As is now traditional, every year around this time we update the model-observation comparison page with an additional annual observational point, and upgrade any observational products to their latest versions.
A couple of notable issues this year. HadCRUT has now been updated to version 5 which includes polar infilling, making the Cowtan and Way dataset (which was designed to address that issue in HadCRUT4) a little superfluous. Going forward it is unlikely to be maintained so, in a couple of figures, I have replaced it with the new HadCRUT5. The GISTEMP version is now v4.
For the comparison with the Hansen et al. (1988), we only had the projected output up to 2019 (taken from fig 3a in the original paper). However, it turns out that fuller results were archived at NCAR, and now they have been added to our data file (and yes, I realise this is ironic). This extends Scenario B to 2030 and Scenario A to 2060.
Nothing substantive has changed with respect to the satellite data products, so the only change is the addition of 2020 in the figures and trends.
So what do we see? The early Hansen models have done very well considering the uncertainty in total forcings (as we’ve discussed (Hausfather et al., 2019)). The CMIP3 models estimates of SAT forecast from ~2000 continue to be astoundingly on point. This must be due (in part) to luck since the spread in forcings and sensitivity in the GCMs is somewhat ad hoc (given that the CMIP simulations are ensembles of opportunity), but is nonetheless impressive.
The forcings spread in CMIP5 was more constrained, but had some small systematic biases as we’ve discussed Schmidt et al., 2014. The systematic issue associated with the forcings and more general issue of the target diagnostic (whether we use SAT or a blended SST/SAT product from the models), give rise to small effects (roughly 0.1ºC and 0.05ºC respectively) but are independent and additive.
The discrepancies between the CMIP5 ensemble and the lower atmospheric MSU/AMSU products are still noticeable, but remember that we still do not have a ‘forcings-adjusted’ estimate of the CMIP5 simulations for TMT, though work with the CMIP6 models and forcings to address this is ongoing. Nonetheless, the observed TMT trends are very much on the low side of what the models projected, even while stratospheric and surface trends are much closer to the ensemble mean. There is still more to be done here. Stay tuned!
The results from CMIP6 (which are still being rolled out) are too recent to be usefully added to this assessment of forecasts right now, though some compilations have now appeared:
The issues in CMIP6 related to the excessive spread in climate sensitivity will need to be looked at in more detail moving forward. In my opinion ‘official’ projections will need to weight the models to screen out those ECS values outside of the constrained range. We’ll see if other’s agree when the IPCC report is released later this year.
Please let us know in the comments if you have suggestions for improvements to these figures/analyses, or suggestions for additions.
References
- Z. Hausfather, H.F. Drake, T. Abbott, and G.A. Schmidt, "Evaluating the Performance of Past Climate Model Projections", Geophysical Research Letters, vol. 47, 2020. http://dx.doi.org/10.1029/2019GL085378
- G.A. Schmidt, D.T. Shindell, and K. Tsigaridis, "Reconciling warming trends", Nature Geoscience, vol. 7, pp. 158-160, 2014. http://dx.doi.org/10.1038/ngeo2105
When the measured temperature goes down from one year to the next, where does that heat go? Atmosphere? Deep ocean? Unmeasured locations?
Thanks in advance
[Response: The heat capacity of the atmosphere is small, and so can be affected by oscillations in ocean heat uptake or the escape of heat out to space. These are both quite well measured (in some respects) but not quite well enough to provide a complete answer to your question. – gavin]
In a couple of places on the graph, the multimodel average is lower than the lowest model or higher than the highest. That seems odd.
[Response: Not sure what you are seeing? The black line is the model mean, grey shading the 95% envelope, and the coloured lines are observations. – gavin]
Congratulations on having modeled more than all plausible forcing outcome pathways !
OTOH, modeling most of the priors Hansen’s grandchildren may employ is not the same thing as knowing how their parents will respond to them.
Because we don’t know , decadally speaking, what will be on deck in energy tech , two three or four decades out, which is rather a problem ,when changing the matter things are made from changes the shape of things to come.
1 Francis:
22 Jan 2021 at 8:19 PM
When the measured temperature goes down from one year to the next, where does that heat go? Atmosphere? Deep ocean? Unmeasured locations?
Thanks in advance
[Response: The heat capacity of the atmosphere is small, and so can be affected by oscillations in ocean heat uptake or the escape of heat out to space. These are both quite well measured (in some respects) but not quite well enough to provide a complete answer to your question. – gavin]
It has always been my understanding radiation into space is quite well constrained and has little variation (not wthstanding clouds and the uncertainties there). Wouldn’t that make the ocean the likely location for the large majority of the excess heat/energy?
Thank you for a very informative post. It is especially interesting to see how close CMIP3 is to what happened. It will be interesting to see what the IPCC does with CMIP6. I always like your comparison articles. As time goes by your projections seem better and better.
Small typo paragraph 2: HadCRTU4
Francis @1,
If you plot out, say, GISS annual global temperature and global Ocean Heat Content on the same graph, you’ll see the OHC (0-100m) waggles in step with the surface temperature and, with a bit of back-of-envelope number-crunching, it shows the 0-100m OHC is losing/gaining about the same number of Zetajoules as the atmosphere is losing/gaining.
If you then plot the OHC (100-300m) or OHC (100-700m) there are signs of an anti-wobble suggesting significant parts (at time the majority) of the atmosphere/0-100mOHC wobbly loses/gains end up as wobbly gains/loses in the deeper ocean.
I’ve published on GitHub an opensource Python script that can parse and print some of the HadCRUT5 datasets.
https://github.com/madrisan/HadCRUT5
Maybe someone can be interested.
Recommended supplemental reading:
“If scientists can create a new way to predict climate change – making it as accurate as, say, forecasting the weather – it would help people make everyday decisions: how high to build a sea wall or what crops to plant.”
“Meet the team shaking up climate models” by Doug Struck, Environment, The Christian Science Monitor, Jan 22, 2021
https://www.csmonitor.com/Environment/2021/0122/Meet-the-team-shaking-up-climate-models
Note: This is a very well-researched and well-written in-depth article. Gavin Schmidt is quoted.
Are you planning to do similar comparison plots to CMIP4 and CMIP5?
[Response: for no good reason, they skipped CMIP4, and the CMIP5 picture is on the linked page. – gavin]
As an interested layperson I find these charts extremely confusing. I’ve been trying to follow the science for 20 years or more, and I thought I was fairly familiar with the common acronyms, but… it turns out I’m not. Which lines are the observations and which are models? And could they be labelled as such? TIA!
[Response: Here’s a nicer version: -gavin ]
Quadrant author Michael Kile seems dissapointed that GISTEMP does not address god and demon variability.
This is a source of modest concern, as he is also of the opinion that :
“The evidence supports a revival of (humane) human sacrifice (HHS) as a mechanism for retarding environmental degradation and reducing dangerous climate change.”; and he may have Gavin in mind:
https://vvattsupwiththat.blogspot.com/2021/01/newscorp-gods-demons-demand-cop27-press.html
Hello – I have a question to ask the scientists here. I would believe it would be true that global mean temperatures are now above 1.0 deg C increase since pre-industrial levels. But isn’t equally true the land surface temperatures are now already around 2.0 deg C warmer? But isn’t also true that the vast majority of humanity lives on the land? In which case what relevance is a global increase when the temperature that’s actually affecting humanity, and its shared natural environment, is already around the temperature that scientist say is dangerous and unsustainable? In which case, why are scientists not taking account of this, and shouting this fact from the rooftops? I’d be interested in your thoughts.
re: 2
I was looking at the CMIP6 graph’s lines. For instance, at the rightmost edge, the multimodel mean is greater than any of the single lines of any other model run. That’s true at several places along the graph. There are other places where the line runs below every other graph result. Your answer seems to say that the multimodel mean is the mean of the 95% error envelopes.
I still don’t understand why the mean of the runs wouldn’t be within the range of their outcomes. If I create a mean of 3 numbers, no matter the range of the numbers the mean will be within that range. No mean can be larger than the largest element or smaller than the smallest of the elements within the range. If x = 2 and y = 4 and z = 12, the mean can’t be greater than 12 or less than 2.
No need to print this. In fact I’d prefer not. I’m only sending it to convince you I wasn’t trolling. It’s genuinely out of my not understanding. I presume the 95% envelopes for the individual runs vary widely or that the spread of the 95% envelopes are not equal above and below the outcomes.
[Response: I think you are misinterpreting the graph. The black line is the ensemble mean, and the 95% envelope of models runs is the grey shading. The individual lines are different estimates of the observations. No individual model runs are shown. – gavin]
John Monro #12,
John, unfortunately, even after all these decades, sloppy communication about climate change causes unnecessary confusion. It’s not your fault.
The global average temperature that is presented (Global Mean Surface Temperature, GMST,) is a proxy for the increase in energy in the entire climate system caused by human activity.
The negative consequences of that increase in energy show up in different ways locally… heat waves, droughts, intense rainfall, melting ice, sea level, rapid intensification of hurricanes, and so on.
So GMST is used for comparison of how bad all that stuff will get given different levels of CO2. You can’t think of it is an actual temperature that has a direct local effect on you. Hope that helps.
#13
Yes, I don’t understand the graph. I thought the black line was derived from the colored lines.
Re: John Munro (12)
as explained by zebra(14) – global surface temp. anomaly is an important metric reflecting total amount of energy, and it is this energy that drives the climate,
therefore to characterize the physics of the system, and land-only temp is a much less useful one for this purpose.
And land-temp. does not compensate for this weakness with a much stronger public communication value – first its use is not obvious – if we use land-average, because humans live on land – then why stop there, and why not EXCLUDE all these places where few people live: Antarctica, Greenland, the rest of the Arctic, Tibet, great deserts and semi-desserts. And at least in the Arctic land warms much faster than the rest of the land, so your land average after removal of the Arctic may not be as much more impressive than global average.
And if anyone is interested in the land data – they are there, one Google click away, e.g. https://www.ncdc.noaa.gov/sotc/global/202012
And the difference to the _communication_ of the urgency of the problem is not as great as you imagined: do you really think that people who are completely unimpressed by +0.78 C over the whole planet (Dec.2020), will radically change their views if “ the scientists shouted from the rooftops [that the land warmed up by 1.27C] ?
BTW – in the table there, out of 141 years, Dec.2020 was 8th warmest December in ALL 3 rankings: global, land-only or ocean-only data. So if you wanted to impress on your audience how untypically warm are recent years – it would make NO DIFFERENCE whether you used global, land-only, or ocean-only data.
John Munro @12,
Fixing a global temperature for pre-industrial to measure the rise against is not without its challenges. Some simply take the pre-1900 average of the temperature records to serve as such a pre-industrial temperature and that would suggest we currently have a +1.0ºC global mean increase and a +1.8ºC global land increase with global land temperatures increasing 50% faster than global mean.
The measure for limiting AGW is set as the global mean rise, not simply a limit to the rise in local temperatures impacting human populations. Mind, if it were a strict +2.0ºC limit, this GISTEMP anomaly map shows relative to pre-1900, such a +2.0ºC limit has been broken across continental Europe, Russia & Alaska over the last decade.
Thanks for the replies, folks, but whilst I appreciate that the global mean temperature increase is the true measure of the increase of energy in the climate system, at least I think that’s what you’re saying, it seems intuitive, even if unduly simplistic, to look at land surface temperatures because that’s where we will be seeing the real problems, as they interact with our own human needs and environment. Extrapolating, does a 2 deg C global rise then imply a 4 deg C rise on the landmasses, affecting the glaciers, water circulation and weather extremes? That’s a huge and likely very damaging change, isn’t it? I still wonder if my simplistic way of looking at things mightn’t be the best way. Cheers.
RE: John Monro @12
Of course scientists know what’s going on across the populated land masses, but I agree that the consequences of average global temperature change, outside of catastrophic storms, are often not communicated.
I’ve found two measures that have been very helpful when communicating this information to the public in the various presentations that I do. One that is easily found are maps showing the change in growing season length for the U.S. This illustrates how a relatively small change in average yearly temperature (small relative to changes in daily high temperatures) has a huge impact on these maps used by farmers and gardeners. To know that Illinois will have the same growing season as Texas opens the eyes of audience members.
I also show a list of historic freezes. I live in a subtropical environment and the lack of hard freezes over the last 30 years has caused obvious (to naturalists and gardeners – my main audiences) changes in how the place looks (palm forests are springing up) and in what people can grow (non-grafted citrus, papaya, etc.). This helps bring it home to them.
Andrew Sipocz @19 > …I agree that the consequences of average global temperature change, outside of catastrophic storms, are often not communicated.
Exactly. Thank you very much.
John Munro @18,
The +2.0ºC limit (now considered to be too lax with the Paris Agreement described ”Its goal is to limit global warming to well below 2, preferably to 1.5 degrees Celsius, compared to pre-industrial levels.”) was always a simply-expressed way of describing what should be an acceptable amount of climate change. When first derived (anecdotally scribbled onto a napkin in a Stockholm restaurant) it was accompanied with a limit to the rate of warming, put at +0.1ºC/decade, a limit which has been continually broken since the 1980s.
While the +2.0ºC limit is simple, the reasons for its adoption are many and complex. Likely the differing viewpoints that accept it are on occasion contradictory. So a proper discussion of why the limit is +2.0ºC global and not +1.0ºC global [= +2.0ºC land] will also be complex and messy.
(And hot-off-the-press, one of the reasons for a +2.0ºC limit was the Holocene Climatic Optimum and the following dip in global temperatures which early stages of AGW would be simply reversing. The existence of a Holocene Climate Optimum is challenged by Bova et al (2021) ‘Seasonal origin of the thermal maxima at the Holocene and the last interglacial’ – paywalled paper, graphic from Rutgers Uni press release here. The paper also considers the Eemian Climate Optimum, another precedent for elevated global temperature, which was a bit hotter than the Holocene Optimum but may also be subject to revision.)
That said, the point that the +2.0ºC limit expresses a measure of the whole global climate is important, something which would become lost by taking a measure of land temperatures rather than global temperatures as being the limit.
And the discussion of a limit would become, I would suggest, much more temperature-centric so ignoring massive changes in other meteorological considerations. And it would also become too ‘localist’. Thus, the map linked @17 shows areas already suffering a +2.0ºC increase in AGW. It is a lot of land area but most is poorly populated and presently suffers terribly cold winters so getting a bit more warmth into those regions could be argued a real benefit of AGW (indeed there are those who do argue along these lines) and that thus a +2.0ºC limit was far too low. And, hey, Spain Italy Greece and Iran; they’ll be part of the Sahara/Arabian Desert soon anyway so ignore them.
I would suggest this would not be a very edifying debate!!!
Further, such consideration applies only to humanity. The natural environment is adapted to those un-increased temperatures and will have to adapt to the new warmth – the reasoning behind the now-forgotten +0.1ºC/decade limit.
And there are places in the world where even a small increase in temperature will have a big impact on humanity. The places where it is already hot and also wet (thus the tropics) become a death-zone for humans above +36ºC outside air-con, this due to hyperthermia. And it should not be considered a ‘hard’ limit. As that limit is approached, live for the unfortunate denizens becomes increasingly unpleasant.
So consider the Amazon Basin. As this BEST data page shows, this region has experienced a +1.5ºC increase above the 1800s, as of 2014. The attached data for monthly averaged ‘Mean of Daily High temperature’ shows a similar rise over the annual average and also an anomaly base for each month running from +30.2ºC to +32.5ºC. So there isn’t much room here for any AGW. Indeed the highest monthly average works out to +35.5ºC for September 2015.
That, perhaps, provides a flavour of the debate a move to using land temperature would involve.
While the discussion of best metrics for communicating climate change is interesting, and to the extent that it’s a search for ‘best practices’ perhaps even valuable, I can’t help reflect that 1) the global metric is well-established (and for good reason, as already articulated by others), 2) the land-only metric is nonetheless current as well (also for good reason) and 3) neither of those facts is likely to change anytime soon.
My takeaway would be the further reflection that WHETHER we take steps to communicate climate change is more crucial than (because prior to) the minutiae of HOW we do so.
(2 cents.)
Andrew Sipocz and others,
(Andrew, I tried valiantly to get someone here to answer the question you raised a few weeks ago about wind shear declining, but no luck. Have you come across anything more on that topic?)
In regard to the current topic, the language is the problem.
Nothing that affects people is a “consequence” of an increase in the average global temperature. I keep pointing this out, and nobody ever disagrees with me, but some form of this fallacious usage keeps popping up.
Perhaps I have more faith in the ability of (non-partisan) lay persons to internalize a basic concept like energy, if it is consistently communicated, than many spokespersons. I think that if you achieve that, it is much easier to explain how the various individual effects like changing growing seasons are a consequence of human activity.
But if we continue to consistently conflate correlation and causality, it is really easy for the Denialists to do their “how could .2 degrees make that much difference anyway?” shtick.
MA Rodger @21 > That, perhaps, provides a flavour of the debate a move to using land temperature would involve.
Thank you for detailing the genesis of the 2 degrees Celsius limit–a clear contribution. But there’s no question at all of a move to using land temperature–and that’s not what John Monro @12 is about. The question is all about communicating the consequences of the heating.
The global mean is a conceptual point anyway, it’s not a place-time. It’s not a place where anybody lives, any day in any season of any year. The problem is to relate those seemingly small numbers to people’s lived experiences.
Gavin, when you say “remember that we still do not have a ‘forcings-adjusted’ estimate of the CMIP5 simulations for TMT”, I take that to mean that the CMIP5 TMT simulations are the likely cause of the discrepancy. If so, does that mean that there is an actual discrepancy between measured land anomaly trends and satellite anomaly trends? What could explain that?
John Munro(18) – “I still wonder if my simplistic way of looking at things mightn’t be the best way”
No, for the reasons we have explained to you. In my case:
Piotr (16) [“Your way” i.e. using land temperature] does not compensate for
the weakness [of not providing information on the total energy of the system that
in turn drives climate] with a much stronger public communication value:
1. justification is not obvious – if we use land-average, because humans live on land – then WHY STOP THERE: why NOT EXCLUDE all these places where few people live: Antarctica, Greenland, the rest of the Arctic, Tibet, great deserts and semi-desserts.
And at least in the Arctic land warms much faster than the rest of the land, so your land average after removal of the Arctic may not be as much more impressive than global average.
2. If anyone is interested in the land data – they are there, one Google click away, e.g. https://www.ncdc.noaa.gov/sotc/global/202012
3. The difference to the _communication_ of the urgency of the problem is not as great as you imagined: do you really think that people who are completely unimpressed by +0.78 C over the whole planet (Dec.2020), will radically change their views if “ the scientists shouted from the rooftops [that the land warmed up by 1.27C] ?
Andrew Sipocz (19) in reply to (12): “ I’ve found two measures that have been very helpful when communicating this information to the public in the various presentations that I do.”
Eeer, John Monro (12) wanted to raise the awareness of “dangerous” changes that “scientist should be shouting about from the rooftops“.
Are you sure that your two metrics:
– “ Illinois will have the same growing season as Texas” and
– “the lack of hard freezes over the last 30 years [caused] palm forests to spring up and people [able to] grow non-grafted citrus, papaya, etc.”
fit eh bill? I.e. would make your “farmers and gardeners” to grab their pichforks or papaya pruning gardening tools, and march on Washington demanding … more ambitious emission cuts targets?
Zebra @23 says: “Nothing that affects people is a “consequence” of an increase in the average global temperature. I keep pointing this out, and nobody ever disagrees with me, but some form of this fallacious usage keeps popping up. Perhaps I have more faith in the ability of (non-partisan) lay persons to internalize a basic concept like energy, if it is consistently communicated, than many spokespersons. I think that if you achieve that, it is much easier to explain how the various individual effects like changing growing seasons are a consequence of human activity….But if we continue to consistently conflate correlation and causality, it is really easy for the Denialists to do their “how could .2 degrees make that much difference anyway?” shtick.”
Ok, but just as a layperson playing devils advocate wont the denialists just say a change of xyz joules of energy “wont make much difference” especially considering the vast quantities of heat energy already in the system?
And getting Donald trumps climate denialists supporters to understand heat energy might not be easy:
“The equation for calculating heat energy is q=mCpΔT, where q is the heat variable, m is the mass of the object, Cp is the specific heat constant and ΔT is the temperature change.”
“Multiply the change in temperature by the specific heat capacity and the mass of your object. This will give you the heat lost or gained in joules.”
And climate change is indirectly a consequence of changes in temperature because that change is a fundamental part of calculating heat energy.
And there is a pretty obvious intuitive and physical relationship between higher temperatures and melting ice. It doesn’t make much sense to say to the general public ignore that and just think about the energy in the system. Or maybe we discuss both?
But discussing changes to weather patterns would obviously benefit from discussing changes in energy.
As regards the above temperature and communication debate, I would suggest we consider using Earth Energy Imbalance as the premier quantity to promote public understanding of our planetary condition, as Hansen has suggested. This is not to disregard rise in temperature whatsoever (“we have a temperature and are sick”).
Since today’s rise in global surface temperature is due to past emissions and will continue to increase due to this fact (even if today’s emissions were zero), it would seem more appropriate to attempt to indicate what is coming. This might be done by explaining Radiative Forcing, the timeline of its “Response Factor,” and the EEI which is reacting to these rising conditions. Earth Energy Imbalance, as a quantity, seems much more impactful than one or two degrees in public (including governmental) communications.
(ditto: my two cents, sorry to veer off the science)
@21…
Re. access: While I do have access to a research library, just clicking on the link you provided led to the whole paper on nature.com. There is a side note stating that open access has been provided by Springer Nature Sharedit.
MA Rodger:
I missed this earlier, but just learned about it at aTTP. Holy crap! It increases the “unprecedented” status of the current warming. From the abstract of the peer-reviewed article (there’s also a Nature News and Views piece):
So much for “the HCO was warmer than now, and we came through it OK” AGW-denialist arguments. I wonder if agriculture would have taken hold in the Fertile Crescent if annual GMST was 2 degrees warmer than pre-industrial? If only summer temperature was elevated, then ceteris paribus, higher spring soil moisture would favor annual crops there. Hmm, crops domesticated in New Guinea were mainly perennial. Was that because seasonality was less of an issue for them? OTOH, irrigation arose early in both places. It’s complicated.
The abolition of the Holocene thermal maximum — “climatic optimum” sounds a little more subjective now — raises more questions than it answers. Gotta love science!
How many different models/calculations/ensembles have been created during the decades of climate science?
If there are more than a handful, then making an animation with the images of these predictions, all put into the same time-axis, and showing the different calculation-results in comparison with the measurements.
In some images there is “hindcast” vs. forecast. In an animation, one could show, how this vertical line between hindcast and forecast shifts from left to right.
If using one forecast/ensemble that would be just showing the measurements adding up.
But if also there would be a way to show how new forecatsts/ensembles were introduced, then this would be one dimension more that could be shown.
Thats just a raw idea, I have only a vague imagination of how that could be used to show the evolution of the models/predictions together with the measurements.
I don’t know enough details on when which models were introduced, so I don’t know if such an animation would make sense or could be understood.
But maybe there is a way to do so. And I somehow have the guess that if thats possible, it would be impressive and explanatory – for laymen as well as the experts.
To the images above: it needs the gray area to be explained inside the images. Images are there to make things clear with one look at it. If it has unexplained elements and the person views it must loook up the information somewhere in the text, then the big advantage of using an image is diminished drastically.
Another idea on what can be drawn into the images: a line that tracks the maximum-so-far. In electronics this would be called a peak-detector.
See here to get an idea:
Peak detector
I think it would be interesting to add that into the graphics which show the meaurements of the global mean temp.
The distance between the steps (steps when using the dots of each year, without interpolating lines between them) of this peak-detection-line could also be shown below the graph. I await to see these steps during the years coming more often.
When every year is warmer than all years before, every year would have such a step.
@Davide Madrisan, #7: Thank you! That’s great.
Re. @21 et al
Good “Guardian” article that explains the new research in easy to understand simple language:
”Climate crisis: world is at its hottest for at least 12,000 years – study”
https://www.theguardian.com/environment/2021/jan/27/climate-crisis-world-now-at-its-hottest-for-12000-years
Looks like warming continued at ~0.2°C/decade, as projected by climate models, consistent with what the IPCC said, and in contradiction to Judith Curry’s predictions for the first couple of decades of the 21st century. It’s 2021, the year Judith Curry said her claims should be assessed. Even the ERA5 re-analysis she likes to cite shows she’s wrong and climate models were right ( https://www.psl.noaa.gov/cgi-bin/data/testdap/timeseries.pl ).
Below are some other visualizations of the surface warming trend vs. model-based projections:
https://archive.is/xR9zw
https://www.carbonbrief.org/state-of-the-climate-2020-ties-as-warmest-year-on-record
And below is further context on Curry’s ongoing history of false predictions in comparison to accurate climate models:
“This is why i prefer the reanalyses, such as ERA5. They assimilate the radiances measured by the satellites.”
https://twitter.com/curryja/status/1232753750617382912
“the AGW dominated prediction of 0.2C/decade does not seem like a good bet”
https://judithcurry.com/2012/02/07/trends-change-points-hypotheses/
[ https://twitter.com/AtomsksSanakan/status/1348566747901788165 ]
In 2016:
“And what of the years following 2016? Will we see cooling and then a continuation of flat temperatures? Or continued warming? I suspect that there will be some cooling and continued flatness. I’ve stated before that it will be another 5 years before we have the appropriate prospective on the current temperature fluctuations and whether or not the early 21st century pause is over.”
https://judithcurry.com/2016/03/06/end-of-the-satellite-data-pause/
“However these data end up being analyzed, the trend since 1997 is very small, much smaller than the decadal trend of 0.2C that we have been led to expect by the IPCC for the early part of the 21st century. […] If you are using data to evaluate the IPCC’s projection of 0.2C/decade warming in the first two decades of the 21st century, with plateaus or pauses at most of 15-17 yrs duration, well then you can pick whatever start date you want”
https://judithcurry.com/2012/10/21/sunday-mail-again/
“A year earlier, Jan 2011, I made it pretty clear that I supported Tsonis’ argument regarding climate shifts and a flat temperature trend for the next few decades”
https://judithcurry.com/2013/07/27/the-97-consensus-part-ii/#comment-353668
“This period since 2002 is scientifically interesting, since it coincides with the ‘climate shift’ circa 2001/2002 posited by Tsonis and others. This shift and the subsequent slight cooling trend provides a rationale for inferring a slight cooling trend over the next decade or so, rather than a flat trend from the 15 yr ‘pause’.”
https://judithcurry.com/2013/06/14/week-in-review-3/
In mid-2018:
“It is possible that a shift to the cold phase of the AMO is underway, which would extend the warming hiatus for ~2 decades.”
https://twitter.com/curryja/status/1019669373471010816
http://blamethenoctambulantjoycean.blogspot.com/2020/02/myth-ipccs-02cdecade-model-based_10.html
Good grief, Russell:
Writing “history” has gotta be more fun when you can make it up out of whole cloth. Get a blog, name it “Quadrant”, indulge your paranoid imagination free of mere facts.
History is only what we agree to remember, ya know?
jgnfld @30,
Thanks for the nod. Via Nature, the appearance of the full paper Bova et al (2021) ‘Seasonal origin of the thermal maxima at the Holocene and the last interglacial’ wasn’t happening a day or so back; it was just hitting the paywall.
Andy May here
https://wattsupwiththat.com/2021/02/02/climate-model-failure/?mc_cid=1f85683f49&mc_eid=63c915037a
shows other graphs on model predictions and observed temperatures.
Which graphs /which data are right?
[Response: The data underlying the graphs are correct, but they are plotted in ways that maximize the apparent difference. The same data is on our page, but plotted coherently. – gavin]
Wolfgang:
2 points:
1. NO models actually accepted as “skilled” (useful) predict .44/decade. Some scenarios do, of course, but scenarios are always based on published assumptions.
2. If you see a graph/graphic in ANY denier source purporting to
“prove” that “scientists are missing/lying about _____” you can pretty much assume you are looking at a graph/graphic that intentionally miscommunicates the actual science or the full, actual context of some particular research finding or data source. Sad. But true.
Wolfgang @38,
The graphics you link-to are not the work of Andy May who is an ex-oilman but now a “writer” although he may be better described as a drone worker on Willard’s rogue Planetoid Wattsupia.
The actual author of the graphics is the denialist John Christy who has a history of producing these graphics comparing models and measurements for a small part of the atmosphere, 9km to 10km over the tropics. This is the place where simple theory tells us that an increase in precipitation over the tropics due to warming (and it doesn’t have to be forced by GHGs) will release increasing levels of latent heat at altitude and thus an increased warming of the tropical upper troposphere.
The climate models show such a warming but measuring the actual warming isn’t unchallenging and do show a mismatch between model and measurement. (The graphic referred to & linked by Gavin @38Response is linked directly here).
Christy has been bashing on about this particular scientific situation for many years now in a particularly unscientific manner and has become entirely untrustworthy on the matter. How, for instance, do you measure the 300-200hpa temperatures which he appears to be doind to make his comparisons with model data. And regarding the particular scientific situation, there is a mass of reasons to suggest the problem is not with the models but with the assumption that the measurements are dependable.
And in a most timely manner, this month-old paper Vergados et al (2020) ‘Quantifying the Tropical Upper Tropospheric Warming Amplification Using Radio Occultation Measurements’ may have shot Christy’s fox. Radio Occultation (RO) appears to be tailor-made for measuring the likes of 300-200hpa tropical atmosphere and initial results… …let them speak for themselves:-
MA Rodger @40. Thanks for that link to Vergados. It may answer my ongoing question. It seems to me that the usual criticism of Christy’s graphs is how he chooses the starting point (correct me if I’m wrong). But, of course, if the trend is what’s important, then the starting point on the graph doesn’t matter. So I’ve been wondering, if the RSS and UAH methods are internally precise even if the accuracy is uncertain, isn’t the persistent discrepancy between the satellite and CIMP5 trends a genuine issue?
Speaking of the importance of trends, I always ask wouldn’t it be useful to present the GMST to CIMP5 trend comparison in the same histogram format presented for the satellites at the bottom of the comparison page? since the question is How Have the Model Projections Done? Maybe add a quantitative dimension to the claim the models are “skillful.”
41 MPassey says:
8 Feb 2021 at 3:19 PM
MA Rodger @40.
But, of course, if the trend is what’s important, then the starting point on the graph doesn’t matter.
This is denier-speak. Of course it matters. Do the math!
Ok and the light is in a much more greater model https://muchadoaboutclimate.wordpress.com/2013/08/03/4-5-billion-years-of-the-earths-temperature/ ,,,, the big picture !