusting the models (like lowering the sensitivity, or assume different natural variability), or by reinterpreting data. Both approaches have their problems. By adjusting the model there is a risk that you do something ad hoc or are merely fitting (you can perfectly model any observations up to the present, but the more fitting you do to do so, it doesn't necessarily increase the predictive force). Data reinterpretation is also a dangerous path which makes you vulnerable to confirmation bias, and prone to accusations of "torturing the data till they confess". Instead I suggest that we let time help us to provide significantly more data. But science has become so impatient.

02 Jun 2017 03:21

midtskogen wrote:
Source of the post I don't think you sufficiently distinguish between consensus, confidence and verification. And I'm surprised that the consensus has become such an authority, being the weakest.

At the time I thought I did, but it is a fair critique.

Confidence can be statistical (arising directly from the mathematical treatment of measurements and their uncertainties) or metastatistical (i.e. a meta-analysis of many studies) in nature. In climate science there is a mixture of both. Philosophically, it can be argued that meta-analysis is weaker (and I would agree), but it is still quite meaningful. If a whole bunch of independent research arrives at consistent conclusions, that leads to increased confidence in the conclusion, and a meta analysis will reveal that. This is the basis of performing a literature review to determine not just the state of knowledge of a field, but also the strength of that knowledge.

Verification means a different study arrived at consistent results. Could be a core prediction of the model tested with a different methodology. Could be the same methodology demonstrated to work by a different team. Sometimes this happens with the goal of verification (or falsifying) in mind. Sometimes it happens by accident -- another team was pursuing the same research question at the same time without knowing it.

Consensus emerges from both of these. Also from falsification of alternate models. That is why in science, consensus is strong, not weak. Consensus can also be wrong and change, as in a paradigm shift. A good example of that is the snowball earth hypothesis. At first, very hypothetical and mostly thought too extreme to be true (how often this happens in different fields of science...

), yet now from decades of very hard work by many independent geologists -- largely trying to refute this hypothesis at first -- a consensus has emerged that there was not just one, but several snowball earth events, with a lot of confidence in our understanding of the most recent one.

The study in question says that 97% endorse a consensus "that humans are causing global warming" (count me in).

Me too. In the well known study that I think you are referencing, this was a completely meta-analysis. And I agree with you, it is rather weak in its methodology. The reliability of the manner in which it determines whether the authors agree or disagree or are indifferent is very open to debate.

The stronger case for the anthropogenic cause of warming is found by models of climate with and without the anthropogenic forcings, and it is those model results that convinced the majority of climate scientists.

I'm not really sure if I follow your extension to "catastrophic" warming and the like. The term itself requires clear, preferably quantitative definition, and I mostly do not see a consistent one being used across the popular discussion. Is there a particular definition that you are using or have seen being used?

midtskogen wrote:
Source of the post We were talking about a catastrophe, famine, and it takes a chain of events to get there.

I think you may be taking the language of it too severely. It is not necessarily a catastrophe and the bulk of research is not presenting it as such (some studies are, while others are concluding it's probably not a problem, but the consensus is in the middle).

What it is is an additional challenge presented by climate change on top of a long list of challenges. It decreases the yield of numerous crops, especially at low latitude, and then virtually everywhere at higher warming threshold (like 4C). It increases the amount of mitigation and/or adaptation we much do on top of current trends in order to achieve food security. It increases risk of high and variable food costs, and malnutrition in low latitudes and developing nations.

There's no obligation to provide new theories or observations by pointing out problems (which you just did). In the case of global warming theory, one of the most debated problems recently has been the hiatus. The problem seems to have been addressed in a couple of ways: By adjusting the models (like lowering the sensitivity, or assume different natural variability), or by reinterpreting data. Both approaches have their problems.

I agree, and there were a lot of investigations into the cause for the hiatus. We would of course like to understand it, and understanding it benefits climate science and the predictions for the future. Some studies arrived at different explanations, some are more compelling than others, and it is appropriate to comment on their strengths and weaknesses. In science we do not like to explain things in an ad hoc manner, or simply tweak a model to fit observations better after the fact, without being able to justify those adjustments and show that they have predictive success.

Of these studies the most compelling for me was the demonstration that treatment of ocean-atmosphere interactions and ocean heat content produce a very steady signal of increasing thermal energy, directly in relation to expectation from the radiative forcings. This does not explain all of the hiatus, but it does explain a lot of it, and much of surface temperature variability in general.

This is convincing because it is not founded on data reinterpretation or epicycle-like model tweaking. It is an accounting of what the ocean-atmosphere interactions (e.g. ENSO) did, and then demonstrating that this accounting is consistent with the change in ocean thermal energy by directly measuring it at different depths.

In other words, it shows that the ocean-atmosphere interactions really do account for where the heat is going. And when we factor this in to the total energy budget, it returns a steady warming signal consistent with the radiation imbalance. This is a predictive success, in a different sense than usual but one which is just as powerful. It is similar to general relativity "predicting" the correct perihelion drift of Mercury's orbit. It did not predict it by design; it could easily have predicted something totally different.

It is also compelling on a theoretical/conceptual basis. We know that most of the additional heat is stored in the ocean, and ocean-atmosphere interactions are important. It makes sense that accounting for it would explain most of what the surface temperatures did, rather than a significant misunderstanding of the physics of the greenhouse effect or other factors.

The effect of ocean-atmosphere heat exchange does imply that transient climate response or climate sensitivity is a bit less, and all else being equal lowers future warming projections slightly. But the effect on climate sensitivity also depends on timescale.

Finally I'd like to answer this earlier question:

Well, the models largely underestimated the recent Arctic ice loss, didn't they? Did they underestimate natural variability or did they underestimate the GHG response? It should be a fair question to ask.

Not necessarily either. Sea ice loss also depends on the short-term behavior of the general circulation, weather, wind and ocean currents. Aspects of all of these are attributed to the sudden accelerated decline, and there is some evidence that they were partly coupled with the climate change itself.

We could call these factors a sort of internal variability, but it's not the same variability as we are talking about in the context of internally-driven variations in global average temperature. It's how different aspects of the system specifically interact with the ice and vice versa. Sea ice predictions models try to capture some of this detail by combining climate with coupled ocean-atmosphere-cryosphere interactions, plus an attempt to model the dynamics of ice loss itself (how it behaves as it gets thinner and the survival of multi-year ice). These processes are much less well understood, so there is greater uncertainty in the model predictions, especially compared to other aspects of climate change.

We can also be confident that it was not an underestimate of the direct GHG response, because the greenhouse forcing did not spike by a comparable amount on a comparable timescale.

If you are interested in testing the predictions of global climate models, and particularly in the sense of gaining confidence in the temperature distribution, you have better methods available. Better in the sense of more directly probing it (the sea ice extent is very indirect for the above reasons). I provided another approach earlier. Others are the change in the general circulation, pressure scale heights, and so forth. Another measure of confidence to view the inter-model variations. See what the models themselves agree or disagree on.

The prediction of the change in temperature distribution is actually one of the least uncertain projections in the climate models. Since the temperature change is also one of the most important factors for the effect on crop yield, this is a lesser source of uncertainty in the agricultural predictions.

Greater sources of uncertainty in the projections are the CO2 fertilization effect, which varies by crop, but experimental studies have narrowed it down significantly. Observations also show that the effect is occurring in the real world and is consistent with expectation. Other uncertainty is from change in regional precipitation, but these also are diminishing with time.

The most significant sources of uncertainty are what happens with tropospheric ozone (still rarely modeled), pests (also rarely modeled), run-off and water availability, and extreme weather (difficult to predict). Most of these factors are expected to point in the direction of increasing risk more than benefit, though in some places water availability may increase production with irrigation -- i.e. can benefit adaptation.

That's all I have time for now, I think the discussion is quite excellent and if there are new or old questions you'd like me to answer specifically feel free to raise them for next time.

midtskogen · 02 Jun 2017 10:43

I don't doubt that you know what consensus, confidence and verification mean. We might have different views on their relative importance. I'll just add here that something with limited verification can have a high degree of consensus. Consider the composition and internal structure of the planets besides Earth. I think there is a reasonable consensus for each of them, but there is still much to be verified, and if the consensus fails verification, the consensus changes even if it was universal. So a high degree of consensus doesn't mean that things are settled for practical purposes. A high degree of verification is different. I think this sets consensus and verification clearly apart.

Watsisname wrote:
Source of the post I'm not really sure if I follow your extension to "catastrophic" warming and the like. The term itself requires clear, preferably quantitative definition, and I mostly do not see a consistent one being used across the popular discussion. Is there a particular definition that you are using or have seen being used?

I agree and even though something catastrophic is often implied in popular discussions, what exactly it is and to what degree remain elusive, and so does the testability. Which is precisely why the prospect of imminent crop yield failures more than cancelling technological advances (hence likely causing severe famines which I would regard as catastrophic) caught my attention, since it's quite specific and holds a promise of testability. Often, it's very hard to grasp exactly what we have in store except that it's something bad so that we in 2050 or 2100 or whenever will regret that we didn't act in 2017. If it's a matter of conscience rather than science, there is less need to quantify.

A few years ago I got into a discussion on RealClimate with a guy who with great precision had calculated how many billion people would die in the 2030's directly or indirectly due to climate change. Quite doomsday, that is, and for that reason we could possibly dismiss the idea on a purely statistical basis: through the entire recorded history of humans not a single doomsayer has been right. But I pushed him ways to falsify his claims (without too much success). His reasoning was mainly based on future events consistent with science, or rather events that science could not yet rule out. I think he's not the only one trapped in this kind of thinking. But what falls within possible outcomes is only guaranteed to be in the realm of science fiction. Time and testing will set science and science fiction apart.

Watsisname wrote:
Source of the post Of these studies the most compelling for me was the demonstration that treatment of ocean-atmosphere interactions and ocean heat content produce a very steady signal of increasing thermal energy, directly in relation to expectation from the radiative forcings.

This implies that other models were wrong. Not wrong about that CO₂ traps heat, but about how it happens and its consequences which is what we care most about. Over at RealClimate some were saying that this heat storage in the ocean merely postpones the atmospheric warming, so the predicted warming by the other models is correct. To me that sounds an awful lot as clinging to a straw, adjusting ad hoc as time goes. And it has the problem that it's stalling falsification opportunities. My prescription remains more decades of observation.

Watsisname wrote:
Source of the post Sea ice loss also depends on the short-term behavior of the general circulation, weather, wind and ocean currents.

Precisely why the predictions of "ice free summers" are likely wrong. Well, since the predictions are all over the place, some might be right about the timing (if we ever get an ice free summer but it's happened before), but less likely be right about the reasons. The sea only freezes when the ocean temperature is low enough, but the ocean is not static and even if it's very cold in the air, the ocean will not freeze if there's a constant influx of warm water.

spaceguy · 08 Jun 2017 19:53

http://www.oism.org/pproject/
How to reply to this?

08 Jun 2017 20:50

spaceguy wrote:
Source of the post http://www.oism.org/pproject/

Try going to OISM's homepage and look for information on their courses, faculty backgrounds, and research opportunities in climate science or any related field. This alone should be a really powerful demonstration as to whether the OISM petition project is credible or not.

midtskogen · 08 Jun 2017 22:43

From the site:

There is no convincing scientific evidence that human release of carbon dioxide, methane, or other greenhouse gasses is causing or will, in the foreseeable future, cause catastrophic hearing of the Earth's atmosphere and disruption of Earth's climate.

For reasonable interpretations of "catastrophic" and "disruption" this is correct. The problem is that such claims are extrapolated or used to persuade people to believe that there is solid scientific evidence for the contrary, ultimately for claims like (from the slides) "Hydrocarbon energy is not warming the Earth". This shows how far the polarisation has gone. There is no place for a middle position fully considering the complexity, or a more agnostic position.

09 Jun 2017 00:14

A search of IPCC AR5 WGI, which is 1552 pages long, for the word "catastrophic" returns exactly 15 results. The first refers to a magnitude of methane hydrate destabilization, which greater than what is expected to occur. Two through nine are all in the same figure referring to "large - catastrophic" magnitudes of river flooding. 10 is in the title of a citation for a paper studying Laurentide lakes 8200 years ago. 11, 13, and 14 are about methane hydrate releases again, 12 is in a citation for a paper studying the effects of nuclear winter, and 15 is in a citation for a paper exploring ice shelf breakup processes.

The point of the exercise:
In climate science, when referring to the magnitude of impacts of climate change, "catastrophic" can be a weasel word. Scientifically it is of no value unless it has a specific, quantitative, agreed upon meaning to be used in a specific context. If you see it being thrown around carelessly by either side of the opinion spectrum, it is probably the case that it is not a scientifically-grounded discussion.

If we want to understand the severity of the impacts, what they mean for us, and what we can or cannot do about them, the discussion requires more care and closer ties to what the research and scientific discussion say. Consensus is a useful tool here. For example,

A few years ago I got into a discussion on RealClimate with a guy who with great precision had calculated how many billion people would die in the 2030's directly or indirectly due to climate change. Quite doomsday, that is, and for that reason we could possibly dismiss the idea on a purely statistical basis: through the entire recorded history of humans not a single doomsayer has been right. But I pushed him ways to falsify his claims (without too much success). His reasoning was mainly based on future events consistent with science, or rather events that science could not yet rule out. I think he's not the only one trapped in this kind of thinking. But what falls within possible outcomes is only guaranteed to be in the realm of science fiction. Time and testing will set science and science fiction apart.

You can challenge a claim like this in a number of ways. The precision of the prediction begs the question of how uncertainties were handled. Verification of the underlying processes and their extrapolation to higher temperatures or climate disruptions is another avenue. But one of the most direct is to simply check the consensus -- what does the bulk of available research have to say, and is it consistent with his claim?

midtskogen · 09 Jun 2017 00:47

I think "catastrophic warming" is a scientific straw man, but in the public debate such ideas are frequently presented and backed up with reference to a scientific consensus which really is on something much less sensational. it's a sign that science gets poorly communicated, and also to some degree intentionally poorly communicated. It attracts attention and the scientist don't have to answer for the boldest claims if they fail to become reality since they didn't actually make those strong claims in their papers.

General global warming / climate change discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

General global warming / climate chage discussion

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