Statements often appear in the media about suggesting that more extreme mid-latitude storms will result from global warming. For instance, western Norway was recently battered by an unusually strong storm which triggered many such speculations. But scientific papers on how global warming may affect the mid-latitude storms give a more mixed picture. In a recent paper by Bengtsson & Hodges (2006), simulations with the ECHAM5 Global Climate Model (GCM) were analysed, but they found no increase in the number of mid-latitude storms world-wide. Another study by Leckebusch et al. (2006) showed that the projection of storm characteristics was model-dependent. (Note that the dynamics of tropical and mid-latitude (often called ‘extra-tropical’) storms involve different processes, and tropical storms have been discussed in previous posts here on RC: here, here, here, and here).
The factors that control this are often confounding and so make this a tricky prediction. Simple arguments based on the expected ‘polar amplification‘ and the fact that the surface temperature gradient between the tropics and the poles will likely decrease would reduce the scope for ‘baroclinic instability’ (the main generator of mid-latitudes storms). However, there are also increases in the upper troposphere/lower stratospheric gradients (due to the stratosphere cooling and the troposphere warming) and that has been shown to lead to increases in wind speeds at the surface. And finally, although latent heat release (from condensing water vapour) is not a fundamental driver of mid-latitude storms, it does play a role and that is likely to increase the intensity of the storms since there is generally more water vapour available in warmer world. It should also be clear that for any one locality, a shift in the storm tracks (associated with phenomena like the NAO or the sea ice edge) will often be more of an issue than the overall change in storm statistics.
I believe that the jury is still out on the extra-tropical storm issue because the climate models are still limited in their ability to represent them adequately. For instance, wind speeds are not well captured by the models (Leckebusch et al., 2006), and modelled key characteristics of the cyclones were sensitive to the models’ spatial resolution: Work by Jung et al. (also published in Quart. J. R. Met. Soc. (2006), vol 132, p. 1839-1857) suggested that several key characteristics of extra-tropical cyclones in the global ECMWF numerical weather model are highly sensitive to the horizontal resolution. This is also acknowledged in a recent paper by Wernli & Schwierz (2006; J. Atm. Sci., vol 63, p. 2486). However, for some regions, Jung et al. noted that model problems were insensitive to the horizontal resolution employed in their model experiments. Ulbrich (EMS/ECAC06) also found a dependency of the storm statistics in re-analysis with different spatial resolution (the picture from GCMs was similar to the re-analysis, provided the re-analysis was carried out with similar spatial resolution). It was also concluded that the different models analysed gave a similar large-scale picture of how extra-tropical storms respond to a global warming: the frequency of weak storms decline and the strong storms are projected to become more frequent. The sensitivity to resolution is understandable, because while an entire storm system can be very well resolved (they can be 1000 miles across), there are very sharp features at the fronts (the comma shaped clouds) which are a challenge even for weather forecast models to get right. Secondary ‘cyclogenesis’ (where a new storm is ‘spun off’ from an existing storm) is also something that improves markedly as resolution increases.
One can try and address that by using a high-resolution regional climate model (RCM), forced by simulations from a coarser GCM at its boundaries (a process called ‘nesting’). The RCMs provide a similar description of the minimum sea level pressure (SLP – a parameter related to wind storms and the cyclone depth) as the GCMs, irrespective of their spatial resolution (The KNMI scenarios 06 Fig. 6-3). RCMs, however, are not completely free to do their own thing, but must follow the GCMs, at least on the larger scales. So should we really expect an RCM to produce a different storm climate? What implications would a substantially different cyclone climate in the RCM have for the larger-scales and the energy transport? Cyclones play an important role in the poleward energy in the mid-latitudes (‘eddy-transport’), which ultimately has a bearing for the large-scale circulation. Since cyclones involve significant parts of the hydrological cycle, such as evaporation, moisture transport, condensation and precipitation, a different cyclone climate in an RCM and GCM would presumably present inconsistencies for the water budget. Furthermore, a paper by Peng et al. (2006) suggests that eddy forcing may be responsble for large-scale response to changes in the sea surface temperatures. In other words, the cyclone climate affects the large-scale circulation, and a widely different behaviour in the RCM and the GCM would imply an inconsistency.
One robust result among most GCMs is a poleward shift in the position of the storm tracks (Bengtsson & Hodges , 2006; Yin ,2006). It is important to keep in mind that for the local communities concerned, it is changes in the position of the storm tracks that is most important, rather than the global number of storms. Another robust result is that the NAO in the models tends to shift more towards its positive phase (stronger westerly winds) as greenhouse gases rise, tending to increase winter storms coming ashore in Northern Europe, and decrease them around the Mediterranean (Miller et al, 2006).
A conceptual picture of processes affecting mid-latitude is: One, that latitudinal variations in the temperature and air flow give rise to ‘baroclinic instability’; Second, the humidity of the air also plays a role as the latter influences the energy budget. An analogy for the two can be a sloping surface: the former is the how steep the slope is and the latter the height of the drop. Sharp spatial temperature contrasts and horizontal wind shear favour an unstable growth of the storm system.
As we mentioned above, global warming generally implies a ‘polar amplification’ (stronger warming near the North Pole), and so the average poleward temperature gradient is expected to diminish, leading to less unstable conditions on average. On the other hand, a warmer Arctic may imply less sea-ice and a greater heat loss to space, which must be balanced by heat transport from the lower latitudes, a poleward heat transport which may involve the mid-latitude storms (ice insulates the ocean from the atmosphere and keeps the temperatures down). Increased temperatures also implies higher humidity, and thus a higher capacity for energy conversion through condensation – the energy fuel of convection. So it isn’t a simple picture and one should be wary of simple statements on the topic.
re: 97. “You have to realise that just because an article is peer reviewed it is not neccessarily correct. There were plenty of articles opposing continetal drift before plate tectonics was accepted, and plenty of papers criticising the idea of an impact causing the dinosaur extinction before the Chicxulub crater was found.”
This statement indicates a misunderstanding of the peer-review process. The *process* is a very strong, difficult and accurate one. Sorry but science is never perfect as no one claims it is. But cherry-picking counter examples is the method that global warming denialists have used for years. Furthermore, the quantity of articles on a subject (e.g. continental drift vs. tectonic plates) is utterly and completely irrelevant. The process of scientific peer-review led us to where we are with regards to our knowledge of tectonic plates. The scientific process involves hypotheses, gathering data to test those hypotheses, experimentation, analyzing data and results, conclusions, peer-review including the ability to repeat the experiments which produce similar conclusions, and new hypotheses for testing. In the case of global climate change, the scientific consensus is quite strong.
re: 96. I used the simple Gaussian model distribution as a simple case to make a simple point about models, as I stated. I never said the models were calculating a Gaussian distribution. Please do not infer that I did.
If the climate sensitivity is 1.5K and other models say that the climate sensitivity is 4.5K, and the rest say somewhere in between, that does *not* mean only one value is correct. It does indicate a range of sensitivity. You may be “entitled” to say anything you like but you would be simply wrong to say “the vast majority of models are wrong”.
Shouting “THE MODELS ARE WRONG!” again and again does absolutely nothing to prove that. If anything, it detracts. Thankfully we have documented scientific processes and thorough review processes that show otherwise.
In Reply to comment 82: “This may be a basis for the notion of rapid change in the geomagnetic field’s inclination. The momentary local measurements do vary. Here’s the inclination changing by about three quarters of one degree, and the declination changing by minus six degrees, briefly, today, in one spot. That’s not the global axis changing, it’s a local event.”
There are two events recorded in lava flows. They were not local events and were not temporary magnetic field changes. A NOVA program was produced to discuss, the Oregon rapid magnetic field change which was a very large change in field inclination (the field has trying to reverse), rather than a permanent reversal. The Afar event was a magnetic field reversal. (See my comment 88 for links to the two papers.)
Please defer dismissing this data, until I can present an explanation of what could possibly account for this extraordinary rapid change in the geomagnetic field.
From the 2002 Nature Paper Abstract which discusses the Oregon partial reversal:
“Palaeomagnetic results from lava flows recording a geomagnetic polarity reversal at Steens Mountain, Oregon suggest the occurrence of brief episodes of astonishingly rapid field change of six degrees per day. The evidence is large, systematic variations in the direction of remanent magnetization as a function of the temperature of thermal demagnetization and of vertical position within a single flow, which are most simply explained by the hypothesis that the field was changing direction as the flow cooled.”
From the abstract of Acton’s paper (see my comment 88 for a link to Acton’s paper for details.) that discusses the Afar event:
“One lava flow has recorded both of the antipodal transient components residing in magnetic materials with unblocking temperatures above and below 500C (my comment, Curie temperature) respectively … Hence the geomagnetic field appears to have jumped nearly instantaneously from a north-hemisphere transitional state to a southern hemisphere one, during the normal to reversal polarity transition.”
#69 Ike, fully agree on moisture, rather water vapour pressure in air, the dynamics may be relatively simple, the more water vapour the more greenhouse effect there is. This is perhaps the #1 strongest feedback in the Arctic, with higher temperatures there is more water vapour, the Arctic is now becoming from a very dry cold place, a warmer wetter environment. There is no question about Hadley cells being more complicated, but a normal North Pole would have a huge High pressure almost at all times somewhere during the long night, this is the world’s roof top cooling system which has been hampered by a recent increase in clouds extent.
Alistair, you should consider the models like prediction instruments, rather than a perfect zillion crunching of calculations giving the coming climates. In Climate projections, the ultimate peer is not a Journal referee, nor an Einstein, the ultimate peer is the future. Models in my opinion are superb tools, making sense of a huge planet, they lack a few algorithms, which will be found out eventually. My opinion of them is that they perhaps are not designed in calculating the total heat content of the Earth’s atmosphere, a flaw if that is not done. I use other methods in determining the total temperature of the atmosphere in key locations, and found great success in “seeing” the future. Eventually the models will incorporate this idea and many others, wait a little, they will surely be more impressive.
Re #101 and #102
Dan,
Rasmus wrote “In a recent paper by Bengtsson & Hodges (2006), simulations with the ECHAM5 Global Climate Model (GCM) were analysed, but they found no increase in the number of mid-latitude storms world-wide. Another study by Leckebusch et al. (2006) showed that the projection of storm characteristics was model-dependent.”
Two peer reviewed papers, not cherry picked but found in this this blog item, which say the opposite. Only one can be correct, and only time will tell which is correct, and then it will be become part of scientific truth. Until then, both papers are in limbo despite being peer reviewed. Publication does not make a paper true. It only makes it a candidate for being part of science.
Therefore it follows that the climate models are not neccessarily true just because they have been published in peer reviewed papers. They will only be true when they are found to match reality. At present they dont, and arguing that the data is wrong and the models are right is even more stupid than shouting THE MODELS ARE WRONG!
Re “However, that argument itself is fallacious because Einstien was writing before the discovery of quantum mechanics.”
Huh? The basic insight of quantum mechanics dates from 1900, when Planck figured out the way around the “ultraviolet catastrophe.”
Re “If some models say that the the climate sensitivity is 1.5K and other models say that the climate sensitivity is 4.5K, and the rest say somewhere in between, only one value is correct. Only one out of those dozens of models is correct, and I am entitled to say the vast majority of models are wrong!
If they now clustered around 3.3K to 3.7K then I would accept them as correct, but they have remained with a variation of over 300% for 15 years. It seems to me obvious that there has been something wrong with the models for at least that time.”
You’re assuming the distribution of doubling predictions is flat over the entire range. In fact they do cluster around 3.0 degrees. Try taking the figures for 20 or so models and graphing them in a histogram and you’ll see what I mean.
Barton, I don’t have access to 20 models, but the ClimatePrediction do and their spread goes upto 10K !
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RE: 92, 97, 98, 100, 101, 102, 105
I believe it’s perfectly senseless to turn this already high-noise conversation into a shouting match. Some people will continue to repeat “peer review” and “IPCC” for the same reason that they go to church on Sunday.
It’s funny that people who never worked in academia are teaching the audience that “peer review process is strong”. Anyone who did participate in it knows full well that it isn’t.
I have personally seen Ph.D. theses being approved by advisors and committees simply because the student hang out in grad school for too long to kick him/her out without a degree. And all this garbage, needless to say, gets published in a refereed literature. For you information, a referee isn’t required to check the math in details. If the author dropped a coefficient somewhere in derivation, it will usually go through just fine. When I took pains once to go in details and found an error I got an incredulous reply from the author: “It was a part of my thesis and /a world-famous scientist/ approved it.” Well … duh! He had better things to do than to go into political fight with the department. The editor wanted no part in this and killed the paper. Keep in mind that it’s a rare exception, though!
But this is nothing compared to the bugs in the computer code. Those are practically uncheckable, certainly not in the peer-review process. Even apart from it, the bugs live undisturbed for years and decades. A well known researcher told me once that while on postdoc he found a bug in GFDL model. His boss (a big name) simply declared that the bug didn’t exist and that was that for quite a while. It took about 10 years until someone else noticed and finally fixed it.
That’s climate. My friend who works in the area of solid state physics tells me that in his field over 50% of published peer-reviewed results are later proved wrong. Virtually anything can be published. Alan Sokal famously demonstrated it:
http://www.physics.nyu.edu/faculty/sokal/transgress_v2/transgress_v2_singlefile.html
[Response: The Sokal hoax was in a social science journal, not a scientific journal and using that as an example of how scientific peer review doesn’t work is misleading. However, I do agree that crap gets published all the time – we discussed examples here – but it is not unusual for serious mistakes to be found during the peer review process and for terrible papers to sink without a trace. Your example is not isolated (ask any journal editor). Finally, as someone who runs a model development group, I can assure you that any bugs found in our code are tracked down and the impacts checked immediately and I would be astounded if that wasn’t true at GFDL. The idea that ‘big names’ go around squishing younger researchers’ corrections to code is not one that has any credibility, I’m afraid. -gavin]
re: 105. The “number of mid-latitude storms world-wide” and “storm characteristics” are not the same. And of course simply publishing is not the end-all. The entire point is the review within the scientific community by knowledgable peers, not laymen. It really is not a difficult concept.
re: 110. A small minority of vocal laymen will continue to repeat with no basis that they know more than literally thousands of climate science researchers who have followed a strong and proven review process for the same reason that they beleive they *must* be right whatever the scientific evidence shows or whatever “church” they attend.
RE: #110 (comment)
True, Sokal published his hoax in the social science journal. I just couldn’t resist bringing it up :-) I didn’t mean to say that peer review process doesn’t work at all. The point was that it’s very much flawed so only a layman could think of it as “strong”.
I’m not at all questioning professional standards in your group. But you are still developing. However, 15-20 years ago GFDL was the only freely distributed model, it was released, effectively a gold standard. The incident in question didn’t occur in Princeton (can’t imagine Kirk Bryan to behave like this) but elsewhere. I’m sure that you’re on the first name basis with the junior figure in this episode so you can pick up the phone and verify it in a matter of minutes. I cannot guarantee that will go “on record” with this, though. [edit – email me directly if you like – gavin]
Re #78: EdGCM runs on OS X too, not just Windows. OS X is actually our primary development environment.
Thanks for the clarification, but alas, I don’t have access to a Mac either, just Linux. Though I do have access to a couple of BlueGenes :-)
Observations in to update models:
http://www.sciencemag.org/cgi/content/abstract/1134548
The new data are “direct aircraft observations … on the chemistry occurring downwind of convection … previously only the province of model analyses. .. quantitative measures that can be used to evaluate global climate and chemistry models.”
Re “My opinion of them is that they perhaps are not designed in calculating the total heat content of the Earth’s atmosphere, a flaw if that is not done.”
Use the specific heat capacity of moist or dry air, depending on how much water each layer of air can hold, and find the temperatures at each altitude from the NOAA et al. (1976) US Standard Atmosphere. Heat energy in a reservoir is temperature times heat capacity times mass. For mass of each layer take the height and density figures, figure a volume and a mean density to get the mass. The numerical answer is left as an exercise for the student.
Re #95 Ike wrote “I don’t hear Alastair crying out about the failure of weather models… why not?”
I don’t cry out about the weather models because it is impossible to get the weather wrong! All you have to do is wait until just before it arrives and then predict it. Of course if you only wait until 24 hours ahead, then you get it right most of the time. If you get your model to predict it 96 hours ahead and it gets it wrong, then you blame chaos theory. I can’t win saying that the weather models are wrong, but they are.
The Met Office produce a Handbook for their weather forecasters and it explains that the cloud base is not where the models predict. In fact there is a paper with a coauthor who has posted here which explains if you rely more on the measurements and less on the model then the results are better!
Craven, Jeffrey P., Jewell, Ryan E. & Brooks, Harold E. (2002) “Comparison between Observed Convective Cloud-Base Heights and Lifting Condensation Level for Two Different Lifted Parcels” Weather and Forecasting 17 pp. 885-890.
Of course it is easier for the climate modellers. No one yet can tell whether they are right or wrong.
72° in New York City; Avalanche rips Colorado highway
The heat is on in New York City! The temperature soared to 72° at New York’s Central Park Saturday, tying their all-time warmest January temperature ever.
http://www.wunderground.com/blog/JeffMasters/comment.html?entrynum=608&tstamp=200701
#116, That would be nice daily number to have, the total heat content of the Northern and Southern Hemisphere’s atmosphere and oceans. Only then will we have an idea about a true GW trend.
#117. Alastair, I agree that some models are practically useless, like temperature Probalistic long term projections. which are worse than flipping a coin. But the models actually mimic quite well huge systems, but fail in micro managing exact scenarios because their resolution is poor. A met station may record no upper inversion, while 20 Kilometers away there is one, this is not a small problem, the models are in effect set-up with an incomplete pack of data, and they can’t “imagine” what is happening between station gaps.
Re #119 Wayne, the models cannot replicate entry into and exit from the Younger Dryas, hemispherical events. Yet a paleoclimatologist has told me all that is needed to use models with a higher resolution!
Here are the letters to the editor regarding the original article published today in the NY Times: Climate Change: No Time to Debate
Alastair, my calculations show, by a small formula called EROAM, equivalent refraction one atmosphere method, a significant gradual yearly warming in the horizontal, not mainly in the vertical, where there is just 35 km of relatively dense atmosphere, compared to 25,000 kilometers of higher pressure air everywhere you look at the horizon. I don’t blame the models if they don’t have this information, they are in some ways blind sided, by too much information in the vertical without upper air verification from the horizontal. But that will change some day…..