Early 20th Century Warming – Polar Amplification, Model-Data & Model-Model Comparisons

A Guest Post By Bob Tisdale

In this post, we’re going to illustrate how poorly climate models used by the IPCC for their 5th Assessment Report simulate the polar amplification that data indicate took place during the early 20th Century warming period of 1916 to 1945.

This is part 2 of the post Global Mean Surface Temperature: Early 20th Century Warming Period – Models versus Models & Models versus Data (The WattsUpWithThat cross post is here). In that post, using the GISS Land-Ocean Temperature Index (GISS LOTI) dataset, we determined the 30-year period that ended before 1950 with the highest warming rate. It was 1916 to 1945. See Figure 1.

Figure 1

If a graph of 30-year trends is new to you, see the discussion that follows “A note for newcomers” in the post linked above.

In that earlier post, based on the climate model outputs of the ensemble members stored in the CMIP5 archive with historic and RCP8.5 forcings, for the period of 1916-1945, we also identified (1) an ensemble member that ran warmest (GISS-E2-H p3), (2) one that ran cool (IPSL-CM5A-LR EM-1), (3) the ensemble member with the highest trend (IPSL-CM5A-LR EM-2), and (4) the one with the lowest trend (CMCC-CMS), the last of which presented a cooling (yes, cooling) rate of -0.055 deg C/decade during a 30-year period when data indicate global surfaces warmed at a rate of about +0.15 deg C/decade.

AN OVERVIEW OF POLAR AMPLIFICATION

Polar Amplification refers to a natural phenomenon through which surfaces at high latitudes of the Northern Hemisphere warm [cool] at rates that are noticeably higher than the warming [cooling] trend for the rest of the globe.

Yes, data indicate that polar amplification will occur during a period of global cooling and result in excessive cooling in the high latitudes of the Northern Hemisphere, as was experienced in the mid-20th Century. See the 2012 post Polar Amplification: Observations Versus IPCC Climate Models (WattsUpWithThat cross post is here.)

THE SOURCE OF THE DATA AND MODEL OUTPUTS…

…presented in this post is the KNMI Climate Explorer.

MODEL-DATA COMPARISONS OF POLAR AMPLIFICATION

The best way I’ve found to illustrate the effects of polar amplification is by plotting the latitude-averaged surface temperatures trends for the period in question. See Figure 2. It is a graph that compares the observed global mean surface temperatures trends and those of the multi-model mean of CMIP5 climate models outputs, both on a zonal-mean basis. (Instead of latitude average, the climate science industry uses the term zonal mean.) The observations-based data are represented GISS Land-Ocean Temperature Index (GISS LOTI) dataset, and the models are represented by multi-model mean of the climate model simulations of global surface temperatures based on the models stored in the CMIP5 archive with historic and RCP8.5 (worst case) forcings.

Figure 2

The curve of the data during the early 20th Century warming period of 1916 to 1945 (solid grey curve) shows a classic example of polar amplification. After the mid-latitudes of the Northern Hemisphere, the warming rates climb higher and higher as the data near the North Pole…but then suddenly stop. On the other hand, the average of the climate model outputs (the multi-model mean, which is presented as the orangey dashed curve) shows little to no polar amplification during this period.

I present the model mean because it represents the consensus (groupthink) of the climate modeling groups for how surface temperatures should warm if they were warmed by the numerical representations of the forcings that are used to drive the models. Because the models couldn’t simulate the warming that took place during this period at most latitudes (other than the slight warming at about 60S latitude, where the model and data curves intersect) the warming must have occurred naturally.

NOTE: If a graph of near-surface temperature trends on a zonal-mean (latitude-average) basis is new to you, don’t worry…it’s easy to understand. The units for the vertical (y) axis are in deg C per decade (deg C/decade), so the data points represent the trends in surface temperatures (the warming and cooling rates). The horizontal (x) axis is latitude, with the South Pole at -90 (90S), the North Pole at 90 (90N) and with the equator at 0. To create a graph like the one shown in Figure 2, temperature data are downloaded in 5 degree latitude bands. For the graphs in this post, the trends start at -62.5 (62.5S), because there is no observations-based data available from Antarctica before the early 1950s. Those first data points at 62.5S are based on surface temperature data for the latitudes of 65S-60S. The next data points at 57.5S are based on the surface temperatures for the latitude band of 60S-55S. The process continues in 5-degree latitude bands northward toward the North Pole. [End note.]

Figures 3 through 6 present the model-data comparisons using the same observations-based data as Figure 2. They also include the 4 ensemble members we isolated in the post Global Mean Surface Temperature: Early 20th Century Warming Period – Models versus Models & Models versus Data. I’m not going to bother to comment on them individually. You’ll see why.

Figure 3

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Figure 4

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Figure 5

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Figure 6

A COUPLE MORE ENSEMBLE MEMBERS

There are 4 ensemble members at the KNMI Climate Explorer for the runs of the IPSL-CM5A-LR model. When asking for the outputs of a model in anomaly form, the KNMI Climate Explorer provides the outputs of all ensemble members in sequence, so they are easily isolated from one another. As a result I had two more ensemble members of the IPSL-CM5A-LR model on file in MS EXCEL. They are identified at the KNMI Climate Explorer as IPSL-CM5A-LR EM-0 and IPSL-CM5A-LR EM-3. Their simulations of global mean surface temperature trends on a zonal-mean basis for the period of 1916-1945 are presented below in the format of this post as Figures 7 and 8.

Figure 7

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Figure 8

Figure 9 is a spaghetti graph that shows the curves of all of the ensemble members presented in this post. I’ve included it to counter any erroneous impressions created by the model-mean presented in Figure 3. The only thing consistent about the ensemble members of the CMIP5 archive shown in this post is their inconsistency when attempting to simulate global mean surface temperatures and resulting polar amplification during the early 20th Century warming period of 1916 to 1945.

Figure 9

NEXT IN THIS SERIES

The next two posts in this series will examine climate model outputs and compare them to data during the 30-year mid-20th Century cooling period with the lowest linear trend.

BOTTOM LINE

In the following, I’ve initially repeated the closing comments from the earlier post in this series.

For the early 20th Century 30-year warming period of 1916-1945, climate models are consistently horrible and consistently inconsistent at simulating the primary metric of human-induced climate change, which is global mean surface temperature.

And, surprisingly, based on those horrendous excuses for climate models, we’re supposed to believe their crystal-ball like prognostications of future global mean surface temperatures and other climate metrics!!?? Fat chance of that happening with anyone who has a spark of common sense. If only more persons understood how poorly climate models simulated global mean surface temperatures—the primary metric of human-induced climate change—the human-induced global warming scare might just disappear into the past like the Y2K scare. Then again, the global warming/climate change scare has nothing to do with science; it is simply global politics at its worst, masquerading as science.

The IPCC couldn’t be a scientific entity. No scientific entity would set its foundation on models that perform as badly as this. The climate models stored in the CMIP5 archive should be presented as examples of failed attempts to simulate Earth’s climate, not used for government policy.

That’s it for this post. Enjoy yourself in the comments and have a wonderful remainder of your day.

STANDARD CLOSING REQUEST

Please purchase my recently published ebooks. As many of you know, last year I published 2 ebooks that are available through Amazon in Kindle format:

And please purchase Anthony Watts’s et al. Climate Change: The Facts – 2017.

To those of you who have purchased them, thank you. To those of you who will purchase them, thank you, too.

Regards,

Bob Tisdale

 

36 thoughts on “Early 20th Century Warming – Polar Amplification, Model-Data & Model-Model Comparisons

  1. You’re wasting your time. Haven’t you heard? The UK Met Office said today that we’re on track for the hottest decade evah! And we could pass a tipping point only FIVE YEARS FROM NOW! We … must … cease … all CO2 emissions immediately, repeat, IMMEDIATELY or …. we’re … all … gonna die.

    • brian,
      We are past the tipping point and we are all going to die — of cold.
      Have a look at this temp map: http://wxmaps.org/

      The cold that was in the upper Midwest has migrated 1,500 miles westward.
      Three states are below 0°F (-18°C).
      At KELN Ellensburg it is 5°F at 9 PM.

      ~~~~~~~
      Thanks, Bob T.

  2. Well… it is interesting, for sure.
    But does it really mean anything?

    After all, we just had a nice article showing a rather conspicuous lack of really big volcanoes to periodically cool things down every half century, in the last one.

    What happens when a few of these slumbering giants blow off steam?

    Just saying,
    GoatGuy

  3. Explicit modelling going to implicit modelling is common in the exploration and mining sectors of the resource industry – perhaps the IPCC chappies could give us a call. Our models are proof tested through the abundant use of the rotary lie detector. Plenty of failures and plenty of revision – marvellous how failures lead to enhanced discipline and better outcomes, especially when there are significant dollars at risk.

    • For the life of me, I can’t see how implicit models can be used for climate science. link

      The main problem is that the climate is the prototypical chaotic system. link The other problem is that some of the time constants involved are centuries long and we have less than two centuries worth of reliable data. The result is that climate models are no better than glorified exercises in curve fitting.

  4. Better models are required for past temperatures. Currently, past temperatures are in a constant state of flux with endless revisions. Unless climate scientists can get a better grasp of how past temperatures change with time, it will be impossible to predict future temperatures.
    Based on Tony Heller’s work, it seems that CO2 cools past temperatures. Our ancestors are facing an increasing risk of severe cold as CO2 levels rise.

    • I hear (somewhere around here) that the current models do at lot better at “simulating” actual temperature trends if you just change ONE little thing…

      You turn off the “CO2 sensitivity” parameters.

    • In fairness, he didn’t just compare models to reality he also compared the models to each other.
      And they don’t even agree with themselves.

    • Which implies that “scientific” models should never be compared to observations.

      That’s reassuring 🙂

      Cheers

      M

    • ?? This can’t be the real Mosher ??

      I had a “scientist” friend who said the same thing about a Lindzen presentation…”I don’t like his focus on prediction”.

      This is what happens when people who are computer programmers are considered “scientists” and “engineers.” So much for Empiricism.

    • Mosher
      It’s too embarrassing to compare
      models with observations !

      And then never change the models,
      so they stop predicting 2.5x to 3x
      the warming that actually happens !

      They are not “models” of any
      climate change process on this planet,
      because they are not even in the ballpark
      of making accurate predictions.

      They are failed prototypes,
      built by people who never
      ‘go back to the drawing board,
      averaging about +3 degrees C.
      per CO2 doubling, when actual
      warming is +1 degree per CO2 doubling,
      ( and there’s no scientific proof
      CO2 caused ANY of the warming
      since 1950 — that’s just an assumption
      used for (wrong) wild guesses
      of the future climate ).

      50 years of wrong wild guesses
      so far — only a stupid head would take
      the predictions of a coming climate
      change catastrophe seriously,
      or a leftist (I repeat myself)

  5. “I present the model mean because it represents the consensus (groupthink) of the climate modeling groups for how surface temperatures should warm if they were warmed by the numerical representations of the forcings that are used to drive the models”

    err. no. thats not what the mean represents. strawmanning again

    • I’m curious, what does the mean actually represent?

      The average outcome of the models if all the assumptions are made? That’s what I suspect it represents but that doesn’t seem to have any use or meaning.

      What do you suspect it represents?

    • Mosher
      Better to cherry pick the “best” model,
      that comes closest to a decent
      climate prediction, and ignore
      all the other wild guess models ?

      Since climate change physics are not known,
      other than a list of suspects,
      it is impossible to build a climate change
      model that predicts the future climate
      based on the science, rather than a lucky guess.

      If any of the climate models DID seem to make
      a good prediction, it would just be by chance,
      not by design.

    • This came up a few weeks ago…despite the publication in question being from 2018, mosh said this has been known for over a decade or something but that nobody knew how to address it lol.

  6. Bob, another fascinating article. Just wondering… do you have a graph of the zonal trend 1916 – 1945 overlaid with the zonal trend 1970 – 1997 (or whatever years cover the highest recent rate of warning)? It would be interesting to compare the two.

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